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 axis_register, how does the structure of its and-inverter graph compare to the complexity reported by static analysis of the RTL — in particular, how many AND and NOT nodes does the AIG contain versus the number of always blocks and assign statements in the source, and do the port counts agree? | The AIG for axis_register has 118 $_AND_ nodes and 168 $_NOT_ nodes (327 nodes, 784 edges overall), while the RTL source contains 4 always blocks and 24 assign statements with a cyclomatic complexity of 24. The AIG shows 10 input ports and 8 output ports, which is fewer than the 15 inputs and 15 outputs counted on the ... | github_repos/corundum_corundum/fpga/lib/pcie/example/AU280/fpga_axi/rtl/axis_register.v | axis_register | graph_extractor+static_analyzer | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$aigmap.cc:118:execute$350",
"type": "$_AND_",
"attributes": {},
"parameters": {}
},
{
"id": "$auto$aigmap.cc:118:execute$354",
"type": "$_AND_",
"attr... | multi_tool | graph_extractor+static_analyzer | compositional | 2d32e7ce3faa | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For axis_register, how does the structure of its and-inverter graph compare to the complexity reported by static analysis of the RTL — in particular, how many AND and NOT nodes does the AIG contain versus the number of always blocks and assign statements in the source, and do the port counts agree?
[graph_ex... | 252e73460343 | 2231f7c1cc63 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/AU280/fpga_axi/rtl/axis_register.v",
"sha256": "ebb03f4f7184b4c45f47ee4448e627f8c40348d08f98e727eb9e7f86f4402fea"
} |
For the system_top module, how does the port structure seen in the CDFG compare with the declared port counts from static analysis, and is the design consistent with a purely structural top level? | The CDFG of system_top contains 29 input ports, 31 output ports, and 21 inout ports, which is broader than the static analysis count of 26 inputs, 27 outputs, and 13 inouts (66 total). Both views agree that system_top is purely structural: the CDFG shows the graph is dominated by the system_bd instance plus a few $mux,... | github_repos/analogdevicesinc_hdl/projects/ad9081_fmca_ebz/s10soc/system_top.v | system_top | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:206$ternary$4",
"type": "$mux",
"attributes": {
"src": "<tmp>:206.21-208.25"
},
"parameters": {
"WIDTH": "00000000000000000000000000000001"
}
... | multi_tool | graph_extractor+static_analyzer | compositional | 53a150ea53df | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the system_top module, how does the port structure seen in the CDFG compare with the declared port counts from static analysis, and is the design consistent with a purely structural top level?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
... | eaf276160fb8 | 225ab93d0763 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/ad9081_fmca_ebz/s10soc/system_top.v",
"sha256": "634dc2d98aac08e9b1a13d09d1566e63c70d64da083d2c545e48e0eb26688f1b"
} |
For the util_adcfifo module, can you summarize its code complexity and how it translates into hardware cost and performance after medium-level delay and power optimization? | The util_adcfifo source is 175 lines of code with a cyclomatic complexity of 21, and after synthesis it maps to 492 gates occupying an area of 534.0. The dominant cells are the 330 $_SDFF_PN0_ flip-flops, reflecting its 7 regs and FIFO storage, and the optimized design achieves a delay of 326.13 with a power of 0.492. | github_repos/analogdevicesinc_hdl/library/util_adcfifo/util_adcfifo.v | util_adcfifo | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "util_adcfifo",
"port_count": {
"inputs": 6,
"outputs": 2,
"inouts": 0,
"total": 8
},
"signal_count": {
"wires": 5,
"regs": 7,
"parameters": 10,
"total": 12
},
"always_blocks": 6,
"assign_st... | multi_tool | static_analyzer+synthesis_tool | compositional | ea725aed2233 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the util_adcfifo module, can you summarize its code complexity and how it translates into hardware cost and performance after medium-level delay and power optimization?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "util_adcfifo",
"port_count": {
"inputs": 6,... | ac0fc8f94236 | 22753c4e5784 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/util_adcfifo/util_adcfifo.v",
"sha256": "5d0e5435bb0e26903c26de6835067cb8c596cd9bfb8ccb581ab7fabca2a8c3d9"
} |
For the erx module, how well does the RTL-to-netlist signal mapping line up with the structural analysis of the RTL, and which signals did not get mapped? | The static analysis of erx shows 36 RTL signals in a module with 21 ports (11 inputs and 10 outputs) and 172 lines of code, and the cross-stage mapping successfully matched 34 of those 36 signals to 49 netlist wires for an alignment score of 94.44. The only unmapped elements were the generic 'input' and 'output' port c... | github_repos/aolofsson_oh/elink/hdl/erx.v | erx | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rxrd_wait": [
"rxrd_wait"
],
"soft_reset": [
"soft_reset"
],
"rx_active": [
"rx_active"
],
"rxrr_wait": [
"rxrr_wait"
],
"rxo_wr_wait_p": [
"rxo_wr_wait_p"
],
"rx_acc... | multi_tool | cross_stage_mapper+static_analyzer | compositional | b2369031de2a | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the erx module, how well does the RTL-to-netlist signal mapping line up with the structural analysis of the RTL, and which signals did not get mapped?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rxrd_wait": [
"rxrd_wait"
],
"soft_reset": [
"soft... | 298ca13f8220 | 23285dacc0eb | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "elink/hdl/erx.v",
"sha256": "bb02570b31cf953a597c8dda78f0054561a1e26fe650a8cd0034b661c92f1f73"
} |
For the erx module, how does the port-level structure seen in the AIG compare with the source-level analysis, and is the structural complexity of the module a concern? | The AIG shows 34 nodes and 1412 edges with 15 port_output and 15 port_input nodes at an average degree of 41.53, while the source analysis reports 21 total ports (11 inputs and 10 outputs) across 172 lines of code. Despite the dense connectivity suggested by the high average degree, the design remains simple at the sou... | github_repos/aolofsson_oh/elink/hdl/erx.v | erx | graph_extractor+static_analyzer | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "erx_clocks",
"type": "erx_clocks",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:91.15-103.27"
},
"parameters": {}
... | multi_tool | graph_extractor+static_analyzer | compositional | ab538b5dc77c | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the erx module, how does the port-level structure seen in the AIG compare with the source-level analysis, and is the structural complexity of the module a concern?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "erx_clocks",
"t... | 7e265013b7da | 23285dacc0eb | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "elink/hdl/erx.v",
"sha256": "bb02570b31cf953a597c8dda78f0054561a1e26fe650a8cd0034b661c92f1f73"
} |
For the module ct_spsram_512x96, how does its CDFG connectivity relate to the synthesized netlist characteristics, and what area/delay trade-off would the area-focused optimization bring? | The CDFG of ct_spsram_512x96 has 8 nodes and 300 edges with an average degree of 37.5, consistent with the synthesis result of 300 wire bits and 7 wires connected to the single ct_f_spsram_512x96 cell. Synthesis reports an area of 1.0 with a critical path delay of 50.0, while the area optimization recipe estimates an a... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/l2c/rtl/ct_spsram_512x96.v | ct_spsram_512x96 | 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",
"nodes": [
{
"id": "x_ct_f_spsram_512x96",
"type": "ct_f_spsram_512x96",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:64.21-72.2"
},
...[2... | multi_tool | graph_extractor+optimization_advisor+synthesis_tool | compositional | 0233286a9bc5 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module ct_spsram_512x96, how does its CDFG connectivity relate to the synthesized netlist characteristics, and what area/delay trade-off would the area-focused optimization bring?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": ... | bb1565f6208c | 2399e5f95858 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/l2c/rtl/ct_spsram_512x96.v",
