question string | answer string | source_file string | module_name string | tool_name string | tool_parameters list | tool_result string | category string | subcategory string | difficulty string | question_hash string | stage1_target string | stage2_context string | plan_id string | design_id string | split string | writer_model string | n_calls int64 | ctx_cap int64 | source dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
For the axil_cdc module, how do the current delay and power results compare with what the delay-focused optimization suggests could be achieved, and what cell-level structure underlies those numbers? | Synthesis currently reports a delay of 61.56 and power of 0.002 for axil_cdc, built from just 2 cells (one axil_cdc_rd and one axil_cdc_wr) with 42 wires. The delay-targeted optimization estimates it could reduce delay by -20.0 percent, at the cost of about 10.0 percent more area and 5.0 percent higher power, suggestin... | github_repos/corundum_corundum/fpga/lib/axi/rtl/axil_cdc.v | axil_cdc | optimization_advisor+synthesis_tool | [
{
"target_metric": "delay"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top axil_cdc",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"descr... | multi_tool | optimization_advisor+synthesis_tool | compositional | 60acd4b6a528 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the axil_cdc module, how do the current delay and power results compare with what the delay-focused optimization suggests could be achieved, and what cell-level structure underlies those numbers?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"rec... | 4a0836c05f98 | 005dc1828524 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/axi/rtl/axil_cdc.v",
"sha256": "fbb8018e34b7173e9a8de97c9e70be092abbb9a581dc83ec037561f401d11edb"
} |
For the ct_lsu_lm module, how complex is the design structurally, and what delay-focused optimization is recommended, including the expected trade-offs? | ct_lsu_lm has 426 lines of code, cyclomatic complexity 53, nesting depth 10, and 2166 operators, with 34 inputs and 16 outputs across 50 total ports. A delay optimization is recommended with an estimated delay improvement of -20.0 at the cost of 10.0 area increase and 5.0 power increase, suggesting pipelining arithmeti... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_lm.v | ct_lsu_lm | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_lsu_lm",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"desc... | multi_tool | optimization_advisor+static_analyzer | compositional | 1332462ee20a | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ct_lsu_lm module, how complex is the design structurally, and what delay-focused optimization is recommended, including the expected trade-offs?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_lsu_lm"... | 1d3b77f2b4e7 | 0036dd6de909 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_lm.v",
"sha256": "983cea5f7ee969d1794e5b59c4eb237f61bb3ad9abf06b63fd26101fb930d8d4"
} |
For system_top, I'd like a quick consistency check: how do the port counts and complexity look, and do the unmapped RTL signals from the RTL-to-netlist mapping match what the DFG shows for the ADC I/O buffers? | The static analysis reports 27 total ports (3 inputs, 5 outputs, 19 inouts) with cyclomatic complexity 1 and 393 operators over 109 lines of code, while the mapping found 11 of 14 RTL signals mapped (alignment score 78.57) with adc_gpio_o, adc_gpio_i, and adc_gpio_t unmapped. The DFG for system_top has 37 nodes and 373... | github_repos/analogdevicesinc_hdl/projects/cn0579/coraz7s/system_top.v | system_top | cross_stage_mapper+graph_extractor+static_analyzer | [
{},
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"adc_gpio_o": [],
"adc_gpio_i": [],
"shutdown_n": [
"shutdown_n"
],
"spi_clk": [
"spi_clk"
],
"ready_in": [
"ready_in"
],
"gpio_i": [
"gpio_i"
],
"clk_in": [
...[13 ch... | multi_tool | cross_stage_mapper+graph_extractor+static_analyzer | compositional | 1987004535d6 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For system_top, I'd like a quick consistency check: how do the port counts and complexity look, and do the unmapped RTL signals from the RTL-to-netlist mapping match what the DFG shows for the ADC I/O buffers?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"adc_gpio_o": []... | a365488d4e73 | 00400c8da762 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/cn0579/coraz7s/system_top.v",
"sha256": "a0589de5035cc348a8366ea68af9e6c09894c682f7bb609204d4b0e6194cffa7"
} |
For the axis_rate_limit module, given the RTL-to-netlist mapping results and the power-focused optimization analysis, summarize how well the RTL signals carried through to the netlist and what power improvement could be expected if the recommended clock-gating and operand-isolation changes were applied. | In the mapping for axis_rate_limit, 23 of the 36 RTL signals were mapped while 13 remained unmapped, giving an alignment score of 63.89. The power optimization analysis recommends clock gating and operand isolation and estimates a power improvement of -25.0, though with trade-offs such as possible area overhead and add... | github_repos/alexforencich_verilog-ethernet/lib/axis/rtl/axis_rate_limit.v | axis_rate_limit | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "power"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"s_axis_tready_reg": [],
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"m_axis_tvalid": [
"m_axis_tvalid_int",
"m_axis_tvalid",
"m_axis_tvalid_next",
"temp_m_axis_tvalid_next"... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | afdbb95498ce | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the axis_rate_limit module, given the RTL-to-netlist mapping results and the power-focused optimization analysis, summarize how well the RTL signals carried through to the netlist and what power improvement could be expected if the recommended clock-gating and operand-isolation changes were applied.
[cro... | 2c4348697af2 | 003256a861cd | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "lib/axis/rtl/axis_rate_limit.v",
"sha256": "bdfb4e29768c5224c543098765b8d648f3fe774eb42643c289d85b446414d155"
} |
For the fec_rot_1 module, how does the number of XOR nodes in its CDFG compare to the gate-level implementation after medium-level optimization, and what are the resulting area, delay, and power figures? | The CDFG of fec_rot_1 contains 4 $xor nodes among its 6 total nodes with 12 edges, and after medium-level optimization this maps directly to 4 $_XOR_ gates, matching the cell breakdown exactly. The synthesized design reports an area of 8.0, a delay (critical path estimate) of 121.26, and a power of 0.004. There are als... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/ethernet_fec/fec_rot_1.v | fec_rot_1 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[3000 chars elided]...
"node_count": 6,
"edge_count": 12,
"graph_properties": {
"node_types": {
"$xor": 4,
"port_input": 1,
"port_output": 1
},
"avg_degree": 2.0,
"module_name": "fec_rot_... | multi_tool | graph_extractor+synthesis_tool | compositional | a7ec5ee79a4a | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fec_rot_1 module, how does the number of XOR nodes in its CDFG compare to the gate-level implementation after medium-level optimization, and what are the resulting area, delay, and power figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[3000 chars ... | 26599f3db7a2 | 01156403d141 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/ethernet_fec/fec_rot_1.v",
"sha256": "04d729f6f74fafdde4b7e83036d676103e79f8b74efc62ec7f6d041806f82289"
} |
For the module fec_rot_1, the CDFG analysis shows four $xor operators feeding the output port — how do those operators relate to each other, and if I apply the recommended area optimization with resource sharing, what improvement can I expect and what trade-off should I watch for? | The CDFG for fec_rot_1 has 6 nodes and 12 edges (average degree 2.0), with four $xor operators plus one input and one output port, so sharing those XORs via the suggested resource_sharing recipe ('share -aggressive') is the natural fit. The area-targeted optimization estimates an area improvement of -15.0 and power of ... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/ethernet_fec/fec_rot_1.v | fec_rot_1 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[3000 chars elided]...
"node_count": 6,
"edge_count": 12,
"graph_properties": {
"node_types": {
"$xor": 4,
"port_input": 1,
"port_output": 1
},
"avg_degree": 2.0,
"module_name": "fec_rot_... | multi_tool | graph_extractor+optimization_advisor | compositional | 6330c21264e2 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the module fec_rot_1, the CDFG analysis shows four $xor operators feeding the output port — how do those operators relate to each other, and if I apply the recommended area optimization with resource sharing, what improvement can I expect and what trade-off should I watch for?
[graph_extractor {"graph_ty... | 294b843cc11c | 01156403d141 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/ethernet_fec/fec_rot_1.v",
"sha256": "04d729f6f74fafdde4b7e83036d676103e79f8b74efc62ec7f6d041806f82289"
} |
For the axis_switch module, can you summarize its RTL structure and how well that structure carried over to the netlist, including its complexity, its port and signal makeup, and how many RTL signals actually mapped to netlist wires? | The axis_switch RTL has 318 lines of code with cyclomatic complexity 48, nesting depth 37, and 526 operators, and it exposes 23 ports total (12 inputs and 11 outputs) with 4 wires and 4 regs. In the cross-stage mapping, only 4 of the 12 RTL signals mapped to the netlist (which contains 6701 netlist wires), leaving 8 un... | github_repos/alexforencich_verilog-ethernet/lib/axis/rtl/axis_switch.v | axis_switch | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"grant_valid": [],
"rst": [
"rst"
],
"wire": [],
"tid": [
"s_axis_tid",
"int_s_axis_tid",
"m_axis_tid"
],
"clk": [
"clk"
],
"m_axis_tvalid_mux": [],
"m_axis_tready_mux": [... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 4f9481211897 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axis_switch module, can you summarize its RTL structure and how well that structure carried over to the netlist, including its complexity, its port and signal makeup, and how many RTL signals actually mapped to netlist wires?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping"... | 1b8cf0787368 | 019f0b716455 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "lib/axis/rtl/axis_switch.v",
"sha256": "ccfe5eb62d5fead748bca36f22a0012599af46d2ec486c1bb091308234510e6f"
} |
For the axis_arb_mux module, how do its complexity characteristics relate to the delay-optimization recommendations, and is the suggested trade-off acceptable given the module's size? | The axis_arb_mux module is fairly large and complex, with 239 lines of code, cyclomatic complexity 21, 352 operators, 32 total ports, and 4 always blocks, which supports the delay-focused suggestions to pipeline arithmetic via register retiming and duplicate logic to cut fanout. The estimated improvement is a 20.0% del... | github_repos/corundum_corundum/fpga/lib/eth/lib/axis/rtl/axis_arb_mux.v | axis_arb_mux | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top axis_arb_mux",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"d... | multi_tool | optimization_advisor+static_analyzer | compositional | 588fb259da3a | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axis_arb_mux module, how do its complexity characteristics relate to the delay-optimization recommendations, and is the suggested trade-off acceptable given the module's size?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes... | ed0be9b2b62b | 01ff01fee60e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/lib/axis/rtl/axis_arb_mux.v",
"sha256": "2e71c10f54a03375e7b9e2f6ae559a0c122715297d6db75a764c0db70701108b"
} |
For the module mac_pause_ctrl_rx, how do its structural complexity from the full static analysis and its synthesized implementation characteristics compare — is the design control-heavy or datapath-heavy, and what does that imply for its area and delay-optimized synthesis results? | mac_pause_ctrl_rx is clearly control-heavy: with only 245 $_SDFF_PP0_ flops out of 2765 total cells and 832 $_AND_ plus 746 $_NAND gates dominating the combinational logic, most silicon goes to random control logic rather than datapath. This matches the source-level view of 2 always blocks, 10 assign statements, cyclom... | github_repos/alexforencich_verilog-ethernet/rtl/mac_pause_ctrl_rx.v | mac_pause_ctrl_rx | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "mac_pause_ctrl_rx",
"port_count": {
"inputs": 18,
"outputs": 10,
"inouts": 0,
"total": 28
},
"signal_count": {
"wires": 27,
"regs": 8,
"parameters": 3,
"total": 35
},
"always_blocks": 2,
"a... | multi_tool | static_analyzer+synthesis_tool | compositional | a5a069407599 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module mac_pause_ctrl_rx, how do its structural complexity from the full static analysis and its synthesized implementation characteristics compare — is the design control-heavy or datapath-heavy, and what does that imply for its area and delay-optimized synthesis results?
[static_analyzer {"analysis... | ac063545a201 | 0208353faf8d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/mac_pause_ctrl_rx.v",
"sha256": "4b8d5d985fe5e7d3ec28f0c70a8c212fb7b3df6548cbf4dcaac2473a23b24a57"
} |
For the uclock module, how does the structure seen in the AIG graph of the instantiated RAM block relate to the complexity metrics reported by the static analysis, and is there anything in the lint results to worry about? | The uclock module instantiates a single RAMB16_S18 in the AIG, giving 4 nodes and 50 edges with an average degree of 12.5, while the static analysis shows only 2 inputs and 1 output (3 ports total), 0 always blocks and 0 assign statements, with a cyclomatic complexity of 1 across 88 lines of code and 222 operators. The... | github_repos/pConst_basic_verilog/pacoblaze-2.2/pacoblaze/uclock.v | uclock | graph_extractor+static_analyzer | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[4190 chars elided]...
"node_count": 4,
"edge_count": 50,
"graph_properties": {
"node_types": {
"RAMB16_S18": 1,
"port_input": 2,
"port_output": 1
},
"avg_degree": 12.5,
"module_name": "ucl... | multi_tool | graph_extractor+static_analyzer | compositional | 4a1f5d39d850 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the uclock module, how does the structure seen in the AIG graph of the instantiated RAM block relate to the complexity metrics reported by the static analysis, and is there anything in the lint results to worry about?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",... | 16eff6067783 | 0234b1c0fe61 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "pacoblaze-2.2/pacoblaze/uclock.v",
"sha256": "2a73beb76a7f2b364f8e18047a7dcf71f3bda1a07dd772ae1dd9ec6acc40b118"
} |
For the uclock module, how does the area optimization trade off against delay and power, and how does that relate to the structure shown in its AIG graph? | The AIG for uclock contains 4 nodes and 50 edges with an average degree of 12.5, including a single RAMB16_S18 block, 2 input ports, and 1 output port. Running the recommended area optimization flow (such as flatten, share -aggressive, and opt_clean -purge) is estimated to improve area by -15.0 and power by -10.0, but ... | github_repos/pConst_basic_verilog/pacoblaze-2.2/pacoblaze/uclock.v | uclock | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[4190 chars elided]...
"node_count": 4,
"edge_count": 50,
"graph_properties": {
"node_types": {
"RAMB16_S18": 1,
"port_input": 2,
"port_output": 1
},
"avg_degree": 12.5,
"module_name": "ucl... | multi_tool | graph_extractor+optimization_advisor | compositional | 9818df2d111d | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the uclock module, how does the area optimization trade off against delay and power, and how does that relate to the structure shown in its AIG graph?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[4190 chars elided]...
"node_count": 4,
"edge_count": 50,
... | 6b2a9b76a9d1 | 0234b1c0fe61 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "pacoblaze-2.2/pacoblaze/uclock.v",
"sha256": "2a73beb76a7f2b364f8e18047a7dcf71f3bda1a07dd772ae1dd9ec6acc40b118"
} |
For pcileech_pcie_cfg_a7, if I apply the recommended area-focused optimization recipes, what impact should I expect on area, delay, and power, and how does that interact with the module's complexity as measured by its cyclomatic complexity and operator count? | The area optimization for pcileech_pcie_cfg_a7 is estimated to reduce area by -15.0 and power by -10.0, but increase delay by 5.0, with a trade-off that aggressive sharing increases routing complexity. This matters because the module is already complex, with a cyclomatic complexity of 24 and an operator count of 2001, ... | github_repos/ufrisk_pcileech-fpga/pciescreamer/src/pcileech_pcie_cfg_a7.sv | pcileech_pcie_cfg_a7 | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top pcileech_pcie_cfg_a7 -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
... | multi_tool | optimization_advisor+static_analyzer | compositional | eccfb1d65d1c | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For pcileech_pcie_cfg_a7, if I apply the recommended area-focused optimization recipes, what impact should I expect on area, delay, and power, and how does that interact with the module's complexity as measured by its cyclomatic complexity and operator count?
[optimization_advisor {"target_metric": "area"}]
... | bfd7a524d834 | 01c31ce8fc61 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/ufrisk/pcileech-fpga",
"commit": "c538c4170678c13f723dc921905fb81ff3c71d8e",
"path": "pciescreamer/src/pcileech_pcie_cfg_a7.sv",
"sha256": "f0e619b4a33cec0bccf444ac26792f01636ba7d27c0671e94bcaab8546d099a4"
} |
For the oh_oa32 module, how does the structure shown in its CDFG compare with the gate-level results after medium-level optimization for area and delay, and what do the two views tell us about the design overall? | The CDFG of oh_oa32 has 10 nodes and 12 edges, consisting of 1 $and, 3 $or, 5 input ports, and 1 output port with an average degree of 1.2, which matches the synthesized netlist exactly: 4 gates (1 $_AND_ and 3 $_OR_) with no restructuring during optimization. Synthesis reports an area of 4.0, a gate count of 4, a crit... | github_repos/aolofsson_oh/stdlib/rtl/oh_oa32.v | oh_oa32 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[2618 chars elided]...