"sha256": "f7e24af3f50ba4769de22e1e5af26d4fe2cf98a6d3fe48d4e468cc53c213df4a"
} |
For the gray_to_bin module, the dataflow graph is essentially a chain of XOR gates. Given the DFG structure and the delay-focused optimization results, is pipelining a reasonable choice, and what delay/area/power impact was estimated? | The DFG for gray_to_bin contains 9 nodes and 21 edges, with 7 $xor nodes plus one input and one output port, forming a serial XOR chain. The delay-oriented optimization estimated a delay improvement of -20.0, at the cost of 10.0 more area and 5.0 more power, so pipelining the XOR chain via register retiming is a reason... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/gray_to_bin.v | gray_to_bin | graph_extractor+optimization_advisor | [
{
"graph_type": "DFG"
},
{
"target_metric": "delay"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:42$xor$1",
"type": "$xor",
"attributes": {
"src": "<tmp>:42.21-42.39"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WIDTH... | multi_tool | graph_extractor+optimization_advisor | compositional | ee50e9ba092d | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the gray_to_bin module, the dataflow graph is essentially a chain of XOR gates. Given the DFG structure and the delay-focused optimization results, is pipelining a reasonable choice, and what delay/area/power impact was estimated?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_... | 54be6b01dd7a | 240dcef0d22e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/gray_to_bin.v",
"sha256": "68182875093c56f762dec0730b98e98bc4f7c0f3c7d7de58c3b1727bbc5283d2"
} |
For the axi_ad9434 module, how do the structural complexity seen in its CDFG compare with the synthesis results for delay and power, and what does that suggest about optimizing this design? | The CDFG of axi_ad9434 has 36 nodes and 965 edges with an average degree of 26.81, dominated by 21 input ports and 12 output ports, while synthesis at medium optimization reports a critical path delay of 69.52, power of 0.003, and an area of 3.0 with only 3 cells (axi_ad9434_core, axi_ad9434_if, up_axi). Since the desi... | github_repos/analogdevicesinc_hdl/library/axi_ad9434/axi_ad9434.v | axi_ad9434 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "i_core",
"type": "axi_ad9434_core",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:174.5-207.26"
},
"parameters": {
... | multi_tool | graph_extractor+synthesis_tool | compositional | aae305aee0e9 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the axi_ad9434 module, how do the structural complexity seen in its CDFG compare with the synthesis results for delay and power, and what does that suggest about optimizing this design?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id"... | b955669f1cc6 | 2422f1bc3f2e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9434/axi_ad9434.v",
"sha256": "88601bbbf5b5c272193065c9f579977e0746390244b398fe847c4f00484bb8b1"
} |
For the gray_to_bin module, how does the dataflow structure shown in its DFG compare with the RTL-to-netlist mapping results, and what does that suggest about the current implementation state? | The DFG for gray_to_bin contains 9 nodes and 21 edges, consisting of 7 $xor operators plus 1 input port and 1 output port with an average degree of 2.33, reflecting its chain of Gray-to-binary XOR conversions. However, the mapping reports an alignment score of 0.0 with 0 of 1 RTL signals mapped and 1 unmapped element (... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/gray_to_bin.v | gray_to_bin | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "DFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"bits": []
},
"alignment_score": 0.0,
"unmapped_elements": [
"bits"
],
"mapping_statistics": {
"rtl_signals": 1,
"netlist_wires": 17,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 1
},
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 73ee42fc9b29 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}] | Question: For the gray_to_bin module, how does the dataflow structure shown in its DFG compare with the RTL-to-netlist mapping results, and what does that suggest about the current implementation state?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"bits": []
},
"alignment_scor... | b448a9ae2e8c | 240dcef0d22e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/gray_to_bin.v",
"sha256": "68182875093c56f762dec0730b98e98bc4f7c0f3c7d7de58c3b1727bbc5283d2"
} |
For the ct_spsram_256x52 module, how do the RTL-to-netlist signal mapping results compare with its AIG structure, and do any signals fail to map? | All 6 RTL signals map successfully with an alignment score of 100.0 and 0 unmapped signals, though WEN maps to two netlist wires (WEN and GWEN) while the 7 netlist wires contain 0 cells. The AIG for ct_spsram_256x52 has 8 nodes and 167 edges with an average degree of 20.88, comprising 1 ct_f_spsram_256x52 instance, 6 i... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_spsram_256x52.v | ct_spsram_256x52 | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"D": [
"D"
],
"WEN": [
"WEN",
"GWEN"
],
"Q": [
"Q"
],
"GWEN": [
"GWEN"
],
"CEN": [
"CEN"
],
"CLK": [
"CLK"
]
},
"alignment_score": 100.0,
"unmapp... | multi_tool | cross_stage_mapper+graph_extractor | compositional | eed9f13b337f | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For the ct_spsram_256x52 module, how do the RTL-to-netlist signal mapping results compare with its AIG structure, and do any signals fail to map?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"D": [
"D"
],
"WEN": [
"WEN",
"GWEN"
],
"Q": [... | e55fcde2ff71 | 24a803de9a60 | 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_spsram_256x52.v",
"sha256": "c8d1a970b1982f3a7174de60d47fb68cc76ce346e6d9c440b5b4ed6f458b9e11"
} |
For temp_sense_s5, how would you summarize the design's structure from its AIG representation and whether the area-focused optimization is worthwhile, considering its impact on delay? | temp_sense_s5's AIG contains 2935 nodes and 7199 edges with an average degree of 2.45, dominated by 1624 NOT gates, 1236 AND gates, and 61 $_DFF_P_ flip-flops. The area optimization (e.g., 'share -aggressive') is estimated to improve area by -15.0 and power by -10.0, but at the cost of a 5.0 increase in delay, since ag... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/debug/temp_sense_s5.v | temp_sense_s5 | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$aigmap.cc:118:execute$1206",
"type": "$_AND_",
"attributes": {},
"parameters": {}
},
{
"id": "$auto$aigmap.cc:118:execute$1210",
"type": "$_AND_",
"at... | multi_tool | graph_extractor+optimization_advisor | compositional | c66bd792a464 | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For temp_sense_s5, how would you summarize the design's structure from its AIG representation and whether the area-focused optimization is worthwhile, considering its impact on delay?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto... | ed7ba92a95f2 | 2501f803c142 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/debug/temp_sense_s5.v",
"sha256": "f5815de38f93ee913986788e80708069538e32f7f839deb7a8fb1206a4214a6f"
} |
For oh_and2, the power-focused optimization analysis predicts certain gains, and the synthesis results give actual area, delay, and power figures—how do these compare, and what trade-offs should I expect if I apply the recommended power optimizations? | Synthesis of oh_and2 currently yields an area of 1.0, a delay of 50.0, and a power of 0.001 with a single $_AND_ cell and 3 wires. The power optimization recipes (including clock gating and operand isolation) are estimated to improve power by -25.0 with 5.0 improvements in both area and delay, but they warn that power ... | github_repos/aolofsson_oh/stdlib/rtl/oh_and2.v | oh_and2 | optimization_advisor+synthesis_tool | [
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top oh_and2",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gating",... | multi_tool | optimization_advisor+synthesis_tool | compositional | 375ef25dd3ce | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For oh_and2, the power-focused optimization analysis predicts certain gains, and the synthesis results give actual area, delay, and power figures—how do these compare, and what trade-offs should I expect if I apply the recommended power optimizations?