"node_count": 10,
"edge_count": 12,
"graph_properties": {
"node_types": {
"$and": 1,
"$or": 3,
"port_input": 5,
"port_output": 1
},
"avg_degree": 1.2,
"module... | multi_tool | graph_extractor+synthesis_tool | compositional | 9b6ad744da0b | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_oa32 module, how does the structure shown in its CDFG compare with the gate-level results after medium-level optimization for area and delay, and what do the two views tell us about the design overall?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[26... | bd4e46e555c1 | 027a7ac58213 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_oa32.v",
"sha256": "664eb2c1501a6d5d2581ad071c4cc1b392ac8a96cab88fa828e6b80a00be45e5"
} |
For the module edma_dp, based on its CDFG structure and the delay-focused optimization advice, how concerned should I be about the high average fanout, and what trade-offs would the suggested delay optimizations bring? | The CDFG of edma_dp has 34 nodes and 793 edges with an average degree of 23.32, which is high fanout and explains why the delay optimization suggests logic duplication via "splitnets -driver" as well as pipelining the arithmetic operations using register retiming. Following those delay-oriented suggestions is estimated... | github_repos/aolofsson_oh/edma/hdl/edma_dp.v | edma_dp | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "delay"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[30552 chars elided]...
"node_count": 34,
"edge_count": 793,
"graph_properties": {
"node_types": {
"$mux": 6,
"$or": 1,
"$sub": 2,
"$add": 2,
"$dffe": 2,
"emesh2packet": 1,
"p... | multi_tool | graph_extractor+optimization_advisor | compositional | f64db53eb1c5 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the module edma_dp, based on its CDFG structure and the delay-focused optimization advice, how concerned should I be about the high average fanout, and what trade-offs would the suggested delay optimizations bring?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
... | 2dc7d5327114 | 02aafd3f71c9 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "edma/hdl/edma_dp.v",
"sha256": "20d40c73ef80e12368567a3fa41682a152fc056e6e5da9320512ad5b0f0a1727"
} |
For the mtx_fifo module, how well do the RTL signals survive into the netlist and how does that relate to the structure seen in its CDFG and the synthesis results — please summarize using the mapping score, unmapped signals, CDFG size, and area/delay/power figures. | The RTL-to-netlist mapping for mtx_fifo has an alignment score of 91.67 with 22 of 24 RTL signals mapped, leaving only emesh_cycle and emesh_wait unmapped. The CDFG has 40 nodes and 1530 edges, including 9 $mux and 8 port_input nodes, and synthesis at medium optimization yields an area of 811.5, delay of 402.28, power ... | github_repos/aolofsson_oh/mio/hdl/mtx_fifo.v | mtx_fifo | cross_stage_mapper+graph_extractor+synthesis_tool | [
{},
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"io_clk": [
"io_clk"
],
"clk": [
"io_clk",
"clk"
],
"valid": [
"valid",
"io_valid"
],
"fifo_data_in": [
"fifo_data_in"
],
"emesh_cycle": [],
"data_wide": [
...[545 c... | multi_tool | cross_stage_mapper+graph_extractor+synthesis_tool | compositional | 2f4fc322f201 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the mtx_fifo module, how well do the RTL signals survive into the netlist and how does that relate to the structure seen in its CDFG and the synthesis results — please summarize using the mapping score, unmapped signals, CDFG size, and area/delay/power figures.
[cross_stage_mapper {}]
{
"status": "succ... | 52b03c0fa34d | 02b188cc4361 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "mio/hdl/mtx_fifo.v",
"sha256": "f7e18ac8da531372bfb4c499bb217e70bf548fa46479a3489c1f70a77d398fef"
} |
For the module edma_dp, how does the structure seen in its dataflow graph (DFG) compare with its source-level complexity, and do any lint issues raise concerns? | The DFG for edma_dp has 34 nodes and 793 edges with an average degree of 23.32, dominated by 6 mux nodes, 2 adders and 2 subtractors, while the source has 84 lines of code, cyclomatic complexity 7, and 477 operators across 2 always blocks and 10 assign statements. With 12 input and 6 output ports and no lint warnings, ... | github_repos/aolofsson_oh/edma/hdl/edma_dp.v | edma_dp | graph_extractor+static_analyzer | [
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[30551 chars elided]...
"node_count": 34,
"edge_count": 793,
"graph_properties": {
"node_types": {
"$mux": 6,
"$or": 1,
"$sub": 2,
"$add": 2,
"$dffe": 2,
"emesh2packet": 1,
"pac... | multi_tool | graph_extractor+static_analyzer | compositional | a4b9fda68c64 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module edma_dp, how does the structure seen in its dataflow graph (DFG) compare with its source-level complexity, and do any lint issues raise concerns?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[30551 chars elided]...
"node_count": 34,
"edge_count... | 89d620a6f6c2 | 02aafd3f71c9 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "edma/hdl/edma_dp.v",
"sha256": "20d40c73ef80e12368567a3fa41682a152fc056e6e5da9320512ad5b0f0a1727"
} |
For the aes_256 module, can you summarize its structure by relating the port and cell hierarchy information to its AIG graph representation, including how many AES round stages appear in the graph? | The aes_256 module has 6 inputs and 3 outputs (9 total ports), 5 assign statements, and instantiates aes_round_256 among its 4 instantiations. Its AIG graph contains 916 nodes and 13082 edges with an average degree of 14.28, including 14 aes_round_256 nodes plus 384 AND gates and 512 NOT gates. | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crypto/aes/aes_256.v | aes_256 | graph_extractor+static_analyzer | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33435 chars elided]...
"node_count": 916,
"edge_count": 13082,
"graph_properties": {
"node_types": {
"$_AND_": 384,
"$_NOT_": 512,
"aes_round_256": 14,
"port_input": 4,
"port_output": 2
... | multi_tool | graph_extractor+static_analyzer | compositional | 69c5e7520ab6 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the aes_256 module, can you summarize its structure by relating the port and cell hierarchy information to its AIG graph representation, including how many AES round stages appear in the graph?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33435 chars elided]... | 234c037296c9 | 0311e75ae9b3 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crypto/aes/aes_256.v",
"sha256": "d583ef9948be20f305335a9475fb62244aa6a1b4bd0416a5ce58fbaed116199d"
} |
For the fpga module, how does the CDFG structure compare with the synthesis results in terms of size and connectivity, and what are the delay and power figures? | The CDFG of the fpga module has 32 nodes and 113 edges with an average degree of 3.53, while synthesis at medium optimization reports only 10 cells (gate_count 10, area 10.0) plus 38 wires and 80 wire bits, indicating most CDFG nodes are the 14 input ports and 7 output ports rather than logic. The critical path estimat... | github_repos/alexforencich_verilog-ethernet/example/ATLYS/fpga/rtl/fpga.v | fpga | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[15878 chars elided]...
"node_count": 32,
"edge_count": 113,
"graph_properties": {
"node_types": {
"$not": 2,
"$and": 1,
"$or": 1,
"BUFG": 1,
"DCM_SP": 1,
"IBUFG": 1,
"fpga_co... | multi_tool | graph_extractor+synthesis_tool | compositional | 7597bdc831a8 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fpga module, how does the CDFG structure compare with the synthesis results in terms of size and connectivity, and what are the delay and power figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[15878 chars elided]...
"node_count": 32,
"edge_cou... | 573d7be2213f | 032974379cfa | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/ATLYS/fpga/rtl/fpga.v",
"sha256": "960ca32f8ca762458b3f82768c7e835e12550afcd620b661a689d531ac2c1626"
} |
For the axis_broadcast module, how does the register-level structure seen in its DFG compare with the RTL complexity metrics, and how well did the RTL signals carry over to the netlist in terms of mapping coverage? | The axis_broadcast DFG contains 60 nodes and 288 edges including 9 register-type elements (6 $dffe, 2 $sdff, 1 $sdffe) with an average degree of 4.8, which is consistent with the RTL's 9 regs, 2 always blocks and cyclomatic complexity of 12. However, the RTL-to-netlist mapping only achieved an alignment score of 61.9 w... | github_repos/alexforencich_verilog-ethernet/lib/axis/rtl/axis_broadcast.v | axis_broadcast | cross_stage_mapper+graph_extractor+static_analyzer | [
{},
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"s_axis_tready_reg": [],
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"store_axis_input_to_temp": [
"store_axis_input_to_temp"
],
"in": [
"store_axis_input_to_temp",
...[700 c... | multi_tool | cross_stage_mapper+graph_extractor+static_analyzer | compositional | 6d859e013d78 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axis_broadcast module, how does the register-level structure seen in its DFG compare with the RTL complexity metrics, and how well did the RTL signals carry over to the netlist in terms of mapping coverage?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"s_axis_tre... | 4ff75e6cb22d | 032cbbcb5a44 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "lib/axis/rtl/axis_broadcast.v",
"sha256": "a644b7542adf7552cb4713ab22856e1b76c58780da970d122351e45bc0bc51bf"
} |
For the module crc24_dat64_only_flat, how does the gate-level structure seen in its CDFG compare with the synthesis results after medium-level delay and power optimization, and does anything in the source-level analysis explain that structure? | The CDFG of crc24_dat64_only_flat contains 726 nodes (724 $xor nodes plus one input and one output port) with 2172 edges and average degree 2.99, which matches synthesis results of 582 gates split into 425 XNOR and 157 XOR cells, giving an area of 1164.0, delay of 540.22, and power of 0.582. The static analysis confirm... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crc/crc24_dat64_only_flat.v | crc24_dat64_only_flat | graph_extractor+static_analyzer+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[67170 chars elided]...
"node_count": 726,
"edge_count": 2172,
"graph_properties": {
"node_types": {
"$xor": 724,
"port_input": 1,
"port_output": 1
},
"avg_degree": 2.99,
"module_name": "... | multi_tool | graph_extractor+static_analyzer+synthesis_tool | compositional | 4eb8010d89fa | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module crc24_dat64_only_flat, how does the gate-level structure seen in its CDFG compare with the synthesis results after medium-level delay and power optimization, and does anything in the source-level analysis explain that structure?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",... | 92f92551e5fd | 033f3e48d47c | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crc/crc24_dat64_only_flat.v",
"sha256": "9a3f0f0ec842fe616d833bd9054130a2de6266e3176ae0a93c922f5fe0263514"
} |
For the module ct_ifu_decd_normal, how does its structural complexity from the CDFG compare with its source-level complexity, and what does this suggest about the design? | The CDFG of ct_ifu_decd_normal contains 273 nodes and 3505 edges with an average degree of 12.84, dominated by 102 $eq and 101 $logic_or operations, while the source itself looks fairly simple with 319 lines of code, 29 assign statements, no always blocks, and a cyclomatic complexity of only 4. This contrast shows that... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/ifu/rtl/ct_ifu_decd_normal.v | ct_ifu_decd_normal | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[67082 chars elided]...
"node_count": 273,
"edge_count": 3505,
"graph_properties": {
"node_types": {
"$logic_and": 24,
"$eq": 102,
"$logic_or": 101,
"$logic_not": 7,
"$ne": 3,
"$red... | multi_tool | graph_extractor+static_analyzer | compositional | 2058080893cb | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module ct_ifu_decd_normal, how does its structural complexity from the CDFG compare with its source-level complexity, and what does this suggest about the design?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[67082 chars elided]...
"node_count": 273,
... | 4684ad59e829 | 034b39c6d6f2 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/ifu/rtl/ct_ifu_decd_normal.v",
"sha256": "17f475965e15af27ab44d9c91412f547bad3734510d7dabcc73cf1f00fbb0684"
} |
For asic_aoi33, considering its RTL structure and the cross-stage signal mapping results, is applying the area-focused optimization flow worthwhile, and what trade-offs should I expect? | asic_aoi33 is a tiny combinational cell (11 lines of code, 1 assign statement, cyclomatic complexity 1, 20 operators) with all 7 RTL signals mapping cleanly to the netlist at an alignment score of 100.0, so the suggested flow (flatten, share -aggressive, technology mapping, opt_clean -purge) would still deliver an esti... | github_repos/aolofsson_oh/asiclib/hdl/asic_aoi33.v | asic_aoi33 | cross_stage_mapper+optimization_advisor+static_analyzer | [
{},
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"a0": [
"a0"
],
"z": [
"z"
],
"a2": [
"a2"
],
"b0": [
"b0"
],
"b1": [
"b1"
],
"b2": [
"b2"
],
"a1": [
"a1"
]
},
"alignment_score": 100.0,
... | multi_tool | cross_stage_mapper+optimization_advisor+static_analyzer | compositional | 4f2bb14e7e5c | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For asic_aoi33, considering its RTL structure and the cross-stage signal mapping results, is applying the area-focused optimization flow worthwhile, and what trade-offs should I expect?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"a0": [
"a0"
],
"z": [
... | 04e9d310f01b | 036be0a4c9ae | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_aoi33.v",
"sha256": "3056d83cd2732a2210bba39d5209bbccd92dee5d505ae90b1bfa5449230e7e70"
} |
For crc24_dat64_only_flat, how does the area-focused optimization trade off against delay, given the structure of its AIG representation? | The AIG for crc24_dat64_only_flat contains 5070 nodes (2172 AND nodes, 2896 NOT nodes, plus 1 input and 1 output port) with 12308 edges and an average degree of 2.43. Applying the recommended area-oriented recipes, including aggressive resource sharing of arithmetic operators, is estimated to improve area by -15.0 and ... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crc/crc24_dat64_only_flat.v | crc24_dat64_only_flat | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33714 chars elided]...
"node_count": 5070,
"edge_count": 12308,
"graph_properties": {
"node_types": {
"$_AND_": 2172,
"$_NOT_": 2896,
"port_input": 1,
"port_output": 1
},
"avg_degree": 2... | multi_tool | graph_extractor+optimization_advisor | compositional | 87c5ee4ab94b | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For crc24_dat64_only_flat, how does the area-focused optimization trade off against delay, given the structure of its AIG representation?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33714 chars elided]...
"node_count": 5070,
"edge_count": 12308,
"graph_pr... | 1f2fa6a5e8ae | 033f3e48d47c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crc/crc24_dat64_only_flat.v",
"sha256": "9a3f0f0ec842fe616d833bd9054130a2de6266e3176ae0a93c922f5fe0263514"
} |
For the ct_had_private_ir module, how well did the RTL survive into the netlist, and given those results, is it worth applying the power-focused optimization suggestions like clock gating? | The RTL-to-netlist mapping for ct_had_private_ir achieved an alignment_score of 95.0 with 57 of 60 RTL signals mapped (only hacr_f, update_dr_ff1, and update_hacr_ff1 unmapped), so the netlist is a faithful starting point for optimization. The power-targeted optimization (clock gating plus operand isolation) estimates ... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/had/rtl/ct_had_private_ir.v | ct_had_private_ir | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "power"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"ir_xx_bypass_reg_sel": [
"ir_xx_bypass_reg_sel"
],
"bank1_sel": [
"bank1_sel"
],
"bank2_sel": [
"bank2_sel"
],
"ir_xx_dbgfifo_reg_sel": [
"ir_xx_dbgfifo_reg_sel"
],
"cpuclk": [
... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | 7f2de80e3f83 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the ct_had_private_ir module, how well did the RTL survive into the netlist, and given those results, is it worth applying the power-focused optimization suggestions like clock gating?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"ir_xx_bypass_reg_sel": [
"ir_x... | 40c53fcee28a | 04278c6fa62d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/had/rtl/ct_had_private_ir.v",
"sha256": "ede3e2e7447ece50fbfbbc92178f7568afdc97404fc2287d1bebe7a529799bd6"
} |
For the axis_xgmii_tx_64 module, the CDFG shows a lot of multiplexing and arithmetic logic while the area-focused optimization run suggests aggressive resource sharing; based on the CDFG structure and the estimated area/power/delay effects, is aggressive sharing a reasonable choice here and what should be watched out f... | The CDFG for axis_xgmii_tx_64 contains 212 nodes and 6371 edges (average degree 30.05) with 61 $mux and 17 $pmux nodes plus 6 $sub and 6 $gt operators, so sharing multiplexers and arithmetic operators has real potential. The area optimization estimates -15.0% area and -10.0% power but +5.0% delay, and the noted trade-o... | github_repos/alexforencich_verilog-ethernet/rtl/axis_xgmii_tx_64.v | axis_xgmii_tx_64 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[57696 chars elided]...
"node_count": 212,
"edge_count": 6371,
"graph_properties": {
"node_types": {
"$mux": 61,
"$not": 16,
"$logic_not": 4,
"$logic_and": 2,
"$logic_or": 3,
"$gt":... | multi_tool | graph_extractor+optimization_advisor | compositional | 13844a8942d2 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the axis_xgmii_tx_64 module, the CDFG shows a lot of multiplexing and arithmetic logic while the area-focused optimization run suggests aggressive resource sharing; based on the CDFG structure and the estimated area/power/delay effects, is aggressive sharing a reasonable choice here and what should be wat... | a28f7fb3b13f | 03e99aadb78f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/axis_xgmii_tx_64.v",
"sha256": "e65559d1aad43507629efa1b54e59a9bfa650ee2e06f1ead8451c1b4134fe8e2"
} |
For cpu_mem_icg_check_top, given its power optimization advice and its structural profile (195 lines of code, cyclomatic complexity 19, 11 instantiations, 8 wires), is the recommended clock gating worth pursuing, and what power improvement is estimated? | Yes — the power analysis recommends clock gating for registers plus operand isolation, with an estimated power improvement of -25.0, though it warns of added area overhead and timing complexity. Structurally, cpu_mem_icg_check_top has 195 lines of code, cyclomatic complexity 19, nesting depth 24, 8 wires, 0 regs, and 1... | github_repos/XUANTIE-RV_openc910/smart_run/impl/mem_icg_test/cpu_mem_icg_check_top.v | cpu_mem_icg_check_top | optimization_advisor+static_analyzer | [
{
"target_metric": "power"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top cpu_mem_icg_check_top",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "... | multi_tool | optimization_advisor+static_analyzer | compositional | 49093c556cfb | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For cpu_mem_icg_check_top, given its power optimization advice and its structural profile (195 lines of code, cyclomatic complexity 19, 11 instantiations, 8 wires), is the recommended clock gating worth pursuing, and what power improvement is estimated?
[optimization_advisor {"target_metric": "power"}]
{
"... | 7c5ac463c2cf | 040ae23d3cc4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "smart_run/impl/mem_icg_test/cpu_mem_icg_check_top.v",
"sha256": "3c2c5dcd224e8a8b6b475ef4d3d11b4749f1b50c77e1fe974d9c71c1f5e0bab5"
} |
For the dut module, the CDFG analysis reports a highly connected graph (448 edges over 18 nodes) — how does that connectivity compare to what was actually synthesized, given the RTL-to-netlist signal mapping and the synthesis results for gate count, delay, and power? | Despite the CDFG for dut having 448 edges over 18 nodes with an average degree of 24.89, synthesis produced a very small netlist of only 14 gates (5 $_AND_, 6 $_NOR_, 1 $_NAND_, 1 $_ANDNOT_, plus the edma instance), and the RTL-to-netlist mapping shows all 12 RTL signals mapped with a 100.0 alignment score and 0 unmapp... | github_repos/aolofsson_oh/edma/dv/dut_edma.v | dut | cross_stage_mapper+graph_extractor+synthesis_tool | [
{},
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"edma_access_in": [
"edma_access_in"
],
"reg_wait_in": [
"reg_wait_in"
],
"nreset": [
"nreset"
],
"reg_access_out": [
"reg_access_out"
],
"reg_access_in": [
"reg_access_in"
... | multi_tool | cross_stage_mapper+graph_extractor+synthesis_tool | compositional | ef5ebb87489e | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the dut module, the CDFG analysis reports a highly connected graph (448 edges over 18 nodes) — how does that connectivity compare to what was actually synthesized, given the RTL-to-netlist signal mapping and the synthesis results for gate count, delay, and power?
[cross_stage_mapper {}]
{
"status": "su... | 67363b68e1ef | 04ab15ffca83 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "edma/dv/dut_edma.v",
"sha256": "91d73e540c961e1b6185f324f82a3224095c790e058a0a6af03aaf8e96a30c9e"
} |
For the oh_reg1 module, given its cross-stage signal mapping results and its code structure analysis, how well do the RTL signals align with the netlist, and which specific input is the cause of any mismatch relative to the module's 4 input ports? | The mapping achieved an alignment score of 75.0, with 3 of 4 RTL signals mapped and only the data input left unmapped. Structurally, oh_reg1 has 4 inputs and 1 output among its 5 total ports, contains 1 always block and 1 assign statement, and reaches a cyclomatic complexity of 7 with a nesting depth of 3 across 35 lin... | github_repos/aolofsson_oh/stdlib/rtl/oh_reg1.v | oh_reg1 | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"en": [
"en"
],
"clk": [
"clk"
],
"nreset": [
"nreset"
],
"data": []
},
"alignment_score": 75.0,
"unmapped_elements": [
"data"
],
"mapping_statistics": {
"rtl_signals": 4,
"... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 52a704c39f35 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_reg1 module, given its cross-stage signal mapping results and its code structure analysis, how well do the RTL signals align with the netlist, and which specific input is the cause of any mismatch relative to the module's 4 input ports?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_ne... | f2f813448f35 | 043586e54a0e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_reg1.v",
"sha256": "60e1bd5ace98a71458f37b128ca37dcaa80f332cea9864b032a76e705e48b34f"
} |
For the debounce_switch module, how does the structure of its CDFG (nodes, edges, node types) relate to its overall code complexity, and does the high average connectivity suggest the module is complex for its size? | The CDFG for debounce_switch has 18 nodes and 470 edges with an average degree of 26.11, dominated by 3 muxes, 2 adffe registers, and 1 adff, which reflects the module's cyclomatic complexity of 13 and nesting depth of 12 across 73 lines of code with 77 operators. The dense connectivity relative to the small node count... | github_repos/corundum_corundum/fpga/lib/pcie/example/S10DX_DK/fpga/rtl/debounce_switch.v | debounce_switch | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[24973 chars elided]...
"node_count": 18,
"edge_count": 470,
"graph_properties": {
"node_types": {
"$lt": 1,
"$add": 1,
"$logic_not": 2,
"$reduce_or": 1,
"$eq": 1,
"$reduce_and": 1,... | multi_tool | graph_extractor+static_analyzer | compositional | 44d8cf1e94dd | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the debounce_switch module, how does the structure of its CDFG (nodes, edges, node types) relate to its overall code complexity, and does the high average connectivity suggest the module is complex for its size?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...... | d23bc314f984 | 052745db4692 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/S10DX_DK/fpga/rtl/debounce_switch.v",
"sha256": "02d6ba80136cb9be942347e33c43881f465acbfc4f41b6af3a32d41c86b4ef5a"
} |
For the ct_lsu_mcic module, compare the RTL-to-netlist signal mapping coverage with the synthesis results: how well do the RTL signals carry into the netlist, and how does that relate to the synthesized gate count and area? | In ct_lsu_mcic, 32 of 33 RTL signals map into the netlist (alignment score 96.97) with only mcic_ar_id_vld unmapped, while synthesis produces 432 gates (e.g., 131 NAND and 128 ORNOT cells plus 8 DFFE_PN0P_ and 1 gated_clk_cell) at an area of 504.0. This indicates nearly complete mapping coverage despite the netlist exp... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_mcic.v | ct_lsu_mcic | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"mcic_dcache_arb_ld_req": [
"mcic_dcache_arb_ld_req"
],
"lsu_mmu_bus_error": [
"lsu_mmu_bus_error"
],
"cp0_yy_clk_en": [
"cp0_yy_clk_en"
],
"ld_da_mcic_data_err": [
"ld_da_mcic_data_err"
... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 93f773d2e676 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ct_lsu_mcic module, compare the RTL-to-netlist signal mapping coverage with the synthesis results: how well do the RTL signals carry into the netlist, and how does that relate to the synthesized gate count and area?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"m... | c2ac9183921b | 051422024433 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_mcic.v",
"sha256": "5ca52fc8fad921cbfb55939363d88363e9e599a7f3bd7deb27a4d78bb0830dc9"
} |
For the axi_ad9361_cmos_if module, how does the port structure seen in its CDFG relate to the delay-focused optimization advice, and what improvement and trade-offs should I expect? | The CDFG for axi_ad9361_cmos_if has 44 nodes with 29 input ports and 15 output ports, and the delay optimization flow (synth, opt -fast, abc -fast, opt_clean, plus retiming and fanout-reduction suggestions) estimates a delay improvement of -20.0 with an area increase of 10.0 and power increase of 5.0. The main trade-of... | github_repos/analogdevicesinc_hdl/library/axi_ad9361/intel/axi_ad9361_cmos_if.v | axi_ad9361_cmos_if | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "delay"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[9943 chars elided]...
"node_count": 44,
"edge_count": 0,
"graph_properties": {
"node_types": {
"port_input": 29,
"port_output": 15
},
"avg_degree": 0.0,
"module_name": "axi_ad9361_cmos_if"
}... | multi_tool | graph_extractor+optimization_advisor | compositional | 509350bd870b | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the axi_ad9361_cmos_if module, how does the port structure seen in its CDFG relate to the delay-focused optimization advice, and what improvement and trade-offs should I expect?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[9943 chars elided]...
"node_cou... | 1794ae8a74e2 | 053d41449bf2 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9361/intel/axi_ad9361_cmos_if.v",
"sha256": "a630b9d6bb1ca389677951635365a610e79b3e3ade6a1925f54a9cde85b929fe"
} |
For ip_eth_rx_64, how well does the RTL line up with the synthesized netlist, and given that, is it worth applying the area-focused optimization recipes, and what are the expected costs? | The RTL-to-netlist mapping only achieves an alignment score of 56.56, with 69 of 122 RTL signals mapped and 53 unmapped (including control registers like state_reg and m_ip_hdr_valid_reg), so verification of the mapping is weak. The area optimization advisor recommends recipes such as 'synth -top ip_eth_rx_64 -flatten'... | github_repos/corundum_corundum/fpga/lib/eth/rtl/ip_eth_rx_64.v | ip_eth_rx_64 | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "area"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"last_word_data_reg": [],
"m_ip_payload_axis_tready_int_early": [
"m_ip_payload_axis_tready_int_early"
],
"m_ip_hdr_valid_reg": [],
"m_ip_version": [
"m_ip_version"
],
"m_ip_payload_axis_tvalid": [
... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | 419aac0c3516 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For ip_eth_rx_64, how well does the RTL line up with the synthesized netlist, and given that, is it worth applying the area-focused optimization recipes, and what are the expected costs?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"last_word_data_reg": [],
"m_ip_pay... | 69c42c7b1934 | 05af878ae78a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/ip_eth_rx_64.v",
"sha256": "8773830d79d7e339ee40c72cd63287fdf3dd884c80e151e401c1195bd32fd917"
} |
For the ct_vfpu_cbus module, how does the structure shown in its CDFG relate to the synthesized results, particularly regarding the clock-gating cells and overall cost? | The CDFG of ct_vfpu_cbus contains 28 nodes and 80 edges, including 3 gated_clk_cell nodes among its node types, and this matches the synthesis result of exactly 3 gated_clk_cell instances in a total of 24 gates. Synthesis further reports an area of 25.0, a critical-path estimate of 128.65, and a power of 0.024, so the ... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/vfpu/rtl/ct_vfpu_cbus.v | ct_vfpu_cbus | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[13417 chars elided]...
"node_count": 28,
"edge_count": 80,
"graph_properties": {
"node_types": {
"$logic_or": 3,
"$adffe": 2,
"$adff": 2,
"$mux": 2,
"gated_clk_cell": 3,
"port_inpu... | multi_tool | graph_extractor+synthesis_tool | compositional | 0dd51ab46800 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ct_vfpu_cbus module, how does the structure shown in its CDFG relate to the synthesized results, particularly regarding the clock-gating cells and overall cost?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[13417 chars elided]...
"node_count": 28,
"... | 6013c5b16e73 | 0624430a8c2a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/vfpu/rtl/ct_vfpu_cbus.v",
"sha256": "ceee498a703ffafdd0678980aa673f453ed9b68b1edfa27808890ba900707174"
} |
For ct_biu_lowpower, if I apply the delay-focused optimization recipes and register retiming, what impact is expected on area and power, and does the module's structure make it a good candidate for that? | The delay optimization is estimated to change delay by -20.0 while increasing area by 10.0 and power by 5.0, with trade-offs of higher area and power consumption. The module ct_biu_lowpower is fully combinational with 0 always blocks, 1 assign statement, 31 total ports (18 inputs and 13 outputs), 31 wires, 0 regs, and ... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/biu/rtl/ct_biu_lowpower.v | ct_biu_lowpower | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_biu_lowpower",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
... | multi_tool | optimization_advisor+static_analyzer | compositional | 519f51c1a492 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For ct_biu_lowpower, if I apply the delay-focused optimization recipes and register retiming, what impact is expected on area and power, and does the module's structure make it a good candidate for that?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
... | 2a75c042f715 | 05fdd1dffc1c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/biu/rtl/ct_biu_lowpower.v",
"sha256": "2434834c91c9337d5a94807f56ba06ea34cc140d173457cf22dcca3f4ccb697a"
} |
For axislave_stub, the data-flow graph (DFG) analysis shows a large number of port nodes but no edges — how does this structural result relate to what synthesis at medium optimization level reports, and what does it imply about whether the module is a true stub? | The DFG for axislave_stub contains 40 nodes (11 port_output and 29 port_input) with an edge_count of 0 and avg_degree 0.0, and synthesis correspondingly reports zero cells, zero area, zero delay, zero power, and a gate_count of 0, leaving only 40 wires totaling 260 wire bits. This agreement confirms the module is purel... | github_repos/aolofsson_oh/axi/dv/axislave_stub.v | axislave_stub | graph_extractor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[5936 chars elided]...
"node_count": 40,
"edge_count": 0,
"graph_properties": {
"node_types": {
"port_output": 11,
"port_input": 29
},
"avg_degree": 0.0,
"module_name": "axislave_stub"
},
"er... | multi_tool | graph_extractor+synthesis_tool | compositional | 047f32e15669 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For axislave_stub, the data-flow graph (DFG) analysis shows a large number of port nodes but no edges — how does this structural result relate to what synthesis at medium optimization level reports, and what does it imply about whether the module is a true stub?
[graph_extractor {"graph_type": "DFG"}]
{
"s... | 416ed87005d1 | 0671eb4c9cbd | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "axi/dv/axislave_stub.v",
"sha256": "02ae9d9b6a1f3d69dcaed2d4dd2e07a6fb08e1d2c07ed0709d9541c11cc68ba6"
} |
For the mac_pause_ctrl_tx module, how large is its and-inverter graph (AIG) representation, and given that I want to reduce power, what optimization would you suggest and what improvement could I expect? | The AIG of mac_pause_ctrl_tx contains 34357 nodes and 83910 edges, including 19334 NOT gates, 14720 AND gates, and 239 $_SDFF_PP0_ plus 1 $_SDFF_PP1_ flip-flops. For power reduction, clock gating of the registers is recommended, with an estimated improvement of -25.0 in power, though it adds timing complexity. | github_repos/corundum_corundum/fpga/lib/eth/rtl/mac_pause_ctrl_tx.v | mac_pause_ctrl_tx | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33923 chars elided]...
"node_count": 34357,
"edge_count": 83910,
"graph_properties": {
"node_types": {
"$_AND_": 14720,
"$_NOT_": 19334,
"$_SDFF_PP0_": 239,
"$_SDFF_PP1_": 1,
"$_DFFE_PP_":... | multi_tool | graph_extractor+optimization_advisor | compositional | 289cb823dfe9 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the mac_pause_ctrl_tx module, how large is its and-inverter graph (AIG) representation, and given that I want to reduce power, what optimization would you suggest and what improvement could I expect?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33923 chars e... | bf50cfb42ce5 | 06e5b2dc6e78 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/mac_pause_ctrl_tx.v",
"sha256": "c5de52ceae4cf7c048262132191b1e4c366deca15d931e4703f6a05eff789c5a"
} |
For the oh_aoi22 module, how does its CDFG structure relate to the area optimization advice — specifically, given that the CDFG has only 9 nodes and 11 edges with 2 $and, 1 $or, and 1 $not gate, is the suggested resource sharing worthwhile, and what delay penalty would it incur? | The CDFG for oh_aoi22 is very small (9 nodes, 11 edges, avg_degree 1.22, with only 2 $and, 1 $or and 1 $not operators besides 4 input ports and 1 output port), so there is little structure to share, yet the area optimization recipe still estimates an area improvement of -15.0 at a delay cost of 5.0. Given the tiny oper... | github_repos/aolofsson_oh/stdlib/rtl/oh_aoi22.v | oh_aoi22 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[2340 chars elided]...
"node_count": 9,
"edge_count": 11,
"graph_properties": {
"node_types": {
"$and": 2,
"$not": 1,
"$or": 1,
"port_input": 4,
"port_output": 1
},
"avg_degree": ... | multi_tool | graph_extractor+optimization_advisor | compositional | 87543c33fbf5 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the oh_aoi22 module, how does its CDFG structure relate to the area optimization advice — specifically, given that the CDFG has only 9 nodes and 11 edges with 2 $and, 1 $or, and 1 $not gate, is the suggested resource sharing worthwhile, and what delay penalty would it incur?