[optimization_advisor {"target_metric": "power"}]
{
"st... | 22e197df7a40 | 24ac2d29b8fa | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_and2.v",
"sha256": "dbffb963593a07acb1054f8dcb3e1b555f78128bab6ebedde0edfdf5957e9f45"
} |
For the module ls_sub_top, do the RTL-to-netlist mapping results and the control/data-flow graph structure agree on the scale of the design — specifically, how many RTL signals were mapped and with what alignment score, and how many nodes and edges appear in the CDFG? | The mapping is clean: all 58 RTL signals were mapped with zero unmapped signals, giving an alignment score of 100.0, against 93 netlist wires. The CDFG extracted from ls_sub_top contains 54 nodes and 1248 edges, including 4 ahb_dummy_top instances and 1 ahb_matrix_1_6_sub, with 26 input ports and 23 output ports, so bo... | github_repos/XUANTIE-RV_wujian100_open/soc/ls_sub_top.v | ls_sub_top | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"lsbus_dummy1_s1_haddr": [
"lsbus_dummy1_s1_haddr"
],
"hmain0_lsbus_s10_hwdata": [
"hmain0_lsbus_s10_hwdata"
],
"dummy3_lsbus_s5_hready": [
"dummy3_lsbus_s5_hready"
],
"lsbus_dummy3_s5_hwrite": [... | multi_tool | cross_stage_mapper+graph_extractor | compositional | d3bf9ad646da | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the module ls_sub_top, do the RTL-to-netlist mapping results and the control/data-flow graph structure agree on the scale of the design — specifically, how many RTL signals were mapped and with what alignment score, and how many nodes and edges appear in the CDFG?
[cross_stage_mapper {}]
{
"status": "s... | 23af5ada3f0f | 2540348979b0 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/wujian100_open",
"commit": "83e297583bb3454b688f9f27d6bc20ff3276ad32",
"path": "soc/ls_sub_top.v",
"sha256": "f697fd48cc388d8f154b2d821bd309025acf47bdaa3b8fd8e5196ce26adec2f7"
} |
For pcileech_mux, the RTL-to-netlist mapping shows an alignment score of 86.11 with 10 unmapped signals out of 72 RTL signals — how does this partial mapping reconcile with the synthesized netlist figures of 2563 gates and 6570 wires, and which specific signals were lost? | The pcileech_mux netlist has 6570 wires and 2563 cells but zero mapped physical cells in the RTL mapping, with 62 of 72 RTL signals mapped and 10 unmapped (including dout_valid, buffer, ctx_reg, data_reg, integrity, idle_count, output, dout_buf_valid, idx_base, and highest). The synthesis used 2563 gates at area 4049.5... | github_repos/ufrisk_pcileech-fpga/ac701_ft601/src/pcileech_mux.sv | pcileech_mux | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [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_din": [
... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | ee1a18d598d5 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For pcileech_mux, the RTL-to-netlist mapping shows an alignment score of 86.11 with 10 unmapped signals out of 72 RTL signals — how does this partial mapping reconcile with the synthesized netlist figures of 2563 gates and 6570 wires, and which specific signals were lost?
[cross_stage_mapper {}]
{
"status"... | bb042d80a2f9 | 26206a9f32bd | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/ufrisk/pcileech-fpga",
"commit": "c538c4170678c13f723dc921905fb81ff3c71d8e",
"path": "ac701_ft601/src/pcileech_mux.sv",
"sha256": "0c264ebf3ab163fbe122bc90ad03cb874809ac9f3e73048b563a768abbd5e63c"
} |
For the apb0_leaf_mux module, how large and complex is the design, and is it worthwhile to apply the aggressive area-reduction suggestions given the potential timing impact? | The apb0_leaf_mux module has 734 lines of code with a cyclomatic complexity of 107, nesting depth of 31, 551 operators, 83 inputs and 42 outputs, and it instantiates documentation, apb0_leaf_mux, and apb0_state_ctrl. Applying the recommended area recipes (including mux sharing via muxcover and aggressive resource shari... | github_repos/XUANTIE-RV_wujian100_open/soc/apb0.v | apb0_leaf_mux | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top apb0_leaf_mux -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 062acd8b32c3 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the apb0_leaf_mux module, how large and complex is the design, and is it worthwhile to apply the aggressive area-reduction suggestions given the potential timing impact?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"sy... | 5ed949f9c5a7 | 268e8cabeb1a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/wujian100_open",
"commit": "83e297583bb3454b688f9f27d6bc20ff3276ad32",
"path": "soc/apb0.v",
"sha256": "b5ee495858be9989183ce2a5047e10c15267dc690bfd9820b58c96f3712cc145"
} |
For ct_vfmau_lza_42, how do the module's structural characteristics from its CDFG relate to the area-optimization recommendations, and what trade-offs should I expect if I apply the suggested sharing optimizations? | The CDFG of ct_vfmau_lza_42 contains 11 nodes and 20 edges, including only a single $reduce_or operator plus 2 logic_or, 1 logic_and, and 3 logic_not cells with an average node degree of 1.82, which is why the area-focused advice recommends aggressive resource sharing of arithmetic operators. The estimated gains are -1... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/vfmau/rtl/ct_vfmau_lza_42.v | ct_vfmau_lza_42 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:39$reduce_or$1",
"type": "$reduce_or",
"attributes": {
"src": "<tmp>:39.18-39.34"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
... | multi_tool | graph_extractor+optimization_advisor | compositional | 948870d12873 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For ct_vfmau_lza_42, how do the module's structural characteristics from its CDFG relate to the area-optimization recommendations, and what trade-offs should I expect if I apply the suggested sharing optimizations?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"n... | 0e734461fbbe | 26905a68f66c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/vfmau/rtl/ct_vfmau_lza_42.v",
"sha256": "bd4bfc04c7e7e628615cd04b11784d455e8815a38390c8e6eb7906bd8c310107"
} |
For the ad_g2b module, the synthesis with medium optimization reports an area, delay, and power, and the cross-stage mapping reports 18 netlist wires but zero mapped RTL signals. Can you summarize what these results together indicate about the post-synthesis state of ad_g2b, including its gate composition and the mappi... | After medium-level optimization, ad_g2b synthesizes to 7 XOR gates with an area of 14.0, a delay (and critical path estimate) of 143.42, and power of 0.007, with 4 wires totaling 56 wire bits. The cross-stage mapping shows 18 netlist wires but 0 RTL signals and 0 netlist cells mapped, giving an alignment score of 0.0, ... | github_repos/analogdevicesinc_hdl/library/common/ad_g2b.v | ad_g2b | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 0,
"netlist_wires": 18,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 0
},
"error": null
}
[synthesis_too... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 3d76006d6d2a | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ad_g2b module, the synthesis with medium optimization reports an area, delay, and power, and the cross-stage mapping reports 18 netlist wires but zero mapped RTL signals. Can you summarize what these results together indicate about the post-synthesis state of ad_g2b, including its gate composition and... | 04a39cfe8489 | 2692aca9d0f2 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/common/ad_g2b.v",
"sha256": "4ce0833408423911b091131901ca6ae8e0800faaa8159089f92756fe27124a04"
} |
For the asic_rsync module, how does the structure shown in the AIG graph analysis (node and flip-flop counts) compare with the cell and area results after medium-level synthesis, and what do they together tell you about the design? | The AIG contains 5 nodes and 8 edges, with 2 nodes of type $_DFF_PN0_ plus 2 input ports and 1 output port, and synthesis at the medium optimization level yields exactly 2 gates of type $_DFF_PN0_ with an area of 2.0, matching the graph's flip-flop count. This confirms asic_rsync is simply two reset-affected D flip-flo... | github_repos/aolofsson_oh/asiclib/hdl/asic_rsync.v | asic_rsync | graph_extractor+synthesis_tool | [
{
"graph_type": "AIG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$ff.cc:337:slice$79",
"type": "$_DFF_PN0_",
"attributes": {
"src": "<tmp>:17.4-21.66"
},
"parameters": {}
},
{
"id": "$auto$ff.cc:337:slice$80",
... | multi_tool | graph_extractor+synthesis_tool | compositional | 450eb5176bda | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the asic_rsync module, how does the structure shown in the AIG graph analysis (node and flip-flop counts) compare with the cell and area results after medium-level synthesis, and what do they together tell you about the design?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_typ... | 6de9f7cca1e6 | 26b7909b936a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_rsync.v",
"sha256": "514efb3d8d5add556ab877ef64cb67341a2350bfe4af733837fb05c80bf46adc"
} |
For the lfsr module, what code characteristics support the case for applying the recommended area optimizations like mux sharing, and what trade-offs should I expect? Note the module's complexity from static analysis and the estimated impact of the area optimization. | The lfsr module is fairly complex for its size, with 51 lines of code, cyclomatic complexity 5, nesting depth 4, and 208 operators across 1 always block and 2 assign statements, which supports applying area-focused optimizations such as multiplexer sharing and aggressive resource sharing. The optimization advisor estim... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/random/lfsr.v | lfsr | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top lfsr -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 | 31ae49decfbe | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the lfsr module, what code characteristics support the case for applying the recommended area optimizations like mux sharing, and what trade-offs should I expect? Note the module's complexity from static analysis and the estimated impact of the area optimization.
[optimization_advisor {"target_metric": "... | 6e163124e958 | 26e75f978643 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/random/lfsr.v",
"sha256": "dceea48b2995afe0029fddb8f5d64377099067cb4e4b58a7a7f9a8113260309c"
} |
For axi_dma_desc_mux, compare the structure seen in its CDFG with the synthesized implementation: how do the control-flow muxes and register elements relate to the final cell counts, and does the design look control-dominated given its area and delay figures? | The CDFG for axi_dma_desc_mux contains 97 nodes and 1072 edges (average degree 11.05) with 20 $mux nodes, 8 $dffe and 4 $dff elements, indicating a control-dominated datapath that maps to a synthesized gate count of 491 cells at an area of 1017.0. After synthesis the register elements expand to 92 $_DFFE_PP_ and 33 $_D... | github_repos/corundum_corundum/fpga/lib/axi/rtl/axi_dma_desc_mux.v | axi_dma_desc_mux | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:145$logic_and$1",
"type": "$logic_and",
"attributes": {
"src": "<tmp>:145.29-145.69"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",... | multi_tool | graph_extractor+synthesis_tool | compositional | 3b319941d3a8 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For axi_dma_desc_mux, compare the structure seen in its CDFG with the synthesized implementation: how do the control-flow muxes and register elements relate to the final cell counts, and does the design look control-dominated given its area and delay figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"sta... | 3477aae882a0 | 26e6823ca7c2 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/axi/rtl/axi_dma_desc_mux.v",
"sha256": "5ab36d7829d1b3ee3c56944b6299cc10eae6c3ed4394d027ce4f22baedee0537"
} |
For the pcie_ptile_if_tx module, how well did the RTL signals survive into the synthesized netlist, and do the synthesis figures suggest that any unmapped signals could be part of registered logic? Please combine the RTL-to-netlist mapping results with the area, delay, power, and cell counts. | The pcie_ptile_if_tx module has an alignment score of 83.78 with 31 of 37 RTL signals mapped and 6 unmapped (wire, have_p_credit_reg, have_cpl_credit_reg, have_np_credit_reg, tx_st_ready_delay_reg, max_payload_size_fc_reg). The netlist contains 440 cells across an area of 513.5, with 258 $_SDFF_PN0_ plus 3 $_SDFF_PP0_ ... | github_repos/corundum_corundum/fpga/lib/pcie/rtl/pcie_ptile_if_tx.v | pcie_ptile_if_tx | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"valid": [
"tx_wr_req_tlp_valid",
"m_axis_rd_req_tx_seq_num_valid",
"tx_st_valid",
"tx_msi_wr_req_tlp_valid",
"tx_rd_req_tlp_va... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 0d5c2cab2f04 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the pcie_ptile_if_tx module, how well did the RTL signals survive into the synthesized netlist, and do the synthesis figures suggest that any unmapped signals could be part of registered logic? Please combine the RTL-to-netlist mapping results with the area, delay, power, and cell counts.
[cross_stage_ma... | 4b58f4af8f64 | 27546da3b171 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/rtl/pcie_ptile_if_tx.v",
"sha256": "49c4f3424ab1bd4c429e38e42eead52c9232d8375731aa816cfae84c79d3c360"
} |
For the module axis_baser_rx_64, how well does the RTL-to-netlist signal mapping line up with the structure seen in its CDFG, considering both the mapping coverage and the CDFG's size and dominant node types? | The mapping covers only 14 of 30 RTL signals (16 unmapped, alignment score 46.67), with unmapped elements including crc_state, m_axis_tlast_reg, and state_reg, even though the netlist has 3116 wires. The CDFG for axis_baser_rx_64 has 172 nodes and 4006 edges with an average degree of 23.29, dominated by 51 $mux and 40 ... | github_repos/corundum_corundum/fpga/lib/eth/rtl/axis_baser_rx_64.v | axis_baser_rx_64 | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"m_axis_tvalid": [
"m_axis_tvalid",
"m_axis_tvalid_next"
],
"clk": [
"clk"
],
"ptp_ts_borrow_reg": [
"ptp_ts_borrow_reg"
],
"crc_state": [],
"cfg_rx_enable": [
"cfg_rx_enable"
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | c0b403e38b8a | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the module axis_baser_rx_64, how well does the RTL-to-netlist signal mapping line up with the structure seen in its CDFG, considering both the mapping coverage and the CDFG's size and dominant node types?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"m_axis_tvalid": ... | 49cdc571a797 | 27d0c64ec0a1 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/axis_baser_rx_64.v",
"sha256": "38b4d6ec695420176906c71584dd40d741f4289121a970497f69e26945cafe5b"
} |
For asic_tielo, given that the AIG graph analysis shows the module contains only a single constant-0 output port with no edges, is it still worth applying the area-optimization recipes, and what trade-off would that involve? | The AIG for asic_tielo has node_count 1 (a single port_output z tied to constant 0) and edge_count 0, so there is essentially no logic for the area recipes such as 'share -aggressive' to optimize. Even so, the area optimization flow reports an estimated area improvement of -15.0, but this comes with a delay penalty of ... | github_repos/aolofsson_oh/asiclib/hdl/asic_tielo.v | asic_tielo | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "z",
"type": "port_output",
"bits": [
"0"
]
}
],
"edges": [],
"node_count": 1,
"edge_count": 0,
"graph_properties": {
"node_types": {
"port_output": 1
... | multi_tool | graph_extractor+optimization_advisor | compositional | f1c88c94c86f | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For asic_tielo, given that the AIG graph analysis shows the module contains only a single constant-0 output port with no edges, is it still worth applying the area-optimization recipes, and what trade-off would that involve?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AI... | 4719819898e7 | 27d18834b5b6 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_tielo.v",
"sha256": "feae3ec3a4218b7b45cecf9fd22419b43c5f45b53688e6bfd54b920bf3cabbbe"
} |
For the module ssio_sdr_out, how does its CDFG structure relate to the synthesized cell count, and how does that compare with its overall code complexity and post-synthesis delay and power figures? | The ssio_sdr_out module's CDFG contains 6 nodes (one $dff and one oddr plus 2 input and 2 output ports) and 7 edges, which matches the synthesis result of 2 cells (one $_DFF_P_ and one oddr). Despite 55 lines of code and a cyclomatic complexity of 3 with 41 operators across 1 always block and 1 assign statement, it map... | github_repos/alexforencich_verilog-ethernet/rtl/ssio_sdr_out.v | ssio_sdr_out | graph_extractor+static_analyzer+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$procdff$3",
"type": "$dff",
"attributes": {
"src": "<tmp>:73.1-75.4"
},
"parameters": {
"CLK_POLARITY": "1",
"WIDTH": "000000000000000000000000
...[1... | multi_tool | graph_extractor+static_analyzer+synthesis_tool | compositional | 7077b10495b7 | [{"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 ssio_sdr_out, how does its CDFG structure relate to the synthesized cell count, and how does that compare with its overall code complexity and post-synthesis delay and power figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
... | 8029dd839902 | 27fe6c6a8890 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/ssio_sdr_out.v",
"sha256": "3eb5251c2cc1bdbf8d380e1954d5d8cdf107c3977541afe219e4a1034cc7eb80"
} |