[graph_extractor {"graph_type... | cca35b87ff7b | 06d7749edf27 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_aoi22.v",
"sha256": "a3c7b70e3fdc1e7c401ca53a6ee41318837eb3f6a2cf7991b6afeb8632d3ccb1"
} |
For the uart module, how well does the RTL-to-netlist signal mapping line up with the RTL signal count from the source analysis, and given the area-focused optimization trade-offs, is the area recipe worth considering? | The RTL source contains 47 signals total (46 wires and 1 reg) across 5 instantiations, and the mapping successfully matched 46 of those 47 signals for a 97.87 alignment score, with only x_uart_apb_reg unmapped. The area optimization recipe (including aggressive resource sharing) is estimated to improve area by -15.0 an... | github_repos/XUANTIE-RV_openc910/smart_run/logical/uart/uart.v | uart | cross_stage_mapper+optimization_advisor+static_analyzer | [
{},
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg_ctrl_thr_vld": [
"reg_ctrl_thr_vld"
],
"receive_clk_en": [
"receive_clk_en"
],
"rst_b": [
"rst_b"
],
"ctrl_reg_fe": [
"ctrl_reg_fe"
],
"ctrl_receive_parity_en": [
...[2160 ... | multi_tool | cross_stage_mapper+optimization_advisor+static_analyzer | compositional | 2b3f0d40f2ae | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the uart module, how well does the RTL-to-netlist signal mapping line up with the RTL signal count from the source analysis, and given the area-focused optimization trade-offs, is the area recipe worth considering?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg_ct... | 2b6838676ab1 | 06f3079bba57 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "smart_run/logical/uart/uart.v",
"sha256": "a50efd8ac28041aac3cb49bacd69616fc71c244b5ffa6983984a863a96ade296"
} |
For the mac_pause_ctrl_rx module, the area-focused optimization analysis suggests aggressive resource sharing, but I'm worried about timing. Given the current synthesized design's critical path and the estimated impact of applying the area optimization recipes, is the area reduction worth it, and what should I watch ou... | The current synthesis of mac_pause_ctrl_rx has a critical path delay of 541.83 with an area of 4132.5 across 2765 cells, and the area optimization is estimated to reduce area by -15.0 and power by -10.0 at the cost of a delay increase of 5.0. The trade-off is that area optimization may increase delay and aggressive sha... | github_repos/corundum_corundum/fpga/lib/eth/rtl/mac_pause_ctrl_rx.v | mac_pause_ctrl_rx | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top mac_pause_ctrl_rx -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
... | multi_tool | optimization_advisor+synthesis_tool | compositional | 4f148f57cf4a | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the mac_pause_ctrl_rx module, the area-focused optimization analysis suggests aggressive resource sharing, but I'm worried about timing. Given the current synthesized design's critical path and the estimated impact of applying the area optimization recipes, is the area reduction worth it, and what should ... | 420cffcf602d | 06fa7dd019fe | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/mac_pause_ctrl_rx.v",
"sha256": "4b8d5d985fe5e7d3ec28f0c70a8c212fb7b3df6548cbf4dcaac2473a23b24a57"
} |
For the bmc_spi module, the delay-focused optimization ideas estimate changes in area, delay, and power — how do these trade-offs compare against the current synthesized figures and the module's structural complexity, and is the optimization worth pursuing? | The current synthesis of bmc_spi reports area 1184.5, delay 456.98, and power 0.69 with 690 gates, and the delay-targeted optimization suggests recipes like retiming and one-hot FSM encoding that would improve delay by -20.0 at the cost of area increasing by 10.0 and power by 5.0. Given the module's cyclomatic complexi... | github_repos/corundum_corundum/fpga/mqnic/fb2CG/fpga_25g/rtl/bmc_spi.v | bmc_spi | optimization_advisor+static_analyzer+synthesis_tool | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top bmc_spi",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"descri... | multi_tool | optimization_advisor+static_analyzer+synthesis_tool | compositional | d33841e01221 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the bmc_spi module, the delay-focused optimization ideas estimate changes in area, delay, and power — how do these trade-offs compare against the current synthesized figures and the module's structural complexity, and is the optimization worth pursuing?
[optimization_advisor {"target_metric": "delay"}]
{... | 0d8eb2934230 | 072929cf3629 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/mqnic/fb2CG/fpga_25g/rtl/bmc_spi.v",
"sha256": "e5f068feec8a6d7c82d6fb977e7caf308811e311ea9e618ee701849e520754c5"
} |
For the mqnic_dram_if module, the CDFG shows 92 nodes but no edges, and elaboration reports 0 cells — how does the port structure relate to the wire usage, and is the area optimization recommendation still sensible given that area optimization is estimated to cost delay? | The CDFG for mqnic_dram_if has 92 nodes (47 port_input and 45 port_output) with 0 edges and average degree 0.0, consistent with elaboration producing 0 cells, 0 submodules, and 1430 port bits carried on 137 wires totaling 2144 wire bits. With no cells to share, the aggressive resource-sharing recipe offers little benef... | github_repos/corundum_corundum/fpga/common/rtl/mqnic_dram_if.v | mqnic_dram_if | graph_extractor+optimization_advisor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[26439 chars elided]...
"node_count": 92,
"edge_count": 0,
"graph_properties": {
"node_types": {
"port_input": 47,
"port_output": 45
},
"avg_degree": 0.0,
"module_name": "mqnic_dram_if"
},
... | multi_tool | graph_extractor+optimization_advisor+synthesis_tool | compositional | 5b9c30bacf75 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the mqnic_dram_if module, the CDFG shows 92 nodes but no edges, and elaboration reports 0 cells — how does the port structure relate to the wire usage, and is the area optimization recommendation still sensible given that area optimization is estimated to cost delay?
[graph_extractor {"graph_type": "CDFG... | 57a684c0ab35 | 0719a05c21b3 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/common/rtl/mqnic_dram_if.v",
"sha256": "4105cc699d188192c000d10203a14e979db5a0330a187ccea4c3a4ac4ca2ac3d"
} |
For the bmc_spi module, how well did the RTL-to-netlist signal mapping hold up given its coding complexity, and what did it cost in area and power after medium-level delay/power optimization? Also, which FSM-style registers were left unmapped? | The bmc_spi module has a cyclomatic complexity of 31 with 230 operators and a nesting depth of 25, and only 14 of 30 RTL signals were mapped (alignment score 46.67), leaving 16 unmapped including state_reg, bit_count_reg, byte_count_reg, and bmc_miso_reg. After synthesis the design occupies an area of 1184.5 with 690 g... | github_repos/corundum_corundum/fpga/mqnic/fb2CG/fpga_25g/rtl/bmc_spi.v | bmc_spi | cross_stage_mapper+static_analyzer+synthesis_tool | [
{},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"ctrl_valid": [
"ctrl_valid"
],
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk",
"bmc_clk",
"bmc_clk_next"
],
"status_timeout_reg": [],
"bmc_nss_reg": [],
"bmc_mosi
...[859 c... | multi_tool | cross_stage_mapper+static_analyzer+synthesis_tool | compositional | cfa199dd9438 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the bmc_spi module, how well did the RTL-to-netlist signal mapping hold up given its coding complexity, and what did it cost in area and power after medium-level delay/power optimization? Also, which FSM-style registers were left unmapped?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlis... | 3b3736887aaa | 072929cf3629 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/mqnic/fb2CG/fpga_25g/rtl/bmc_spi.v",
"sha256": "e5f068feec8a6d7c82d6fb977e7caf308811e311ea9e618ee701849e520754c5"
} |
For the ct_spsram_256x7 module, how well do the RTL and netlist signal names line up after synthesis, and given that all seven ports map one-to-one, is the suggested power optimization with clock gating still worthwhile given its estimated trade-offs? | The RTL-to-netlist mapping for ct_spsram_256x7 is perfect, with an alignment score of 100.0 and all 7 RTL signals mapped with 0 unmapped, including WEN mapping to both WEN and GWEN. Synthesis produced a single ct_f_spsram_256x7 cell with a delay of 50.0, power of 0.001, and 32 wire bits, so the clock-gating power recip... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_spsram_256x7.v | ct_spsram_256x7 | cross_stage_mapper+optimization_advisor+synthesis_tool | [
{},
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"D": [
"D"
],
"Q": [
"Q"
],
"GWEN": [
"GWEN"
],
"CEN": [
"CEN"
],
"CLK": [
"CLK"
],
"WEN": [
"WEN",
"GWEN"
],
"A": [
"A"
]
},
"alignm... | multi_tool | cross_stage_mapper+optimization_advisor+synthesis_tool | compositional | ac4d81274ea0 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ct_spsram_256x7 module, how well do the RTL and netlist signal names line up after synthesis, and given that all seven ports map one-to-one, is the suggested power optimization with clock gating still worthwhile given its estimated trade-offs?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_t... | 91fde83b934a | 0710d49c17de | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_spsram_256x7.v",
"sha256": "80e2f92e707f3e6474b5d519d452806d031c70f1122ebc54be13416fc4dc0bc6"
} |
For karatsuba_mult, the RTL-to-netlist mapping shows a 100.0 alignment score with 3 mapped signals, but how does that small RTL signal count reconcile with the complexity seen in the module's DFG, and what does the DGF reveal about the datapath structure? | Although the RTL-to-netlist mapping for karatsuba_mult only tracks 3 RTL signals (o_h_sel, clk, tmp) against 1315 netlist wires with a 100.0 alignment score and zero unmapped signals, the DFG shows the real complexity lies in the datapath: 29 nodes and 2782 edges with an average degree of 95.93. The DFG node types incl... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/arithmetic/karatsuba_mult.v | karatsuba_mult | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "DFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"o_h_sel": [
"o_h_sel"
],
"clk": [
"clk"
],
"tmp": [
"tmp"
]
},
"alignment_score": 100.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 3,
"netlist_wires": 1315,
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 59583d4a86ac | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}] | Question: For karatsuba_mult, the RTL-to-netlist mapping shows a 100.0 alignment score with 3 mapped signals, but how does that small RTL signal count reconcile with the complexity seen in the module's DFG, and what does the DGF reveal about the datapath structure?
[cross_stage_mapper {}]
{
"status": "success",
"r... | 0c25c92cce21 | 078e3a1579f0 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/arithmetic/karatsuba_mult.v",
"sha256": "6de762e2705a27168fbb71ea8f5a713ff37ac1cba987a81cab20a62a7db82857"
} |
For the module asic_oai222, how does the number of synthesized netlist gates and wires compare with the RTL port and signal structure, and what are the resulting area, delay, and power after delay-aware medium-level optimization? | The RTL for asic_oai222 has 7 total ports (6 inputs, 1 output), 0 wires/regs, and 11 lines of code, while the synthesized netlist contains 5 gates (1 $_AND_, 1 $_NAND_, 3 $_OR_) and 11 wires. After synthesis the module achieves an area of 5.0, a critical-path delay of 77.79, and a power of 0.005, and the RTL-to-netlist... | github_repos/aolofsson_oh/asiclib/hdl/asic_oai222.v | asic_oai222 | cross_stage_mapper+static_analyzer+synthesis_tool | [
{},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"a0": [
"a0"
],
"z": [
"z"
],
"b0": [
"b0"
],
"b1": [
"b1"
],
"c0": [
"c0"
],
"a1": [
"a1"
],
"c1": [
"c1"
]
},
"alignment_score": 100.0,
... | multi_tool | cross_stage_mapper+static_analyzer+synthesis_tool | compositional | 31ca9cde1957 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module asic_oai222, how does the number of synthesized netlist gates and wires compare with the RTL port and signal structure, and what are the resulting area, delay, and power after delay-aware medium-level optimization?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
... | 3c5ad1c6a79d | 07dc4f283159 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_oai222.v",
"sha256": "07983af3d8d39f2f4240874e07d6f18191008f97f306da9d3075577fc57614ea"
} |
For the cordic_demod module, I ran an AIG analysis and an area-focused optimization analysis — given the size of the and-inverter graph, is the recommended area optimization worth it, and what delay penalty should I expect? | The AIG for cordic_demod is fairly large with 14976 nodes and 39645 edges, including 6403 AND gates, 8357 NOT gates, 173 D flip-flops and 31 memory-init nodes, so the aggressive sharing and gate-mapping recipes could help. The area-focused optimization estimates an area improvement of -15.0 and power of -10.0, but at a... | github_repos/analogdevicesinc_hdl/library/cordic_demod/cordic_demod.v | cordic_demod | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[45898 chars elided]...
"node_count": 14976,
"edge_count": 39645,
"graph_properties": {
"node_types": {
"$meminit_v2": 31,
"$memrd": 1,
"$_AND_": 6403,
"$_NOT_": 8357,
"$_DFFE_PP_": 173,
... | multi_tool | graph_extractor+optimization_advisor | compositional | 14e24456ce8f | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the cordic_demod module, I ran an AIG analysis and an area-focused optimization analysis — given the size of the and-inverter graph, is the recommended area optimization worth it, and what delay penalty should I expect?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG... | c07aeffe6597 | 0876c75104f9 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/cordic_demod/cordic_demod.v",
"sha256": "bdf075da1dc6ccd9479b4b261728b1fbbdde6027ceb64668a4d068e185187a24"
} |
For the cordic_demod module, the RTL-to-netlist mapping shows several signals couldn't be matched to the netlist while the delay-focused optimization analysis suggests retiming and FSM recoding — can you summarize how these two results relate? Specifically, which internal signals are unmapped, and would the suggested d... | In cordic_demod, 8 of 17 RTL signals are unmapped (step_counter, state, q_shift, i_shift, shift_counter, phase, q, and angle) with an alignment score of 52.94, which is notable because those unmapped signals are exactly the FSM and datapath logic the delay optimization targets: one-hot FSM recoding would speed up state... | github_repos/analogdevicesinc_hdl/library/cordic_demod/cordic_demod.v | cordic_demod | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "delay"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"step_counter": [],
"i": [
"m_axis_valid",
"s_axis_ready",
"s_axis_data",
"m_axis_data",
"signed"
],
"state": [],
"clk": [
"clk"
],
"q_shift": [],
"i_shift": [],
"m_axis... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | 2d40e094c301 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the cordic_demod module, the RTL-to-netlist mapping shows several signals couldn't be matched to the netlist while the delay-focused optimization analysis suggests retiming and FSM recoding — can you summarize how these two results relate? Specifically, which internal signals are unmapped, and would the s... | 013cbe0a77e7 | 0876c75104f9 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/cordic_demod/cordic_demod.v",
"sha256": "bdf075da1dc6ccd9479b4b261728b1fbbdde6027ceb64668a4d068e185187a24"
} |
For the ad9434_spi module, how does the high code complexity reflected in the static analysis affect the synthesized area and timing, and is the design dominated by sequential elements? | The ad9434_spi module has a cyclomatic complexity of 7, a nesting depth of 8, and 426 operators across 43 lines of code, yet it synthesizes to a fairly small netlist of 33 gates with an area of 38.0 and a critical path delay of 147.92 at a power of 0.033. The cell breakdown shows the design is indeed sequential-dominat... | github_repos/analogdevicesinc_hdl/projects/ad9434_fmc/common/ad9434_spi.v | ad9434_spi | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ad9434_spi",
"port_count": {
"inputs": 2,
"outputs": 1,
"inouts": 1,
"total": 4
},
"signal_count": {
"wires": 2,
"regs": 2,
"parameters": 0,
"total": 4
},
"always_blocks": 2,
"assign_statem... | multi_tool | static_analyzer+synthesis_tool | compositional | 81e5d55f1a92 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ad9434_spi module, how does the high code complexity reflected in the static analysis affect the synthesized area and timing, and is the design dominated by sequential elements?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ad9434_spi",
"port_count": {
"... | 5b6ad72b4922 | 088f5a48f150 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/ad9434_fmc/common/ad9434_spi.v",
"sha256": "d1aeced43e700a080b57eabbca5c61a5ae514429e929a62619520ac50be25ba1"
} |
For the IBUFGDS module, how does its control-flow/dataflow graph structure relate to the power optimization opportunities — does the purely combinational structure of the CDFG affect which power reduction suggestions apply, and what improvement is estimated? | The CDFG of IBUFGDS contains only 5 nodes — one $and gate, one $not gate, one port_output, and two port_inputs with 5 edges and an average degree of 1.0 — meaning there are no registers, so the suggested clock gating would have no sequential elements to act on. The power optimization still estimates a power improvement... | github_repos/aolofsson_oh/xilibs/dv/IBUFGDS.v | IBUFGDS | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[611 chars elided]...
"node_count": 5,
"edge_count": 5,
"graph_properties": {
"node_types": {
"$and": 1,
"$not": 1,
"port_output": 1,
"port_input": 2
},
"avg_degree": 1.0,
"module_n... | multi_tool | graph_extractor+optimization_advisor | compositional | b9c24a7dd03f | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the IBUFGDS module, how does its control-flow/dataflow graph structure relate to the power optimization opportunities — does the purely combinational structure of the CDFG affect which power reduction suggestions apply, and what improvement is estimated?