For the module fec_rot_n2112, compare the structure seen in its CDFG with the results after medium-level optimization for delay and power: how do the XOR operations in the graph map onto the final gate implementation and its reported cost figures? | The CDFG of fec_rot_n2112 contains 270 nodes and 804 edges, with 268 of the nodes being $xor operations plus one input and one output port. After medium optimization targeting delay and power, these become 197 gates (136 XNOR and 61 XOR cells) with an area of 394.0, a delay of 390.33, and a power of 0.197. | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/ethernet_fec/fec_rot_n2112.v | fec_rot_n2112 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:103$xor$80",
"type": "$xor",
"attributes": {
"src": "<tmp>:103.5-104.26"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_... | multi_tool | graph_extractor+synthesis_tool | compositional | 57ef682c2079 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module fec_rot_n2112, compare the structure seen in its CDFG with the results after medium-level optimization for delay and power: how do the XOR operations in the graph map onto the final gate implementation and its reported cost figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "succe... | 3f58f4807404 | 281b00cb832a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/ethernet_fec/fec_rot_n2112.v",
"sha256": "1a49c6621efbb616d4c7111f713d7b9cf2aebe89e4eab932828029f656607a4d"
} |
For the axis_baser_rx_64 module, how does the complexity seen in its CDFG compare with the cost reported after delay- and power-aware synthesis at the medium optimization level, and do the cell counts in the synthesis statistics match the final log? | The CDFG of axis_baser_rx_64 contains 172 nodes and 4006 edges, dominated by 51 $mux and 40 $eq operations with an average degree of 23.29, and synthesis reports an area of 2568.5, a delay of 569.0, a power of 1.525, and 1525 gates including 504 $_NAND_ cells and 238 $_DFF_P_ cells. The final log confirms the same cell... | github_repos/corundum_corundum/fpga/lib/eth/rtl/axis_baser_rx_64.v | axis_baser_rx_64 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:210$eq$1",
"type": "$eq",
"attributes": {
"src": "<tmp>:210.23-210.48"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+synthesis_tool | compositional | 4f5e4b4c10f0 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the axis_baser_rx_64 module, how does the complexity seen in its CDFG compare with the cost reported after delay- and power-aware synthesis at the medium optimization level, and do the cell counts in the synthesis statistics match the final log?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "suc... | 9be22ceed61a | 27d0c64ec0a1 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/axis_baser_rx_64.v",
"sha256": "38b4d6ec695420176906c71584dd40d741f4289121a970497f69e26945cafe5b"
} |
For the module system_top, the CDFG analysis reports a fairly dense control/dataflow structure; how does that density compare with the actual structural complexity after medium-level synthesis, considering the delay and power optimization results and the statistics logged during the synthesis run? | The CDFG for system_top has 108 nodes with 18904 edges (an average degree of 175.04), which reflects heavy interconnect; after medium-level synthesis, this translates into 12311 gates, 7294 wires and 15780 wire bits, with area 23074.5, delay 1243.77 and power 12.311. The synthesis log confirms 12311 cells with 0 proces... | github_repos/analogdevicesinc_hdl/projects/ad9213_dual_ebz/s10soc/system_top.v | system_top | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:233$eq$1",
"type": "$eq",
"attributes": {
"src": "<tmp>:233.23-233.39"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+synthesis_tool | compositional | 9102dec81463 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module system_top, the CDFG analysis reports a fairly dense control/dataflow structure; how does that density compare with the actual structural complexity after medium-level synthesis, considering the delay and power optimization results and the statistics logged during the synthesis run?
[graph_ext... | c48445cc53c6 | 2849128e3072 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/ad9213_dual_ebz/s10soc/system_top.v",
"sha256": "9a20736e6f518a23c312f037cf5721fefeed7fcf96b190ee20e9b3ecde1ab443"
} |
For the ssio_sdr_out module, how do the estimated area and delay trade-offs from area-focused optimization compare with the module's structural complexity from the full static analysis, and is the optimization worth it? | The area optimization for ssio_sdr_out is estimated to improve area by -15.0 and power by -10.0 while increasing delay by 5.0, with trade-offs noting that area optimization may increase delay and aggressive sharing increases routing complexity. Given the module's low structural complexity (cyclomatic complexity 3, nest... | github_repos/alexforencich_verilog-ethernet/rtl/ssio_sdr_out.v | ssio_sdr_out | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ssio_sdr_out -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 2ff015569ff5 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ssio_sdr_out module, how do the estimated area and delay trade-offs from area-focused optimization compare with the module's structural complexity from the full static analysis, and is the optimization worth it?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metri... | 9b8639e30ac8 | 27fe6c6a8890 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/ssio_sdr_out.v",
"sha256": "3eb5251c2cc1bdbf8d380e1954d5d8cdf107c3977541afe219e4a1034cc7eb80"
} |
For the oh_aoi221 module, how does the operator mix in its CDFG compare to the cell types reported after medium-optimization synthesis, and what are the resulting area, delay, and power figures? | The CDFG of oh_aoi221 has 11 nodes and 14 edges, with node types of 2 $and, 2 $or, and 1 $not plus 5 input ports and 1 output port, while synthesis maps this to 4 gates: 2 $_AND_, 1 $_NAND_, and 1 $_NOR_. Synthesis reports an area of 4.0, a delay (critical path estimate) of 68.21, and a power of 0.004. | github_repos/aolofsson_oh/stdlib/rtl/oh_aoi221.v | oh_aoi221 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:18$and$1",
"type": "$and",
"attributes": {
"src": "<tmp>:18.18-18.25"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WID... | multi_tool | graph_extractor+synthesis_tool | compositional | b89e97c632b7 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_aoi221 module, how does the operator mix in its CDFG compare to the cell types reported after medium-optimization synthesis, and what are the resulting area, delay, and power figures?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
... | 692f17ea17ff | 2898b3b1535c | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_aoi221.v",
"sha256": "b632b36bbf15ff44f4bc5569f1f427c2221850c38361d5aab06806dc85da7768"
} |
For the ct_lsu_st_wb module, how do its complexity metrics compare with what an area-focused optimization would buy me, and is that trade-off worth it? | The ct_lsu_st_wb module has 272 lines of code, cyclomatic complexity 15, nesting depth 7, and 1084 operators across 3 always blocks and 29 assign statements, so aggressive resource sharing is plausible given the large operator count. An area-targeted optimization is estimated to reduce area by 15.0 and power by 10.0 at... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_st_wb.v | ct_lsu_st_wb | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ct_lsu_st_wb -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 2e16b9db6510 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ct_lsu_st_wb module, how do its complexity metrics compare with what an area-focused optimization would buy me, and is that trade-off worth it?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ct_lsu_st_wb ... | 8b9753df5e6d | 28aa749cba15 | 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_st_wb.v",
"sha256": "e25adf86323519e777af1b2e0e7fd1582c3d385b3e5b344f4d910ed13b9dc7fa"
} |
For the stats_counter module, if I apply the recommended area-focused optimization flow (mux sharing and aggressive resource sharing), what trade-offs should I expect relative to the current synthesized results? | The current synthesis reports an area of 1302.5, a delay of 500.27, a power of 0.722, and 722 gates for stats_counter. The area optimization estimates an area improvement of -15.0 and a power improvement of -10.0, but at the cost of a 5.0 increase in delay, since aggressive sharing also increases routing complexity. | github_repos/corundum_corundum/fpga/common/rtl/stats_counter.v | stats_counter | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top stats_counter -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+synthesis_tool | compositional | a4c632136850 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the stats_counter module, if I apply the recommended area-focused optimization flow (mux sharing and aggressive resource sharing), what trade-offs should I expect relative to the current synthesized results?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "are... | 2b15c6218b8a | 2952d03ea886 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/common/rtl/stats_counter.v",
"sha256": "63f77dea123d1414482cd2ddb3942f6f55550824034f42b81d4875acd7a4b7bf"
} |
For reset_control_tb, is applying the recommended area optimization worthwhile given the code characteristics, and what impact would it have on delay and power? | The module reset_control_tb is a 61-line code file with cyclomatic complexity 7, nesting depth 6, and 243 operators, and instantiates reset_control. The area optimization (aggressive resource sharing of arithmetic operators) is estimated to improve area by -15.0 and power by -10.0, but at the cost of delay increasing b... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/synchronization/reset_control_tb.v | reset_control_tb | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top reset_control_tb -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{... | multi_tool | optimization_advisor+static_analyzer | compositional | 267e9e462898 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For reset_control_tb, is applying the recommended area optimization worthwhile given the code characteristics, and what impact would it have on delay and power?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top rese... | a7beaed9fdcb | 297441510d5e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/synchronization/reset_control_tb.v",
"sha256": "b3bcb26881d1a6c0d08a416e12b087f447285111f215e6d9589a202dfe4ac399"
} |
For gearbox_67_40, how does the control/dataflow structure captured in the DFG compare with the source-level complexity metrics — can you summarize the module's size and structure using figures from both? | The gearbox_67_40 DFG contains 66 nodes and 4521 edges with an average degree of 68.5, dominated by 22 $eq nodes, 14 $adff nodes, and 6 $mux nodes, while at the source level the module has 176 lines of code, a cyclomatic complexity of 25, 7 always blocks, and 15 regs. The very high edge-to-node ratio in the DFG is cons... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/communication/gearbox_67_40.v | gearbox_67_40 | graph_extractor+static_analyzer | [
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:215$ternary$31",
"type": "$mux",
"attributes": {
"src": "<tmp>:215.13-215.33"
},
"parameters": {
"WIDTH": "00000000000000000000000000000001"
}
... | multi_tool | graph_extractor+static_analyzer | compositional | a6dba38e6dfb | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For gearbox_67_40, how does the control/dataflow structure captured in the DFG compare with the source-level complexity metrics — can you summarize the module's size and structure using figures from both?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
... | 6a6f19d80d1f | 298b861eae39 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/communication/gearbox_67_40.v",
"sha256": "3286325e313bd903918c1c7c7b3b0a3ca9fa2a945a95fcb8535aa8f3c1afb3d6"
} |
For gearbox_67_40, how does the structure of its control/data-flow graph relate to the synthesized area figures — in particular, what dominates the CDFG and what dominates the gate-level cell count? | The CDFG of gearbox_67_40 has 125 nodes and 5406 edges, with multiplexers dominating ($mux: 69 and $pmux: 4, versus 12 $adff and 22 $eq nodes). Synthesis at medium optimization yields 2936 gates and an area of 2986.5, dominated by combinational logic — 1507 $_AND_ cells plus 504 $_NOR_ and 289 $_NAND_ — while sequentia... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/communication/gearbox_67_40.v | gearbox_67_40 | graph_extractor+synthesis_tool | [
{
"graph_type": "CDFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$$auto$proc_rom.cc:155:do_switch$35$rdreg[0]",
"type": "$adff",
"attributes": {},
"parameters": {
"ARST_POLARITY": "00000000000000000000000000000001",
"ARST_VALUE":... | multi_tool | graph_extractor+synthesis_tool | compositional | 51d4fd254450 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For gearbox_67_40, how does the structure of its control/data-flow graph relate to the synthesized area figures — in particular, what dominates the CDFG and what dominates the gate-level cell count?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
... | 7f74d1897307 | 298b861eae39 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/communication/gearbox_67_40.v",
"sha256": "3286325e313bd903918c1c7c7b3b0a3ca9fa2a945a95fcb8535aa8f3c1afb3d6"
} |
For the oh_sdffsq module, can you combine the RTL structure analysis with the cross-stage mapping results to summarize how the register 'reg' fared between RTL and the netlist, and how complex the module is? | The RTL analysis of oh_sdffsq shows 15 lines of code with cyclomatic complexity 3, nesting depth 0, 28 operators, 1 always block, and an instantiation of 'array', while the cross-stage mapping reports 1 RTL signal ('reg'), 12 netlist wires, and 0 netlist cells. The register 'reg' is completely unmapped, with 0 mapped s... | github_repos/aolofsson_oh/stdlib/rtl/oh_sdffsq.v | oh_sdffsq | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg": []
},
"alignment_score": 0.0,
"unmapped_elements": [
"reg"
],
"mapping_statistics": {
"rtl_signals": 1,
"netlist_wires": 12,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 1
},
"... | multi_tool | cross_stage_mapper+static_analyzer | compositional | fc49a252c7ea | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_sdffsq module, can you combine the RTL structure analysis with the cross-stage mapping results to summarize how the register 'reg' fared between RTL and the netlist, and how complex the module is?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"reg": []
},
"... | 99a813fff2f4 | 2a5c045ffc33 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_sdffsq.v",
"sha256": "c591557b13fe2c05794744caa576d3df253647cf0e34394686d2ee61bf56ebd5"
} |
For the oh_sdffsq module, how does its structural complexity as an AIG compare with its source-code complexity metrics? | After mapping oh_sdffsq to an AIG, the graph has 14 nodes and 21 edges with an average degree of 1.5, including 3 AND nodes, 4 NOT nodes, 1 DFF, 5 input ports, and 1 output port. At the source level the module has 15 lines of code out of 25 total lines, a cyclomatic complexity of 3, an operator count of 28, one always ... | github_repos/aolofsson_oh/stdlib/rtl/oh_sdffsq.v | oh_sdffsq | graph_extractor+static_analyzer | [
{
"graph_type": "AIG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$aigmap.cc:118:execute$85",
"type": "$_AND_",
"attributes": {},
"parameters": {}
},
{
"id": "$auto$aigmap.cc:118:execute$89",
"type": "$_AND_",
"attrib... | multi_tool | graph_extractor+static_analyzer | compositional | 4f7f234724af | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_sdffsq module, how does its structural complexity as an AIG compare with its source-code complexity metrics?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$aigmap.cc:118:execute$85",