[graph_extractor {"graph_type": "CDFG"}]
{
"stat... | 9f3f0d90281d | 08ae97ead797 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "xilibs/dv/IBUFGDS.v",
"sha256": "2f0e9ff0071bcec4a7e251692fb27bf7cc508eabffe765131edeeba7ab2b72dc"
} |
For the pcie_us_if_cc module, given its code complexity and port/signal profile, is applying the aggressive area optimization flow worthwhile, and what delay penalty should I expect? | The pcie_us_if_cc module is fairly complex, with 473 lines of code, cyclomatic complexity 48, 18 total ports (10 inputs and 8 outputs), and 14 registers, so the aggressive sharing recipes like share -aggressive and muxcover are reasonable to try. The estimated area improvement is -15.0 with an estimated delay increase ... | github_repos/corundum_corundum/fpga/lib/pcie/rtl/pcie_us_if_cc.v | pcie_us_if_cc | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top pcie_us_if_cc -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 644402c0017f | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the pcie_us_if_cc module, given its code complexity and port/signal profile, is applying the aggressive area optimization flow worthwhile, and what delay penalty should I expect?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": ... | a5373330bb49 | 0888d48f2598 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/rtl/pcie_us_if_cc.v",
"sha256": "0349d7a18d87fa1cd47d7a1e89da18c6c53f052cf926daabc4d706678d90a943"
} |
For the IBUFGDS module, if I apply the power optimization suggestions like clock gating and operand isolation, how much improvement can I expect relative to the current post-synthesis power and area figures, and what trade-offs should I watch out for? | The IBUFGDS module currently synthesizes to a single $_ANDNOT_ gate with power of 0.001 and area of 1.5, and the power-focused optimization is estimated to reduce power by -25.0 while also improving area and delay by 5.0 each. However, these gains come with trade-offs: power optimization may add area overhead and clock... | github_repos/aolofsson_oh/xilibs/dv/IBUFGDS.v | IBUFGDS | optimization_advisor+synthesis_tool | [
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top IBUFGDS",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gating",... | multi_tool | optimization_advisor+synthesis_tool | compositional | e88de4fbe43b | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the IBUFGDS module, if I apply the power optimization suggestions like clock gating and operand isolation, how much improvement can I expect relative to the current post-synthesis power and area figures, and what trade-offs should I watch out for?
[optimization_advisor {"target_metric": "power"}]
{
"st... | 285a7a56fda3 | 08ae97ead797 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "xilibs/dv/IBUFGDS.v",
"sha256": "2f0e9ff0071bcec4a7e251692fb27bf7cc508eabffe765131edeeba7ab2b72dc"
} |
For the cmac_pad module, how do the code structure characteristics relate to the power optimization opportunities — is it worth applying the clock gating suggestion, and what improvement and trade-offs should I expect? | cmac_pad has 8 inputs, 6 outputs, 1 always block, 6 assign statements, and only 1 register with cyclomatic complexity 6, so the clock gating and operand isolation suggestions would be applied to a small register set. The power optimization estimates a -25.0 power improvement (5.0 area and 5.0 delay), with trade-offs of... | github_repos/corundum_corundum/fpga/common/rtl/cmac_pad.v | cmac_pad | optimization_advisor+static_analyzer | [
{
"target_metric": "power"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top cmac_pad",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gating"... | multi_tool | optimization_advisor+static_analyzer | compositional | 683b3d45ba1d | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the cmac_pad module, how do the code structure characteristics relate to the power optimization opportunities — is it worth applying the clock gating suggestion, and what improvement and trade-offs should I expect?
[optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metri... | 351e398ae6f9 | 0939564c6041 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/common/rtl/cmac_pad.v",
"sha256": "db4349a03850733cc4870c94b90b5bc04cfa2d59f5c4d18fcab3493904455d16"
} |
For the led_sreg_driver module, how do the structural analysis results (complexity, registers) relate to the synthesized implementation, and is the design clean? Give a short multi-part summary combining the static checks, the delay- and power-aware synthesis numbers, and the technology mapping results. | The led_sreg_driver module has 109 lines of code with a cyclomatic complexity of 13 and 6 regs, mapping to 119 gates and an area of 208.0 with a delay of 270.34 and power of 0.119 after medium-level optimization. The mapped netlist keeps 119 cells, including 16 $_DFF_P_ flip-flops and 19 $_NAND_ gates, with no lint war... | github_repos/corundum_corundum/fpga/lib/pcie/example/fb2CG/fpga_axi/rtl/led_sreg_driver.v | led_sreg_driver | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "led_sreg_driver",
"port_count": {
"inputs": 3,
"outputs": 4,
"inouts": 0,
"total": 7
},
"signal_count": {
"wires": 5,
"regs": 6,
"parameters": 5,
"total": 11
},
"always_blocks": 1,
"assign_... | multi_tool | static_analyzer+synthesis_tool | compositional | 65d9803b9413 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the led_sreg_driver module, how do the structural analysis results (complexity, registers) relate to the synthesized implementation, and is the design clean? Give a short multi-part summary combining the static checks, the delay- and power-aware synthesis numbers, and the technology mapping results.
[sta... | 88ce27590eda | 093cd18e11fa | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/fb2CG/fpga_axi/rtl/led_sreg_driver.v",
"sha256": "91ef35971991fd2b536d1ccb263e892441e9fa0d631e8a14d3db896238f3cb34"
} |
For the fpga module, if I apply the recommended area optimization flow, how will that trade off against the module's current structure, given it has 14 inputs and 14 outputs across 28 total ports, 30 assign statements, and no always blocks? | The fpga module is purely structural with 28 ports (14 inputs, 14 outputs), 121 wires, 30 assign statements, 0 always blocks, and 158 operators across 585 lines of code. The area optimization flow, including aggressive resource sharing of arithmetic operators, is estimated to improve area by -15.0 and power by -10.0, b... | github_repos/corundum_corundum/fpga/lib/eth/example/fb2CG/fpga_25g/rtl/fpga.v | fpga | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top fpga -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"type... | multi_tool | optimization_advisor+static_analyzer | compositional | d6cfc4244a07 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the fpga module, if I apply the recommended area optimization flow, how will that trade off against the module's current structure, given it has 14 inputs and 14 outputs across 28 total ports, 30 assign statements, and no always blocks?
[optimization_advisor {"target_metric": "area"}]
{
"status": "succ... | 2beec35b950f | 08f1b39698e7 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/example/fb2CG/fpga_25g/rtl/fpga.v",
"sha256": "9a9855f784c6decb46471b776bcfd6f8fe20705dbab8803f655907f4e1c47059"
} |
For dec_67_64, given its current synthesis results and structure, how much delay improvement could the suggested delay-focused optimizations bring, and is that plausible given how the design is built? | The delay-targeted optimization suggestions (pipeline insertion and logic duplication) estimate a delay improvement of -20.0 at the cost of 10.0 more area and 5.0 more power, on top of the current synthesized delay of 281.16, area of 132.0, and power of 0.066. This is plausible because dec_67_64 is purely combinational... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/interlaken_lane/dec_67_64.v | dec_67_64 | optimization_advisor+static_analyzer+synthesis_tool | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top dec_67_64",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"desc... | multi_tool | optimization_advisor+static_analyzer+synthesis_tool | compositional | 3a63a6de8ca2 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For dec_67_64, given its current synthesis results and structure, how much delay improvement could the suggested delay-focused optimizations bring, and is that plausible given how the design is built?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"re... | bcdcbd80aeca | 096b515fe8cf | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/interlaken_lane/dec_67_64.v",
"sha256": "f55965bc48ca2b2b89ce07f367f55e8289aa5d3104bcb4694412ac76c29bf764"
} |
For the crc16_dat32 module, how do the code characteristics relate to the power optimization advice, and what trade-offs should I expect if I follow it? | crc16_dat32 is a purely combinational module (0 always blocks, 22 assign statements, 944 operators across 150 lines of code), so the suggested power recipes center on clock gating and operand isolation with an estimated power reduction of -25.0 plus 5.0 improvements in area and delay. The trade-offs are that power opti... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crc/crc16_dat32.v | crc16_dat32 | optimization_advisor+static_analyzer | [
{
"target_metric": "power"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top crc16_dat32",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gati... | multi_tool | optimization_advisor+static_analyzer | compositional | f65141f46bb6 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the crc16_dat32 module, how do the code characteristics relate to the power optimization advice, and what trade-offs should I expect if I follow it?
[optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top crc16_dat3... | 074fec67ef32 | 09c2d87e0cd3 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crc/crc16_dat32.v",
"sha256": "bf5d311669de894ffd607ea608cbfa5eafc979ea404ad79e213d5919e5b10e16"
} |
For the oh_dffsqn module, how do the CDFG structure and the synthesis results relate — in particular, do the graph's node types match the cells reported after medium-level optimization targeting delay and power, and what are the resulting area, delay, and power figures? | The CDFG of oh_dffsqn contains 6 nodes (one $not, one $adff, 3 input ports, 1 output port) and 6 edges with average degree 1.0, which matches synthesis exactly: 2 cells comprising one $_DFF_PN0_ (the asynchronous-reset flip-flop) and one $_NOT_ (the inverter). Synthesis reports an area of 1.5, a critical-path delay of ... | github_repos/aolofsson_oh/stdlib/rtl/oh_dffsqn.v | oh_dffsqn | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[619 chars elided]...
"node_count": 6,
"edge_count": 6,
"graph_properties": {
"node_types": {
"$not": 1,
"$adff": 1,
"port_input": 3,
"port_output": 1
},
"avg_degree": 1.0,
"module_... | multi_tool | graph_extractor+synthesis_tool | compositional | 524a602407c1 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_dffsqn module, how do the CDFG structure and the synthesis results relate — in particular, do the graph's node types match the cells reported after medium-level optimization targeting delay and power, and what are the resulting area, delay, and power figures?
[graph_extractor {"graph_type": "CDFG"... | 0849ffbf9c3b | 09de49df29d4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_dffsqn.v",
"sha256": "e2ebe1bb4a5ce196dfa1fc6f7596eea9c2f9e84c3a5156cee800d5a437eacb5f"
} |
For the module pcileech_mux, how do the DFG structure and the RTL-to-netlist mapping results support the area-optimization recommendation, and what trade-off should I expect if I apply it? | The DFG for pcileech_mux is dominated by 174 mux nodes out of 319 nodes (with 11082 edges and average degree 34.74), which supports the suggested mux sharing via muxcover, while the mapping shows 62 of 72 RTL signals mapped (alignment score 86.11, 10 unmapped signals like dout_valid and ctx_reg). The area recipe (share... | github_repos/ufrisk_pcileech-fpga/GBOX/src/pcileech_mux.sv | pcileech_mux | cross_stage_mapper+graph_extractor+optimization_advisor | [
{},
{
"graph_type": "DFG"
},
{
"target_metric": "area"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"p1_tag": [
"p1_tag"
],
"dout_valid": [],
"p5_ctx": [
"p5_ctx"
],
"p3_req_data": [
"p3_req_data"
],
"p6_tag": [
"p6_tag"
],
"p6_din": [
"p6_din"
],
"p4_d
...[2434 ... | multi_tool | cross_stage_mapper+graph_extractor+optimization_advisor | compositional | 21ef437d7b95 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the module pcileech_mux, how do the DFG structure and the RTL-to-netlist mapping results support the area-optimization recommendation, and what trade-off should I expect if I apply it?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"p1_tag": [
"p1_tag"
],
... | 57d5553d38bc | 09dfa18e3094 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/ufrisk/pcileech-fpga",
"commit": "c538c4170678c13f723dc921905fb81ff3c71d8e",
"path": "GBOX/src/pcileech_mux.sv",
"sha256": "0c264ebf3ab163fbe122bc90ad03cb874809ac9f3e73048b563a768abbd5e63c"
} |
For the module oh_dffsqn, how well does the AIG graph structure line up with the RTL-to-netlist mapping results, and what does this suggest about the design? | The AIG graph for oh_dffsqn contains 6 nodes and 6 edges, including one $_DFF_PN0_ flip-flop, one $_NOT_ inverter, 3 input ports, and 1 output port, but the RTL-to-netlist mapping found 0 mapped signals out of 1 RTL signal (leaving "reg" unmapped with an alignment score of 0.0) despite 6 netlist wires. This mismatch in... | github_repos/aolofsson_oh/stdlib/rtl/oh_dffsqn.v | oh_dffsqn | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg": []
},
"alignment_score": 0.0,
"unmapped_elements": [
"reg"
],
"mapping_statistics": {
"rtl_signals": 1,
"netlist_wires": 6,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 1
},
"e... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 564e8a3e6077 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For the module oh_dffsqn, how well does the AIG graph structure line up with the RTL-to-netlist mapping results, and what does this suggest about the design?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg": []
},
"alignment_score": 0.0,
"unmapped_elements": [
... | cc7a2c369f53 | 09de49df29d4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_dffsqn.v",
"sha256": "e2ebe1bb4a5ce196dfa1fc6f7596eea9c2f9e84c3a5156cee800d5a437eacb5f"
} |
For the module crc16_dat32, how complex is its dataflow structure according to the DFG analysis, and does that structure justify the power-focused optimizations that were recommended? | The DFG for crc16_dat32 contains 56 nodes and 407 edges, including 49 xor6 gates with an average degree of 7.27, so the dense XOR network gives real opportunities for gate-level restructuring. The power optimization advice is to run logic sharing and technology mapping plus clock gating and operand isolation, which is ... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crc/crc16_dat32.v | crc16_dat32 | graph_extractor+optimization_advisor | [
{
"graph_type": "DFG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[28557 chars elided]...
"node_count": 56,
"edge_count": 407,
"graph_properties": {
"node_types": {
"crc16_dat32_factor": 1,
"port_input": 4,
"port_output": 2,
"xor6": 49
},
"avg_degree": ... | multi_tool | graph_extractor+optimization_advisor | compositional | 0a09e630efe2 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the module crc16_dat32, how complex is its dataflow structure according to the DFG analysis, and does that structure justify the power-focused optimizations that were recommended?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[28557 chars elided]...
"node_co... | e8c399626cfd | 09c2d87e0cd3 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crc/crc16_dat32.v",
"sha256": "bf5d311669de894ffd607ea608cbfa5eafc979ea404ad79e213d5919e5b10e16"
} |
For the timer module, how do the area-focused optimization recommendations relate to its structural complexity, and is it worth applying the aggressive resource sharing given the trade-offs? | The timer module has 12 inputs, 3 outputs, 9 always blocks, 12 assign statements, and a cyclomatic complexity of 52, so aggressive sharing of arithmetic operators and mux sharing are reasonable to cut area by an estimated 15.0. However, the trade-offs note that area optimization may increase delay by 5.0 and that aggre... | github_repos/XUANTIE-RV_openc910/smart_run/logical/common/timer.v | timer | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top timer -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"typ... | multi_tool | optimization_advisor+static_analyzer | compositional | 8fee2f23b6f0 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the timer module, how do the area-focused optimization recommendations relate to its structural complexity, and is it worth applying the aggressive resource sharing given the trade-offs?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_re... | c54f880c2cb1 | 0a4c7b2e7243 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "smart_run/logical/common/timer.v",
"sha256": "f3c7d3604409960087dee8c0d24679d83d1e947cd937c7eef18d13a46d93746c"
} |
For the oh_standby module, my RTL declares 12 signals but the formal mapping only matched 10 of them to the netlist — which signals failed to map, and do the RTL statistics suggest why, given the module's port and internal signal counts? | The unmapped elements are "clock" and "input", giving an alignment score of 83.33 with 10 of 12 RTL signals mapped. The RTL analysis shows oh_standby has 8 ports total (5 inputs, 3 outputs) and 4 internal wire signals with 0 registers, so those two unmatched names are likely leftovers from truncated names in netlist wi... | github_repos/aolofsson_oh/stdlib/rtl/oh_standby.v | oh_standby | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"wakeup_now": [
"wakeup_now"
],
"idle": [
"idle"
],
"testenable": [
"testenable"
],
"sync_reset_pulse": [
"sync_reset_pulse"
],
"clk_en": [
"clk_en"
],
"sync_reset": [... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 155536ec2082 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_standby module, my RTL declares 12 signals but the formal mapping only matched 10 of them to the netlist — which signals failed to map, and do the RTL statistics suggest why, given the module's port and internal signal counts?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapp... | 9d0daaf1781a | 0a49bdc5606e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_standby.v",
"sha256": "61d424bbcb7f70abf510b2769eae5d826b12ad7411e8e3f6c6085c3edaefbfeb"
} |
For the oh_standby module, the source code is quite small (55 lines) yet synthesis reports 16 cells including 5 flip-flops. Given the structure of the module and the delay-optimized synthesis results, explain whether the size and complexity of the RTL match the implemented hardware, and give the key figures for area, d... | The oh_standby module has 5 inputs and 3 outputs across 8 total ports, 3 assign statements and 1 always block, with a cyclomatic complexity of 5 in 55 lines of code. Synthesis maps this to 16 cells over a 16.0 area, including 5 $_DFF_PN0_ flip-flops plus instances of oh_clockgate, oh_edge2pulse, oh_delay, and oh_dsync,... | github_repos/aolofsson_oh/stdlib/rtl/oh_standby.v | oh_standby | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "oh_standby",
"port_count": {
"inputs": 5,
"outputs": 3,
"inouts": 0,
"total": 8
},
"signal_count": {
"wires": 4,
"regs": 0,
"parameters": 4,
"total": 4
},
"always_blocks": 1,
"assign_statem... | multi_tool | static_analyzer+synthesis_tool | compositional | 5490830d0067 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_standby module, the source code is quite small (55 lines) yet synthesis reports 16 cells including 5 flip-flops. Given the structure of the module and the delay-optimized synthesis results, explain whether the size and complexity of the RTL match the implemented hardware, and give the key figures f... | 92dc242b210d | 0a49bdc5606e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_standby.v",
"sha256": "61d424bbcb7f70abf510b2769eae5d826b12ad7411e8e3f6c6085c3edaefbfeb"
} |
For asic_dmux7, how do the RTL-to-netlist mapping results compare with the module's CDFG structure in terms of signal counts and graph size, and what does that suggest about how the combinational logic was implemented? | The mapping shows 15 RTL signals mapped to 54 netlist wires with 0 unmapped signals and a 100.0 alignment score, while the CDFG for asic_dmux7 contains 28 nodes and 39 edges with 7 $and and 6 $or operators plus 14 input ports and 1 output port. Together this indicates all 15 ports (14 inputs and 1 output) carried over ... | github_repos/aolofsson_oh/asiclib/hdl/asic_dmux7.v | asic_dmux7 | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"in5": [
"in5"
],
"in1": [
"in1"
],
"sel0": [
"sel0"
],
"in0": [
"in0"
],
"sel6": [
"sel6"
],
"in3": [
"in3"
],
"in2": [
"in2"
],
"sel3": [... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 741a539da938 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For asic_dmux7, how do the RTL-to-netlist mapping results compare with the module's CDFG structure in terms of signal counts and graph size, and what does that suggest about how the combinational logic was implemented?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"in5": ... | aa79a2608dcb | 0a567bfd3c6f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_dmux7.v",
"sha256": "55cec81f9b2b184927609a960256cefd000d60cc8cb88b95cf643a48c9cf6476"
} |
For the module asic_dmux7, based on its DFG structure, would applying the aggressive resource sharing suggested by the area-focused optimization advisor be worthwhile, and what delay penalty should I expect? | The DFG for asic_dmux7 has 28 nodes and 39 edges, with only 7 $and and 6 $or operators, so there is little arithmetic logic to share, yet the area optimization suggests "share -aggressive" with an estimated area improvement of -15.0 while warning that aggressive sharing increases routing complexity. The trade-off is an... | github_repos/aolofsson_oh/asiclib/hdl/asic_dmux7.v | asic_dmux7 | graph_extractor+optimization_advisor | [
{
"graph_type": "DFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[10389 chars elided]...