"type": "$_AND_",
"attri... | 22111dea8061 | 2a5c045ffc33 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_sdffsq.v",
"sha256": "c591557b13fe2c05794744caa576d3df253647cf0e34394686d2ee61bf56ebd5"
} |
For example_core_pcie_s10, how does the structure shown in its CDFG relate to the power optimization opportunity, and what improvement and trade-offs are expected? | The CDFG of example_core_pcie_s10 has 35 nodes and 4568 edges with an average degree of 130.51, including one $and, one $logic_not, 25 port_input and 6 port_output nodes, plus the core_pcie and pcie_s10_if instances. Given this structure, power optimization via clock gating and operand isolation is recommended, with an... | github_repos/corundum_corundum/fpga/lib/pcie/example/common/rtl/example_core_pcie_s10.v | example_core_pcie_s10 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:203$and$2",
"type": "$and",
"attributes": {
"src": "<tmp>:203.22-203.53"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_... | multi_tool | graph_extractor+optimization_advisor | compositional | 3fcce414a051 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For example_core_pcie_s10, how does the structure shown in its CDFG relate to the power optimization opportunity, and what improvement and trade-offs are expected?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:203$and$2",
... | 8e1ac6d8a320 | 2ab6b65e53c3 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/common/rtl/example_core_pcie_s10.v",
"sha256": "33b88c3944c80cd49694e693f96552a2d7c48cba2f1033163944acb19d9c7c85"
} |
For the system_top module, did synthesis preserve all the RTL port names in the final netlist, and how do the synthesized wire counts relate to the RTL port count and the overall design statistics? | The RTL-to-netlist mapping for system_top shows a 100.0 alignment score with 36 of 36 RTL signals mapped and 0 unmapped, so every port such as reset (mapped to reset_b, reset_a, and reset) survived synthesis. The synthesized netlist has 42 wires and 263 wire bits with 36 ports and 67 port bits, which matches the mappin... | github_repos/analogdevicesinc_hdl/projects/cn0506/zcu102/system_top_rgmii.v | system_top | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"led_ar_a_c2m": [
"led_ar_a_c2m"
],
"link_st_b": [
"link_st_b"
],
"led_al_c_c2m": [
"led_al_c_c2m"
],
"rgmii_tx_ctl_a": [
"rgmii_tx_ctl_a"
],
"led_bl_a_c2m": [
"led_bl_a_c2m"
... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 0338b5e3791d | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the system_top module, did synthesis preserve all the RTL port names in the final netlist, and how do the synthesized wire counts relate to the RTL port count and the overall design statistics?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"led_ar_a_c2m": [
"led... | 784bb7c47df6 | 2ad23a96448d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/cn0506/zcu102/system_top_rgmii.v",
"sha256": "f60c3fdea9cf648512b4439d1dbb46a9dcc9071e281a05e2525edde31273d00f"
} |
For the module ptp_td_leaf, how does its structural complexity from the code analysis compare with the resources reported after medium-level delay- and power-optimized synthesis, and is the code lint-clean? | The ptp_td_leaf module is a large, lint-clean design with 783 lines of code, cyclomatic complexity 125, 80 registers, and 13 always blocks, and synthesis maps it to 4830 gates with an area of 7828.0, a delay of 761.63, and 4.83 power, including 314 $_DFFE_PP_ and 201 $_SDFF_PP0_ flip-flops. | github_repos/alexforencich_verilog-ethernet/rtl/ptp_td_leaf.v | ptp_td_leaf | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ptp_td_leaf",
"port_count": {
"inputs": 9,
"outputs": 9,
"inouts": 0,
"total": 18
},
"signal_count": {
"wires": 12,
"regs": 80,
"parameters": 27,
"total": 92
},
"always_blocks": 13,
"assign... | multi_tool | static_analyzer+synthesis_tool | compositional | cc2de3477e13 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module ptp_td_leaf, how does its structural complexity from the code analysis compare with the resources reported after medium-level delay- and power-optimized synthesis, and is the code lint-clean?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ptp_td_leaf",
... | 46bc5e1397a4 | 2b4d44c0689a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/ptp_td_leaf.v",
"sha256": "aef2c2e2a1d6eedf49e81618025974f288e08d7f9dfe7bc8dbb4d9c1e6283d95"
} |
For the asic_delay module, how well did the RTL carry over to the netlist, and does that match what the source code itself suggests about its complexity? | The RTL-to-netlist mapping for asic_delay is perfect, with an alignment score of 100.0 and all 2 RTL signals mapped to the 2 netlist wires with 0 unmapped elements. This is consistent with the source, which has 6 lines of code, cyclomatic complexity 1, nesting depth 0, and 13 operators, meaning the purely combinational... | github_repos/aolofsson_oh/asiclib/hdl/asic_delay.v | asic_delay | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"z": [
"z"
],
"a": [
"a"
]
},
"alignment_score": 100.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 2,
"netlist_wires": 2,
"netlist_cells": 0,
"mapped_signals": 2,
"... | multi_tool | cross_stage_mapper+static_analyzer | compositional | e0f06de52759 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the asic_delay module, how well did the RTL carry over to the netlist, and does that match what the source code itself suggests about its complexity?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"z": [
"z"
],
"a": [
"a"
]
},
"alignment_sco... | ebfa6998238e | 2b654dbd589a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_delay.v",
"sha256": "86b0709b875308d66c5411a6b1d194e8c5e4476c947e681ad8c76e78790ac121"
} |
For the arbiter module, the RTL-to-netlist mapping shows some signals that didn't carry over, and the delay optimization advice suggests certain trade-offs. Combining these two views, which RTL signals are unmapped, and how much delay improvement and area penalty does the recommended speed-focused optimization flow est... | The unmapped RTL signals in arbiter are wire, grant_valid_reg, and masked_request_valid, with only 4 of 7 RTL signals mapped. The delay optimization flow estimates a delay improvement of -20.0 at the cost of a 10.0 area increase, plus higher power consumption as a stated trade-off. | github_repos/corundum_corundum/fpga/lib/pcie/rtl/arbiter.v | arbiter | cross_stage_mapper+optimization_advisor | [
{},
{
"target_metric": "delay"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"grant_valid": [
"grant_valid"
],
"rst": [
"rst"
],
"wire": [],
"clk": [
"clk"
],
"request_valid": [
"request_valid"
],
"grant_valid_reg": [],
"masked_request_valid": []
}... | multi_tool | cross_stage_mapper+optimization_advisor | compositional | b0024ae3a37a | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the arbiter module, the RTL-to-netlist mapping shows some signals that didn't carry over, and the delay optimization advice suggests certain trade-offs. Combining these two views, which RTL signals are unmapped, and how much delay improvement and area penalty does the recommended speed-focused optimizatio... | 7dab63d31fef | 2bbbac85ef0d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/rtl/arbiter.v",
"sha256": "a001507c82843e36e133dea75491fc044f56660fac0aff0127cf3afec7f927e0"
} |
For system_top, can you compare the port and connectivity information from its DFG with the structural details from the source analysis, and note any discrepancies? | The DFG for system_top has 81 nodes and 368 edges with an average degree of 4.54, counting 26 input, 35 output, and 15 inout port nodes, while the source analysis reports only 34 total ports (15 inputs, 16 outputs, 3 inouts). The DFG likely reflects elaborated bit-level connections, whereas the source-level counts are ... | github_repos/analogdevicesinc_hdl/projects/adrv9009/s10soc/system_top.v | system_top | graph_extractor+static_analyzer | [