"node_count": 28,
"edge_count": 39,
"graph_properties": {
"node_types": {
"$and": 7,
"$or": 6,
"port_input": 14,
"port_output": 1
},
"avg_degree": 1.39,
"modul... | multi_tool | graph_extractor+optimization_advisor | compositional | 9288734de60f | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the module asic_dmux7, based on its DFG structure, would applying the aggressive resource sharing suggested by the area-focused optimization advisor be worthwhile, and what delay penalty should I expect?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[10389 cha... | f00349bff9df | 0a567bfd3c6f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_dmux7.v",
"sha256": "55cec81f9b2b184927609a960256cefd000d60cc8cb88b95cf643a48c9cf6476"
} |
For ct_ebiu_lowpower, how well does the RTL-to-gate-level mapping hold up given the module's structural complexity, and is anything left unmapped? | ct_ebiu_lowpower has 10 RTL signals (9 wires and 1 reg) across 7 inputs and 3 outputs with a cyclomatic complexity of 7 in 58 lines of code, and the mapping achieved an alignment score of 90.0 with 9 of 10 signals mapped, leaving only ebiu_pad_csysack unmapped. | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/ciu/rtl/ct_ebiu_lowpower.v | ct_ebiu_lowpower | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"forever_cpuclk": [
"forever_cpuclk"
],
"ebiu_read_channel_no_op": [
"ebiu_read_channel_no_op"
],
"ebiu_snoop_channel_no_op": [
"ebiu_snoop_channel_no_op"
],
"clk_en": [
"clk_en"
],
... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 6b57e0e3d9d1 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For ct_ebiu_lowpower, how well does the RTL-to-gate-level mapping hold up given the module's structural complexity, and is anything left unmapped?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"forever_cpuclk": [
"forever_cpuclk"
],
"ebiu_read_channel_no_op"... | a63a68e155dd | 0a5cdef37ddb | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/ciu/rtl/ct_ebiu_lowpower.v",
"sha256": "08369ffbb8bbf7ce91727a1f3e500b95040cf3074b9189e39612b22fbc5e82a6"
} |
For ct_ifu_icache_data_array1, given that the delay-focused optimization study projects a -20.0 change in delay at the cost of area and power, how do those trade-offs weigh against what the static analysis shows about the module's structure and complexity? | The delay optimization for ct_ifu_icache_data_array1 projects a -20.0 delay improvement but increases area by 10.0 and power by 5.0, so it trades area and power for speed. Since the module is purely combinational glue logic (0 always blocks, 13 assign statements, cyclomatic complexity 7, nesting depth 0) over 15 total ... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/ifu/rtl/ct_ifu_icache_data_array1.v | ct_ifu_icache_data_array1 | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_ifu_icache_data_array1",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_inserti... | multi_tool | optimization_advisor+static_analyzer | compositional | d6bc919d256e | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For ct_ifu_icache_data_array1, given that the delay-focused optimization study projects a -20.0 change in delay at the cost of area and power, how do those trade-offs weigh against what the static analysis shows about the module's structure and complexity?
[optimization_advisor {"target_metric": "delay"}]
{
... | a9ee50523e50 | 09ee6230d861 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/ifu/rtl/ct_ifu_icache_data_array1.v",
"sha256": "359cc1fd57943aed281b2095758785c86aacddfcff4da43adaefc602234fa985"
} |
For the mlab_dcfifo module, the RTL-to-netlist cross-check shows that signals like rdused, wrused, rdempty, and wrfull did not map to the synthesized netlist, while wer, arst, wrclk, rdreq, rdclk, parity_err, and wrreq did. Given the synthesis results (area, delay, power, and gate count), how would you summarize the st... | Synthesis of mlab_dcfifo at medium optimization produced 228 gates with an area of 285.0, a delay of 283.06, and power of 0.228, but the cross-check mapped only 7 of 15 RTL signals (alignment score 46.67), leaving rdused, reg, wrused, rdempty, wrfull, rdfilter, rdarst, and wrfilter unmapped. This suggests the FIFO stat... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/mlab_dcfifo.v | mlab_dcfifo | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rdused": [],
"reg": [],
"wrused": [],
"rdempty": [],
"wer": [
"wer"
],
"arst": [
"arst"
],
"wrclk": [
"wrclk"
],
"rdreq": [
"rdreq"
],
"wrfull": [],
"rdclk": [
... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 1fee68d6422c | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the mlab_dcfifo module, the RTL-to-netlist cross-check shows that signals like rdused, wrused, rdempty, and wrfull did not map to the synthesized netlist, while wer, arst, wrclk, rdreq, rdclk, parity_err, and wrreq did. Given the synthesis results (area, delay, power, and gate count), how would you summar... | acb4a19ac4d8 | 0ae05d9fdfae | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/mlab_dcfifo.v",
"sha256": "d591f4eedddb98f484f23373301f567cb6c2ac797d688424958c6a19325725cc"
} |
For the module oh_ao21, compare its AIG representation with its final synthesized gate-level implementation: how does the node/gate structure differ between the two views, and what are the resulting delay, area, and power figures from synthesis? | The AIG view of oh_ao21 has 9 nodes (2 $_AND_, 3 $_NOT_, 3 input ports, 1 output port) and 12 edges with an average degree of 1.33, while the synthesized netlist collapses this to just 2 gates (1 $_AND_ and 1 $_OR_) with 5 wires. The optimized implementation achieves an area of 2.0, a delay (critical path) of 61.56, an... | github_repos/aolofsson_oh/stdlib/rtl/oh_ao21.v | oh_ao21 | graph_extractor+synthesis_tool | [
{
"graph_type": "AIG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[1366 chars elided]...
"node_count": 9,
"edge_count": 12,
"graph_properties": {
"node_types": {
"$_AND_": 2,
"$_NOT_": 3,
"port_input": 3,
"port_output": 1
},
"avg_degree": 1.33,
"mod... | multi_tool | graph_extractor+synthesis_tool | compositional | 4350bce956d9 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module oh_ao21, compare its AIG representation with its final synthesized gate-level implementation: how does the node/gate structure differ between the two views, and what are the resulting delay, area, and power figures from synthesis?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success"... | 8e3cb59ba897 | 0ae1a27340eb | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_ao21.v",
"sha256": "ceb8e68365dd44b63c999c871e6c77b6fa44b3916fee2f9c2a9644bd965d77b3"
} |
For mlab_dcfifo, how do the storage elements in its CDFG compare with the flip-flop counts after synthesis, and what are the resulting delay and power figures for this delay- and power-aware medium-effort optimization? | The CDFG of mlab_dcfifo contains 51 nodes and 666 edges, including 15 $adff and 1 $dff elements plus 4 mlab_fifo_cells, which after synthesis appear as 96 $_DFF_PN0_, 1 $_DFF_PN1_, 4 $_DFF_PP0_, and 1 $_DFF_P_ flip-flops among 228 total cells. Synthesis at the medium optimization level reports a delay of 283.06 and pow... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/mlab_dcfifo.v | mlab_dcfifo | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[37047 chars elided]...
"node_count": 51,
"edge_count": 666,
"graph_properties": {
"node_types": {
"$eq": 2,
"$add": 2,
"$and": 3,
"$not": 4,
"$mux": 1,
"$xor": 2,
"$logic_not... | multi_tool | graph_extractor+synthesis_tool | compositional | 44fb2f31de11 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For mlab_dcfifo, how do the storage elements in its CDFG compare with the flip-flop counts after synthesis, and what are the resulting delay and power figures for this delay- and power-aware medium-effort optimization?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
... | 990ac3cd1b72 | 0ae05d9fdfae | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/mlab_dcfifo.v",
"sha256": "d591f4eedddb98f484f23373301f567cb6c2ac797d688424958c6a19325725cc"
} |
For mqnic_tx_scheduler_block, how reliable is the correspondence between the RTL signals and the synthesized netlist, and does the structure shown in the module's CDFG support that the design made it through synthesis largely intact? Please cite the mapping coverage, at least one signal that failed to map, and a couple... | The RTL-to-netlist mapping scored 85.48, with 53 of 62 RTL signals mapped and 9 unmapped, including tdma_enable_reg, sched_enable_reg, and ctrl_reg_wr_ack_reg. The CDFG for mqnic_tx_scheduler_block contains 178 nodes and 4585 edges with an average degree of 25.76, and includes the expected hierarchical blocks (axil_cro... | github_repos/corundum_corundum/fpga/common/rtl/mqnic_tx_scheduler_block_rr_tdma.v | mqnic_tx_scheduler_block | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"tdma_timeslot_end": [
"tdma_timeslot_end"
],
"s_axil_bresp": [
"s_axil_bresp"
],
"tdma_enable_reg": [],
"set_tdma_active_period_reg": [
"set_tdma_active_period_reg"
],
"tdma_error": [
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | da8fc53e060f | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For mqnic_tx_scheduler_block, how reliable is the correspondence between the RTL signals and the synthesized netlist, and does the structure shown in the module's CDFG support that the design made it through synthesis largely intact? Please cite the mapping coverage, at least one signal that failed to map, an... | 8c5ae4b84d3f | 0b87fdb48b2d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/common/rtl/mqnic_tx_scheduler_block_rr_tdma.v",
"sha256": "15a682fbae8367a7d536d646e98954fc41b258de508f524fa6783e18036a4f52"
} |
For the emmu module, how does the DFG structure compare with the synthesis results at medium optimization in terms of size and timing — summarize the graph, area, delay, and power figures together. | The DFG for emmu has 20 nodes and 1072 edges with an average degree of 53.6, and after synthesis at medium optimization it maps to 177 gates (104 of them $_DFFE_PN_ flip-flops) with an area of 167.0. The critical path delay is 207.41 and the total power is 0.177. | github_repos/aolofsson_oh/emmu/hdl/emmu.v | emmu | graph_extractor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[28623 chars elided]...
"node_count": 20,
"edge_count": 1072,
"graph_properties": {
"node_types": {
"$and": 1,
"$mux": 2,
"$sdffe": 1,
"$dffe": 1,
"oh_memory_dp": 1,
"packet2emesh": 2... | multi_tool | graph_extractor+synthesis_tool | compositional | 0b6f7ec55f42 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the emmu module, how does the DFG structure compare with the synthesis results at medium optimization in terms of size and timing — summarize the graph, area, delay, and power figures together.
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[28623 chars elided]... | 7e894028b942 | 0c506d2b8b18 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "emmu/hdl/emmu.v",
"sha256": "4e86356d401c2287267a06980b8b8d1029da2e7028f45ec89266c73ef6d85f87"
} |
For the axi_register module, how do the CDFG structure and the RTL-to-netlist signal mapping compare — specifically, do the submodule instances shown in the control/data-flow graph account for the signals reported as successfully mapped, and are there any signals that didn't line up? | The CDFG for axi_register contains 92 nodes and 490 edges with an average degree of 5.33, including one axi_register_rd instance and one axi_register_wr instance along with 46 input ports and 44 output ports. The RTL-to-netlist mapping successfully matched 62 of the 63 RTL signals to netlist wires (out of 90 netlist wi... | github_repos/corundum_corundum/fpga/lib/axi/rtl/axi_register.v | axi_register | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"m_axi_arregion": [
"m_axi_arregion"
],
"rst": [
"m_axi_arburst",
"s_axi_arburst",
"rst",
"m_axi_awburst",
"s_axi_awburst"
],
"wire": [],
"s_axi_arvalid": [
"s_axi_arvalid"
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 492eac458777 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the axi_register module, how do the CDFG structure and the RTL-to-netlist signal mapping compare — specifically, do the submodule instances shown in the control/data-flow graph account for the signals reported as successfully mapped, and are there any signals that didn't line up?
[cross_stage_mapper {}]
... | cbd92708235f | 0c0e797467e4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/axi/rtl/axi_register.v",
"sha256": "76eea19cf4967cfeb40cb4c0f10de3e20b70e841a79271134de685df7e91e3a2"
} |
For the axis_tap module, how would applying the delay-focused optimization recommendations affect the synthesized design's current area of 245.5 and delay of 274.61, and what cell types dominate the current implementation? | The current synthesis of axis_tap reports an area of 245.5 with 146 gates and a critical path delay of 274.61, dominated by 41 $_AND_ and 36 $_NAND_ cells plus 20 $_DFFE_PP_ flip-flops. The delay optimization suggests pipelining arithmetic operations, one-hot FSM encoding, and logic duplication, estimating a delay chan... | github_repos/corundum_corundum/fpga/lib/eth/lib/axis/rtl/axis_tap.v | axis_tap | optimization_advisor+synthesis_tool | [
{
"target_metric": "delay"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top axis_tap",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"descr... | multi_tool | optimization_advisor+synthesis_tool | compositional | d8d9b0cc7998 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the axis_tap module, how would applying the delay-focused optimization recommendations affect the synthesized design's current area of 245.5 and delay of 274.61, and what cell types dominate the current implementation?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_m... | 398d1476e073 | 0c5851e3885f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/lib/axis/rtl/axis_tap.v",
"sha256": "9b659c8c99dcef1feba2f859369c8c127a1b5539c35245446e35591de9fa8106"
} |
For the axis_tap module, how well do the RTL signals line up with the synthesized netlist, and does the extracted DFG support that picture of the design's control-heavy structure? | The RTL-to-netlist mapping only achieved an alignment score of 58.06, with 18 of 31 RTL signals mapped and 13 unmapped against 373 netlist wires. The DFG, which has 91 nodes and 474 edges with an average degree of 5.21, is dominated by control logic such as 36 $mux and 5 $pmux nodes plus 11 $sdff/$dffe/$sdffe-type regi... | github_repos/corundum_corundum/fpga/lib/eth/lib/axis/rtl/axis_tap.v | axis_tap | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "DFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"tap_axis_tvalid": [
"tap_axis_tvalid"
],
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"m_axis_tvalid": [
"m_axis_tvalid_next",
"temp_m_axis_tvalid_next",
"m_axis_tvalid_... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 4b9f310bdda5 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}] | Question: For the axis_tap module, how well do the RTL signals line up with the synthesized netlist, and does the extracted DFG support that picture of the design's control-heavy structure?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"tap_axis_tvalid": [
"tap_axis_tvalid"
... | d5d1f79d0e21 | 0c5851e3885f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/lib/axis/rtl/axis_tap.v",
"sha256": "9b659c8c99dcef1feba2f859369c8c127a1b5539c35245446e35591de9fa8106"
} |
For the system_top module, the synthesis run reports a certain delay and power; given the delay-focused optimization recommendations, is the suggested pipelining/logic-duplication effort worthwhile, and what trade-offs should I expect relative to the current synthesized results? | The current synthesis of system_top has a critical path of 50.0 with power of 0.001 and only 1 gate (a single system_wrapper instance), so the delay-targeted optimization (register retiming and splitnets -driver) offers little to gain, projecting only a -20.0 delay improvement at the cost of 10.0 area growth and 5.0 hi... | github_repos/analogdevicesinc_hdl/projects/max96724/kv260/system_top.v | system_top | optimization_advisor+synthesis_tool | [
{
"target_metric": "delay"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top system_top",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"des... | multi_tool | optimization_advisor+synthesis_tool | compositional | d000fed7b8fc | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the system_top module, the synthesis run reports a certain delay and power; given the delay-focused optimization recommendations, is the suggested pipelining/logic-duplication effort worthwhile, and what trade-offs should I expect relative to the current synthesized results?
[optimization_advisor {"targe... | 8ac6006ed8e3 | 0c6aefbd3a03 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/max96724/kv260/system_top.v",
"sha256": "59079a06e1b7aa8213ba4ce850d09d82610a7a2c51e63a131b7a71e0f4008904"
} |
For the module dut, the CDFG shows some ports that the static analysis of the module declaration does not seem to count. Which port list should I trust, and what do the two views each report? | The module declaration view reports 4 inputs, 2 outputs, and 6 total ports, while the CDFG of dut shows 8 port_input nodes and 5 port_output nodes (13 nodes total with 0 edges). The CDFG apparently counts individual bits, since e.g. clkout spans bits 2 through 218, so the discrepancy comes from bit-level versus port-le... | github_repos/aolofsson_oh/stdlib/testbench/dut_template.v | dut | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[2852 chars elided]...
"node_count": 13,
"edge_count": 0,
"graph_properties": {
"node_types": {
"port_output": 5,
"port_input": 8
},
"avg_degree": 0.0,
"module_name": "dut"
},
"error": null... | multi_tool | graph_extractor+static_analyzer | compositional | 02f28a8fa79e | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module dut, the CDFG shows some ports that the static analysis of the module declaration does not seem to count. Which port list should I trust, and what do the two views each report?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[2852 chars elided]...
... | bdd3495a3325 | 0c85dcd6337c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/testbench/dut_template.v",
"sha256": "196f6ebf58b22950ada6f56397f73806e0090837a585c568bc64a50197dcc563"
} |
For the dut module, do all of its ports line up one-to-one with the synthesized netlist signals, and given the module's overall structure (its port counts and statement mix), does anything about that mapping result seem surprising? | Yes, all 4 inputs and 2 outputs of dut (6 ports total, with 3 assign statements, 0 always blocks, and cyclomatic complexity of 1) map one-to-one to netlist signals, giving an alignment score of 100.0 with 0 unmapped signals. It is somewhat notable that a purely combinational module with 0 always blocks still shows 15 n... | github_repos/aolofsson_oh/stdlib/testbench/dut_template.v | dut | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"clk1": [
"clk1"
],
"dut_active": [
"dut_active"
],
"nreset": [
"nreset"
],
"vss": [
"vss"
],
"clkout": [
"clkout"
],
"clk2": [
"clk2"
]
},
"alignment_sc... | multi_tool | cross_stage_mapper+static_analyzer | compositional | c5543ddd6d09 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the dut module, do all of its ports line up one-to-one with the synthesized netlist signals, and given the module's overall structure (its port counts and statement mix), does anything about that mapping result seem surprising?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": ... | 22bee5fd46e1 | 0c85dcd6337c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/testbench/dut_template.v",
"sha256": "196f6ebf58b22950ada6f56397f73806e0090837a585c568bc64a50197dcc563"
} |
For the system_top module, given that the area-focused optimization analysis suggests aggressive resource sharing while the synthesis run reports very low cell usage, is pursuing the area optimization worthwhile, and what delay impact should I expect? | The current synthesis of system_top is already extremely small, with an area of 1.0, a gate_count of 1, and only 15 wires carrying 254 wire bits, so aggressive sharing has little room to help. If you still apply the area optimization, the estimated improvement is -15.0 in area but a delay penalty of 5.0 on top of the c... | github_repos/analogdevicesinc_hdl/projects/ad9783_ebz/zcu102/system_top.v | system_top | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top system_top -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+synthesis_tool | compositional | dd8aa72fdf70 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the system_top module, given that the area-focused optimization analysis suggests aggressive resource sharing while the synthesis run reports very low cell usage, is pursuing the area optimization worthwhile, and what delay impact should I expect?
[optimization_advisor {"target_metric": "area"}]
{
"sta... | a00a8391e1fb | 0cae8d4dc9ab | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/ad9783_ebz/zcu102/system_top.v",
"sha256": "2e4ecb70a2cfc39592e9b6f31e37a63e66545edefdc088175883356feb5318ff"
} |
For axi_adc_decimate_reg, based on its AIG representation and the power-focused optimization analysis, what types of sequential elements dominate the graph and what power savings and trade-offs are expected if clock gating is applied to them? | The AIG of axi_adc_decimate_reg contains 2264 nodes and 5857 edges, with sequential elements consisting of 34 $_DFF_PN0_ flops and 101 $_DFFE_PN0P_ enable flops (plus 852 AND and 1259 NOT gates). Applying clock gating to these registers is estimated to yield a power improvement of -25.0 (with area and delay each at 5.0... | github_repos/analogdevicesinc_hdl/library/axi_adc_decimate/axi_adc_decimate_reg.v | axi_adc_decimate_reg | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33475 chars elided]...
"node_count": 2264,
"edge_count": 5857,
"graph_properties": {
"node_types": {
"$_AND_": 852,
"$_NOT_": 1259,
"$_DFF_PN0_": 34,
"$_DFFE_PN0P_": 101,
"up_xfer_cntrl": ... | multi_tool | graph_extractor+optimization_advisor | compositional | aef907ac3e93 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For axi_adc_decimate_reg, based on its AIG representation and the power-focused optimization analysis, what types of sequential elements dominate the graph and what power savings and trade-offs are expected if clock gating is applied to them?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
... | 25eafba54b28 | 0c929c2b9f3c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_adc_decimate/axi_adc_decimate_reg.v",
"sha256": "f38c8be9ce6d5286ed36427db32ae715ff1136ff1aa1a4d886566d807f37a183"
} |
For the system_top module, how well does the RTL-to-netlist signal mapping agree with the CDFG structure and the static analysis port counts, and does anything look inconsistent? | The RTL-to-netlist mapping is clean with an alignment score of 100.0, mapping all 13 RTL signals (from 15 netlist wires) with zero unmapped elements, and the CDFG for system_top contains 13 nodes and 233 edges with 4 input ports and 8 output ports. The static analysis, however, reports only 11 total ports (4 inputs and... | github_repos/analogdevicesinc_hdl/projects/ad9783_ebz/zcu102/system_top.v | system_top | cross_stage_mapper+graph_extractor+static_analyzer | [
{},
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"gpio_bd_i": [
"gpio_bd_i"
],
"spi_do": [
"spi_do"
],
"spi_clk": [
"spi_clk"
],
"gpio_i": [
"gpio_i"
],
"spi_dio": [
"spi_dio"
],
"dco1_n": [
"dco1_n"
],
... | multi_tool | cross_stage_mapper+graph_extractor+static_analyzer | compositional | 64227b800038 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the system_top module, how well does the RTL-to-netlist signal mapping agree with the CDFG structure and the static analysis port counts, and does anything look inconsistent?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"gpio_bd_i": [
"gpio_bd_i"
],
"sp... | 1703deda4811 | 0cae8d4dc9ab | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/ad9783_ebz/zcu102/system_top.v",
"sha256": "2e4ecb70a2cfc39592e9b6f31e37a63e66545edefdc088175883356feb5318ff"
} |
For the axis_srl_register module, how do its code complexity and port structure relate to the power optimization opportunity — is clock gating likely to pay off, and what is the estimated power saving versus the added area cost? Consider the register and always-block structure when answering. | axis_srl_register has 3 regs updated in 1 always block, so clock gating could effectively cut dynamic power; the power optimization is estimated to improve power by -25.0 at a cost of only 5.0 area and 5.0 delay. The module is moderately complex (cyclomatic complexity 12, nesting depth 7, 148 operators across 119 lines... | github_repos/alexforencich_verilog-ethernet/lib/axis/rtl/axis_srl_register.v | axis_srl_register | optimization_advisor+static_analyzer | [
{
"target_metric": "power"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top axis_srl_register",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "cloc... | multi_tool | optimization_advisor+static_analyzer | compositional | 692e0fbc568b | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axis_srl_register module, how do its code complexity and port structure relate to the power optimization opportunity — is clock gating likely to pay off, and what is the estimated power saving versus the added area cost? Consider the register and always-block structure when answering.
[optimization_a... | 76c4ace86dd5 | 0d0213535826 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "lib/axis/rtl/axis_srl_register.v",
"sha256": "5c0a8b0810977520e78fdee88254a824e6e86e526b0e1b04b89734217a66e6a6"
} |
For the axi_ad9361_cmos_if module, how does its register structure shown in the AIG relate to the suggested power optimizations, and what savings and trade-offs are expected? | The AIG for axi_ad9361_cmos_if contains 154 $_DFF_P_ flip-flops plus 24 $_DFFE_PN_ and other register types, which is why clock gating of registers is recommended to reduce power, with an estimated power improvement of -25.0 and area and delay impacts of 5.0 each. The trade-offs are that power optimization may add area... | github_repos/analogdevicesinc_hdl/library/axi_ad9361/xilinx/axi_ad9361_cmos_if.v | axi_ad9361_cmos_if | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33578 chars elided]...
"node_count": 1650,
"edge_count": 4503,
"graph_properties": {
"node_types": {
"$_AND_": 599,
"$_NOT_": 794,
"$_DFF_P_": 154,
"$_DFF_PP0_": 4,
"$_SDFF_PN0_": 1,
... | multi_tool | graph_extractor+optimization_advisor | compositional | 7d4499f16c76 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the axi_ad9361_cmos_if module, how does its register structure shown in the AIG relate to the suggested power optimizations, and what savings and trade-offs are expected?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33578 chars elided]...
"node_count": 165... | 16035ea49e35 | 0d71a500f3ef | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9361/xilinx/axi_ad9361_cmos_if.v",
"sha256": "a0aea713bfbbd3e7c57a10a329714f498ef20995ce6036b8e41f561748d8e8f8"
} |
For the ptp_perout module, how well did the RTL signals survive into the gate-level netlist, and does the dataflow graph (DFG) structure suggest why so many signals lost their names? | Only 18 of 43 RTL signals were mapped (25 unmapped, alignment score 41.86), with the netlist containing 9304 wires and 0 cells. The DFG for ptp_perout has 115 nodes and 4516 edges with an average degree of 39.27, so the heavy fanout and dense connectivity (e.g., 15 $mux and 11 $pmux nodes) explain why most named signal... | github_repos/corundum_corundum/fpga/lib/eth/rtl/ptp_perout.v | ptp_perout | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "DFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"locked": [
"locked"
],
"rst": [
"rst"
],
"wire": [],
"error": [
"error_next",
"error"
],
"input_start": [
"input_start",
"input_start_valid"
],
"ts_96_fns_inc_reg":... | multi_tool | cross_stage_mapper+graph_extractor | compositional | d2d92c5d22d4 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}] | Question: For the ptp_perout module, how well did the RTL signals survive into the gate-level netlist, and does the dataflow graph (DFG) structure suggest why so many signals lost their names?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"locked": [
"locked"
],
"rst"... | 485a366b2bf1 | 0d97e55fbd04 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/ptp_perout.v",
"sha256": "78dc33fda3b18a4027dab0d444e88e2cd6eb5cde7de3b72dd8bea50a48256123"
} |
For the bmc_spi module, how do the register and multiplexer structures seen in its DFG compare with the synthesized sequential cell counts, and what do the area, delay, and power figures indicate about the overall cost of the design? | The bmc_spi DFG contains 49 $mux, 10 $pmux, and 17 flip-flop nodes (5 $dffe, 3 $sdff, 5 $sdffe, 4 $dff), which correspond to the synthesized 88 $_DFFE_PP_, 23 $_DFF_P_, 5 $_SDFFE_PP_, and 5 $_SDFF_PP_ cells within a total gate count of 690. This comes at an area of 1184.5, a delay of 456.98, and a power of 0.69, showin... | github_repos/corundum_corundum/fpga/mqnic/fb2CG/fpga_100g/rtl/bmc_spi.v | bmc_spi | graph_extractor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[55245 chars elided]...
"node_count": 133,
"edge_count": 2229,
"graph_properties": {
"node_types": {
"$reduce_bool": 7,
"$sub": 4,
"$logic_not": 5,
"$logic_and": 1,
"$ne": 12,
"$eq": ... | multi_tool | graph_extractor+synthesis_tool | compositional | ca42a9be18f4 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the bmc_spi module, how do the register and multiplexer structures seen in its DFG compare with the synthesized sequential cell counts, and what do the area, delay, and power figures indicate about the overall cost of the design?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_t... | d90c47fc73fa | 0d8730c7ff03 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/mqnic/fb2CG/fpga_100g/rtl/bmc_spi.v",
"sha256": "e5f068feec8a6d7c82d6fb977e7caf308811e311ea9e618ee701849e520754c5"
} |
For the debounce_switch module, compare the post-synthesis gate-level results with the source-level complexity and the AIG structure: how do the synthesized area, delay, and power relate to the number of gates, the AIG node count, and the source complexity metrics? | The debounce_switch module has 73 lines of code with cyclomatic complexity 13 and nesting depth 12, which after medium-level delay- and power-aware optimization maps to 127 gates with an area of 139.0, a delay of 219.91, and power of 0.127. In the AIG representation, the design expands to 3314 nodes and 8034 edges (135... | github_repos/corundum_corundum/fpga/lib/pcie/example/ExaNIC_X25/fpga_axi/rtl/debounce_switch.v | debounce_switch | graph_extractor+static_analyzer+synthesis_tool | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
...[33841 chars elided]...
"node_count": 3314,
"edge_count": 8034,
"graph_properties": {
"node_types": {
"$_AND_": 1354,
"$_NOT_": 1928,
"$_DFF_PP0_": 24,
"$_DFFE_PP0P_": 4,
"port_input": 3,
... | multi_tool | graph_extractor+static_analyzer+synthesis_tool | compositional | 794449c8fe0e | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the debounce_switch module, compare the post-synthesis gate-level results with the source-level complexity and the AIG structure: how do the synthesized area, delay, and power relate to the number of gates, the AIG node count, and the source complexity metrics?
[graph_extractor {"graph_type": "AIG"}]
{
... | 1e3ae9eb61ed | 0ddf34a930f0 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/ExaNIC_X25/fpga_axi/rtl/debounce_switch.v",
"sha256": "02d6ba80136cb9be942347e33c43881f465acbfc4f41b6af3a32d41c86b4ef5a"
} |
For the debounce_switch module, the RTL-to-netlist signal mapping looks poor — how does the structural complexity seen in the module's CDFG help explain why so few signals could be matched? | The mapping only matched 2 of 7 RTL signals (alignment score 28.57) because the synthesized logic has expanded into far more structure: the CDFG of debounce_switch contains 18 nodes and 470 edges with an average degree of 26.11, including heavy fanout from nodes like the reduce_or at line 82 driving many target wires, ... | github_repos/corundum_corundum/fpga/lib/pcie/example/ExaNIC_X25/fpga_axi/rtl/debounce_switch.v | debounce_switch | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"signals": [],
"cnt_reg": [],
"and": [],
"is": []
},
"alignment_score": 28.57,
"unmapped_elements": [
"wire",
"signals",
"cnt_r... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 1eec118aecb4 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the debounce_switch module, the RTL-to-netlist signal mapping looks poor — how does the structural complexity seen in the module's CDFG help explain why so few signals could be matched?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rst": [
"rst"
],
"wir... | 71f2884c479b | 0ddf34a930f0 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/ExaNIC_X25/fpga_axi/rtl/debounce_switch.v",
"sha256": "02d6ba80136cb9be942347e33c43881f465acbfc4f41b6af3a32d41c86b4ef5a"
} |
For the module ad_data_in, how well do the RTL and netlist line up, and does the CDFG structure suggest any reason why some signals might not map? Please give the alignment figure, the unmapped signals, and the relevant CDFG (control/data-flow graph) statistics. | The RTL-to-netlist mapping for ad_data_in has an alignment score of 84.62, with 11 of 13 signals mapped and rx_data_ibuf_s and rx_data_idelay_s left unmapped. The CDFG contains 12 nodes (8 port_input and 4 port_output) with an edge count of 0 and avg_degree 0.0, so the purely port-level structure with no internal conne... | github_repos/analogdevicesinc_hdl/library/xilinx/common/ad_data_in.v | ad_data_in | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rx_clk": [
"rx_clk"
],
"rx_data_in_n": [
"rx_data_in_n"
],
"up_dld": [
"up_dld"
],
"rx_data_n": [
"rx_data_n"
],
"en_vtc": [
"en_vtc"
],
"delay_locked": [
"dela... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 8e7ad21b67b7 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the module ad_data_in, how well do the RTL and netlist line up, and does the CDFG structure suggest any reason why some signals might not map? Please give the alignment figure, the unmapped signals, and the relevant CDFG (control/data-flow graph) statistics.
[cross_stage_mapper {}]
{
"status": "success... | a9237f9f940a | 0e1a5d42f5eb | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/xilinx/common/ad_data_in.v",
"sha256": "2c41a1bdce5ba97c6741d347f8574f5d6bf336a0327003739d8b1e615a3c345d"
} |
For the jtag_to_c_probe module, does its static structure suggest the synthesized sequential cell counts we get, and can you summarize whether the area and critical path delay figures look reasonable given the module's complexity? | jtag_to_c_probe has 11 inputs and 3 outputs, 2 always blocks and 4 assign statements with a cyclomatic complexity of 12, which is consistent with the synthesis result of 111 gates and 111 cells including 32 $_DFFE_PN0P_ and 2 $_DFF_PN0_ flip-flops plus 2 clock_crossing_fifo instances. The synthesized area is 115.5 with... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/debug/jtag_to_c_probe.v | jtag_to_c_probe | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "jtag_to_c_probe",
"port_count": {
"inputs": 11,
"outputs": 3,
"inouts": 0,
"total": 14
},
"signal_count": {
"wires": 2,
"regs": 2,
"parameters": 5,
"total": 4
},
"always_blocks": 2,
"assign... | multi_tool | static_analyzer+synthesis_tool | compositional | f6e64944edbe | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the jtag_to_c_probe module, does its static structure suggest the synthesized sequential cell counts we get, and can you summarize whether the area and critical path delay figures look reasonable given the module's complexity?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module... | 2b5c799b7c2d | 0e9ec139f2b8 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/debug/jtag_to_c_probe.v",
"sha256": "b4a502e87e9e89b27a541ad51c91f5965a385e6a5c134daeed457d042c2deb4c"
} |
For ram_delay_reg, how consistent are the RTL analysis and the CDFG structure — can you summarize the module's port/complexity profile, what the control/data-flow graph contains, and whether the RTL-to-netlist mapping raised any issues? | The static analysis of ram_delay_reg reports 1 input port, 0 outputs, 1 always block, 4 parameters, and a cyclomatic complexity of 4 across 71 lines of code, with no lint warnings. Its CDFG has 8 nodes and 303 edges (average degree 37.88), consisting of 2 $add nodes, 1 $dffe, 1 altsyncram, 3 port_inputs, and 1 port_out... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/ram_delay_reg.v | ram_delay_reg | cross_stage_mapper+graph_extractor+static_analyzer | [
{},
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"clock": [
"clock"
]
},
"alignment_score": 100.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 1,
"netlist_wires": 224,
"netlist_cells": 0,
"mapped_signals": 1,
"unmapped_signals":... | multi_tool | cross_stage_mapper+graph_extractor+static_analyzer | compositional | 3792c007681e | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For ram_delay_reg, how consistent are the RTL analysis and the CDFG structure — can you summarize the module's port/complexity profile, what the control/data-flow graph contains, and whether the RTL-to-netlist mapping raised any issues?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mappi... | 8490c44590d9 | 0ef2da63568b | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/ram_delay_reg.v",
"sha256": "c2c78fd5533e7bc82a68dc77bd127ccee338b3be2fde601ab942e5a82a3512df"
} |
For the altera_avalon_sc_fifo module, the RTL-to-netlist mapping shows an alignment score of 39.66 with 35 unmapped signals, while its And-Inverter Graph (AIG) representation contains 680 nodes and 1664 edges — how do these results compare, and what do they suggest about the RTL-to-gate-level correspondence of the desi... | The altera_avalon_sc_fifo module maps poorly from RTL to the netlist, with an alignment score of only 39.66 because just 23 of 58 RTL signals were mapped while 35 remain unmapped (against 288 netlist wires). Meanwhile, its AIG contains 680 nodes and 1664 edges, including 261 AND gates, 364 inverters, and a single memor... | github_repos/pConst_basic_verilog/example_projects/quartus_test_prj_template_v4/ip/jtag_io/synthesis/submodules/altera_avalon_sc_fifo.v | altera_avalon_sc_fifo | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"in_startofpacket": [
"in_startofpacket"
],
"drop_on_error": [
"drop_on_error"
],
"in_endofpacket": [
"in_endofpacket"
],
"wire": [],
"in_pkt_eop_arrive": [],
"next_full": [
"next_f... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 9677cee386d9 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For the altera_avalon_sc_fifo module, the RTL-to-netlist mapping shows an alignment score of 39.66 with 35 unmapped signals, while its And-Inverter Graph (AIG) representation contains 680 nodes and 1664 edges — how do these results compare, and what do they suggest about the RTL-to-gate-level correspondence o... | 95f5165a1419 | 0f521444fc80 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "example_projects/quartus_test_prj_template_v4/ip/jtag_io/synthesis/submodules/altera_avalon_sc_fifo.v",
"sha256": "b71ebd28aab28bd9393df54e92fada1d4b02d0c8817afca0d6d497871dcf8850"
} |
For the i2c_master module, how does the RTL-to-netlist mapping quality compare with the complexity indicated by its CDFG — for instance, do the number of unmapped signals and the graph's node and edge counts suggest the mapping is incomplete because of design complexity? Please give the alignment score, unmapped signal... | The RTL-to-netlist mapping for i2c_master achieved an alignment score of 57.53 with 31 unmapped signals out of 73 RTL signals, while its CDFG contains 294 nodes and 2968 edges (avg_degree 10.1), dominated by 103 $mux nodes. Given the dense control/data-flow structure, the moderate alignment score and substantial unmapp... | github_repos/alexforencich_verilog-ethernet/example/NetFPGA_SUME/fpga/rtl/i2c_master.v | i2c_master | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rst": [
"rst"
],
"wire": [],
"missed_ack_reg": [],
"mode_write_multiple_reg": [],
"last_scl_i_reg": [],
"missed_ack": [
"missed_ack"
],
"phy_write_bit": [
"phy_write_bit"
],
"del... | multi_tool | cross_stage_mapper+graph_extractor | compositional | fb9b8acaaf15 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the i2c_master module, how does the RTL-to-netlist mapping quality compare with the complexity indicated by its CDFG — for instance, do the number of unmapped signals and the graph's node and edge counts suggest the mapping is incomplete because of design complexity? Please give the alignment score, unmap... | 32aae405a5eb | 0f5f87509da7 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/NetFPGA_SUME/fpga/rtl/i2c_master.v",
"sha256": "ff46775d79e00853c9008f668ae9dfb71ad2cb93d6fec783aa08e527f207efb4"
} |
For the module fec_rot_20, how does its control/dataflow graph (CDFG) structure compare with its source-level complexity metrics — in particular, what do the CDFG node composition and the code complexity numbers tell us about the nature of this design? | The CDFG of fec_rot_20 has 90 nodes and 264 edges with 88 $xor nodes, showing the module is essentially a pure XOR network (avg degree 2.93), while the source analysis reports only 71 lines of code, cyclomatic complexity 2, and 380 operators across 32 assign statements. Together this indicates a structurally simple but... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/ethernet_fec/fec_rot_20.v | fec_rot_20 | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
...[61518 chars elided]...
"node_count": 90,
"edge_count": 264,
"graph_properties": {
"node_types": {
"$xor": 88,
"port_input": 1,
"port_output": 1
},
"avg_degree": 2.93,
"module_name": "fec... | multi_tool | graph_extractor+static_analyzer | compositional | f159add5daf6 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module fec_rot_20, how does its control/dataflow graph (CDFG) structure compare with its source-level complexity metrics — in particular, what do the CDFG node composition and the code complexity numbers tell us about the nature of this design?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "... | 160c737481ff | 0f61631b423e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/ethernet_fec/fec_rot_20.v",
"sha256": "9b83b31d5bc5daeaf3f5616d680ffd48cd668946687a20662cb693659cc2782a"
} |
For the crc32_dat48 module, how does the structure seen in the DFG relate to the synthesized results, and what delay-oriented optimization trade-offs would you expect if you applied it? | The DFG for crc32_dat48 contains 150 nodes (143 xor6 plus 1 crc32_dat48_factor) with 1113 edges, matching the synthesis result of 144 gates (143 xor6 and 1 crc32_dat48_factor) and a critical path delay of 222.06 with area 144.0 and power 0.144. Applying the delay-focused optimization (e.g., pipelining and logic duplica... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/crc/crc32_dat48.v | crc32_dat48 | graph_extractor+optimization_advisor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"target_metric": "delay"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[39779 chars elided]...
"node_count": 150,
"edge_count": 1113,
"graph_properties": {
"node_types": {
"crc32_dat48_factor": 1,
"port_input": 4,
"port_output": 2,
"xor6": 143
},
"avg_degree... | multi_tool | graph_extractor+optimization_advisor+synthesis_tool | compositional | c9cadc384959 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the crc32_dat48 module, how does the structure seen in the DFG relate to the synthesized results, and what delay-oriented optimization trade-offs would you expect if you applied it?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
...[39779 chars elided]...
"node_... | 5b9aba3b8abc | 1053b12c3dd6 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/crc/crc32_dat48.v",
"sha256": "e87d8df0ca41a3050eaf416f96ecf56f98f2375a5d77c8962dd815171d2ce520"
} |
For the ODELAYE2 module, how do the port and signal structure compare to the synthesis results, and given an area-focused optimization estimate, what trade-offs should I expect? | ODELAYE2 has 13 total ports (11 inputs and 2 outputs), 1 reg, 8 parameters, and a cyclomatic complexity of 3 across 36 lines of code, yet synthesis produced 0 gates and 0 cells with 12 wires and 20 wire bits, suggesting the logic optimizes away entirely. If you apply the area optimization recipes (e.g., aggressive reso... | github_repos/aolofsson_oh/xilibs/dv/ODELAYE2.v | ODELAYE2 | optimization_advisor+static_analyzer+synthesis_tool | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ODELAYE2 -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"... | multi_tool | optimization_advisor+static_analyzer+synthesis_tool | compositional | 6ff7dae3c530 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ODELAYE2 module, how do the port and signal structure compare to the synthesis results, and given an area-focused optimization estimate, what trade-offs should I expect?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
... | b619003bbd60 | 108415de0864 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "xilibs/dv/ODELAYE2.v",
"sha256": "c5933ecc499471174e0573d83261db3cfc0cd1514d05dd6493d6cf85b719e23c"
} |
For the ct_had_pcfifo module, is the delay optimization worthwhile given its complexity, and what does the module look like structurally? | The delay-focused optimization for ct_had_pcfifo is projected to reduce delay by -20.0 while costing 10.0 more area and 5.0 more power, and it suggests pipelining arithmetic operations and logic duplication to reduce fanout. The module is fairly complex, with 9 always blocks, 25 assign statements, 5 regs, 30 wires, 12 ... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/had/rtl/ct_had_pcfifo.v | ct_had_pcfifo | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_had_pcfifo",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"... | multi_tool | optimization_advisor+static_analyzer | compositional | 2cbe16975e4c | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ct_had_pcfifo module, is the delay optimization worthwhile given its complexity, and what does the module look like structurally?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top ct_had_pcfifo",
"opt ... | 8c8f029fc992 | 108b6c737f69 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/had/rtl/ct_had_pcfifo.v",
"sha256": "f2efc8eda5f885157cc305652ac2d362bc79339fe28fbfc294991ea94e00f59a"
} |
For the ODELAYE2 module, how reliable is the RTL-to-netlist signal mapping, and if I apply the recommended area-optimization recipes, what impact should I expect on delay and power? | The cross-stage mapping for ODELAYE2 succeeded with an alignment score of 78.57, mapping 11 of 14 RTL signals while leaving 3 unmapped (to, value, and output). The area-targeted optimization recipes (e.g., synth -top ODELAYE2 -flatten, opt -full; share -aggressive; opt) are estimated to improve area by -15.0 and power ... | github_repos/aolofsson_oh/xilibs/dv/ODELAYE2.v | ODELAYE2 | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "area"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"CLKIN": [
"CLKIN"
],
"CNTVALUEOUT": [
"CNTVALUEOUT"
],
"to": [],
"INC": [
"INC"
],
"C": [
"CNTVALUEOUT",
"CLKIN",
"C",
"INC",
"CE"
],
"LDPIPEEN": [
... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | 82e03e957e47 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the ODELAYE2 module, how reliable is the RTL-to-netlist signal mapping, and if I apply the recommended area-optimization recipes, what impact should I expect on delay and power?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"CLKIN": [
"CLKIN"
],
"CNTVALU... | de3c0410eea9 | 108415de0864 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "xilibs/dv/ODELAYE2.v",
"sha256": "c5933ecc499471174e0573d83261db3cfc0cd1514d05dd6493d6cf85b719e23c"
} |
For system_top, how well did the RTL signals carry over into the netlist, and does the structural picture from the AIG graph agree with that mapping result? | The cross-stage mapping reports a 100.0 alignment score with all 46 RTL signals mapped and 0 unmapped, against 84 netlist wires. This is consistent with the AIG graph for system_top, which contains 76 nodes and 564 edges with an average degree of 7.42, including 3 ad_iobuf instances, 28 inout ports, 26 output ports, an... | github_repos/analogdevicesinc_hdl/projects/cn0506/zed/system_top_mii.v | system_top | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"led_ar_a_c2m": [
"led_ar_a_c2m"
],
"hdmi_data": [
"hdmi_data_e",
"hdmi_data"
],
"link_st_b": [
"link_st_b"
],
"i2s_sdata_in": [
"i2s_sdata_in"
],
"led_al_c_c2m": [
"led... | multi_tool | cross_stage_mapper+graph_extractor | compositional | be0a8fcf0701 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For system_top, how well did the RTL signals carry over into the netlist, and does the structural picture from the AIG graph agree with that mapping result?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"led_ar_a_c2m": [
"led_ar_a_c2m"
],
"hdmi_data": [
... | 6c823201c6e7 | 1090455a236d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/cn0506/zed/system_top_mii.v",
"sha256": "d226103719469ca13be5b753bde724ed4027993640132856fc34a2e8e933cdfc"
} |
For the oh_lfsr module, if I apply the area-focused optimization suggestions, how would the current synthesized area, delay, and power figures be expected to change, and what synthesis recipe should I run to achieve that? | The current synthesis of oh_lfsr reports an area of 126.0, delay of 221.6, and power of 0.095, and the area optimization is estimated to improve area by -15.0 and power by -10.0 at the cost of a +5.0 delay penalty. The recommended recipe is 'synth -top oh_lfsr -flatten; opt -full; share -aggressive; opt; abc -g gates -... | github_repos/aolofsson_oh/stdlib/rtl/oh_lfsr.v | oh_lfsr | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top oh_lfsr -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"t... | multi_tool | optimization_advisor+synthesis_tool | compositional | 6b8ea44f2d4a | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_lfsr module, if I apply the area-focused optimization suggestions, how would the current synthesized area, delay, and power figures be expected to change, and what synthesis recipe should I run to achieve that?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_met... | a1de4987b818 | 10926a17e1ea | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_lfsr.v",
"sha256": "1ed2704e38427ed01d86f1e9faf54a035b45b2a0fe92ded1c93ea89c84d902fd"
} |
For the oh_lfsr module, if I apply the recommended area optimization recipes, what are the estimated area, delay, and power impacts, and how do these relate to the finding from the RTL-to-netlist signal mapping that reg and value were left unmapped? | For oh_lfsr, the area optimization is estimated to reduce area by -15.0 and power by -10.0 but increase delay by 5.0, with trade-offs that aggressive sharing increases routing complexity. The signal mapping only aligned 3 of 5 RTL signals (score 60.0), leaving reg and value unmapped even though the netlist has 134 wire... | github_repos/aolofsson_oh/stdlib/rtl/oh_lfsr.v | oh_lfsr | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "area"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"en": [
"en"
],
"reg": [],
"clk": [
"clk"
],
"nreset": [
"nreset"
],
"value": []
},
"alignment_score": 60.0,
"unmapped_elements": [
"reg",
"value"
],
"mapping_statistics": {... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | 553da7defa74 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the oh_lfsr module, if I apply the recommended area optimization recipes, what are the estimated area, delay, and power impacts, and how do these relate to the finding from the RTL-to-netlist signal mapping that reg and value were left unmapped?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_... | 2236243b74da | 10926a17e1ea | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_lfsr.v",
"sha256": "1ed2704e38427ed01d86f1e9faf54a035b45b2a0fe92ded1c93ea89c84d902fd"
} |
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