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:194$and$2",
"type": "$and",
"attributes": {
"src": "<tmp>:194.25-194.51"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+static_analyzer | compositional | 72f674006ef1 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For system_top, can you compare the port and connectivity information from its DFG with the structural details from the source analysis, and note any discrepancies?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:194$and$2",
... | 297c280f6f54 | 2bcc65535087 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "projects/adrv9009/s10soc/system_top.v",
"sha256": "e53ac612ea50f80df8f63347d315da2c211db6d6bbc493c419a418e8cc235ac2"
} |
For the arbiter module, its AIG contains a mix of combinational and sequential nodes — how does that composition relate to the area-optimization advice, and what delay trade-off should I expect if I follow it? | The arbiter's AIG has 81 nodes and 207 edges, including 29 AND nodes, 37 NOT nodes, and 7 $_SDFFE_PP0N_ flip-flops, so the area is dominated by combinational logic that the recommended recipes (such as 'share -aggressive' resource sharing) target. The area-focused optimization is estimated to improve area by -15.0 but ... | github_repos/corundum_corundum/fpga/lib/pcie/rtl/arbiter.v | arbiter | graph_extractor+optimization_advisor | [
{
"graph_type": "AIG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": [
{
"id": "$auto$aigmap.cc:118:execute$216",
"type": "$_AND_",
"attributes": {},
"parameters": {}
},
{
"id": "$auto$aigmap.cc:118:execute$220",
"type": "$_AND_",
"attr... | multi_tool | graph_extractor+optimization_advisor | compositional | 81119948049d | [{"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the arbiter module, its AIG contains a mix of combinational and sequential nodes — how does that composition relate to the area-optimization advice, and what delay trade-off should I expect if I follow it?
[graph_extractor {"graph_type": "AIG"}]
{
"status": "success",
"graph_type": "AIG",
"nodes": ... | d60a8ac9bf4b | 2bbbac85ef0d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/rtl/arbiter.v",
"sha256": "a001507c82843e36e133dea75491fc044f56660fac0aff0127cf3afec7f927e0"
} |
For the asic_dffq module, how well does the RTL-to-netlist mapping line up with the module's port and signal structure, and which parts of the design are not accounted for? | The asic_dffq module has 3 ports total (2 inputs, 1 output), 1 reg, and 8 lines of code, but the mapping only aligned 2 of the 4 RTL signals for an alignment score of 50.0, leaving q and reg unmapped even though the netlist only contains 2 wires and 0 cells. In short, the sequential output and register behavior capture... | github_repos/aolofsson_oh/asiclib/hdl/asic_dffq.v | asic_dffq | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"d": [
"d"
],
"q": [],
"reg": [],
"clk": [
"clk"
]
},
"alignment_score": 50.0,
"unmapped_elements": [
"q",
"reg"
],
"mapping_statistics": {
"rtl_signals": 4,
"netlist_wires": 2,
... | multi_tool | cross_stage_mapper+static_analyzer | compositional | a5e21ada5bdb | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the asic_dffq module, how well does the RTL-to-netlist mapping line up with the module's port and signal structure, and which parts of the design are not accounted for?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"d": [
"d"
],
"q": [],
"reg": [],
... | 1c61875f78d5 | 2c0f184603ba | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_dffq.v",
"sha256": "8670bc47aa570c818b1f4cf54d52cf27f96ac6ac9dd8265262b0b1f0f3449a1d"
} |
For the oh_nor3 module, can you summarize its structure and complexity by combining the structural analysis with the RTL-to-netlist cross-stage mapping results — for instance, how many assign statements and operators it has, how many lines of code, and how the netlist wiring compares to the RTL signal count found in th... | The oh_nor3 module is very simple structurally: it has 9 lines of code, 21 operators, 1 assign statement, cyclomatic complexity 1, one parameter, and zero always blocks. The cross-stage mapping shows 0 RTL signals mapped but 11 netlist wires and 0 netlist cells, consistent with an alignment score of 0.0 and the module'... | github_repos/aolofsson_oh/stdlib/rtl/oh_nor3.v | oh_nor3 | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 0,
"netlist_wires": 11,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 0
},
"error": null
}
[static_analyz... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 9857977e6f3c | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_nor3 module, can you summarize its structure and complexity by combining the structural analysis with the RTL-to-netlist cross-stage mapping results — for instance, how many assign statements and operators it has, how many lines of code, and how the netlist wiring compares to the RTL signal count f... | 68a1b1f90e0b | 2c73096f1f97 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_nor3.v",
"sha256": "c24a91ed460ee15b9fd36a3f71452185e1962ddc42c5c28812298a35a18c77f2"
} |
For ct_rtu_encode_32, considering its CDFG structure (node and edge counts, average degree) and the area-focused optimization recommendations, is pursuing the aggressive resource sharing suggested for area worthwhile, and what trade-offs should I expect? | The CDFG for ct_rtu_encode_32 has 32 nodes (30 $or gates plus one input and one output port) and 450 edges, giving a high average degree of 14.06, which already indicates dense connectivity; aggressive sharing on such a structure is warned to increase routing complexity. The area optimization is estimated to improve ar... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/rtu/rtl/ct_rtu_encode_32.v | ct_rtu_encode_32 | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:37$or$11",
"type": "$or",
"attributes": {
"src": "<tmp>:37.12-42.40"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WIDT... | multi_tool | graph_extractor+optimization_advisor | compositional | bb5eefbca731 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For ct_rtu_encode_32, considering its CDFG structure (node and edge counts, average degree) and the area-focused optimization recommendations, is pursuing the aggressive resource sharing suggested for area worthwhile, and what trade-offs should I expect?
[graph_extractor {"graph_type": "CDFG"}]
{
"status":... | 1685256fa13f | 2cbd4acf0c2a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/rtu/rtl/ct_rtu_encode_32.v",
"sha256": "b50d7c9faf452630f6eec0cd0f7a51f27bacbaadb6da001f82c368bc92d89bbe"
} |
For ct_biu_top, how does the connectivity shown in its DFG relate to its synthesis results, and does the cell breakdown match the submodule instances in the graph? | The DFG for ct_biu_top has 231 nodes, 4174 edges, and an average degree of 18.07, including one instance each of seven submodules such as ct_biu_csr_req_arbiter and ct_biu_lowpower; synthesis reports exactly those same 7 cells (gate_count 7), with 316 wires and 3414 wire bits, plus an area of 7.0, delay of 89.64, and p... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/biu/rtl/ct_biu_top.v | ct_biu_top | graph_extractor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "x_ct_biu_csr_req_arbiter",
"type": "ct_biu_csr_req_arbiter",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:1166.25-1182.2"
}... | multi_tool | graph_extractor+synthesis_tool | compositional | 35288d2ff8c4 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For ct_biu_top, how does the connectivity shown in its DFG relate to its synthesis results, and does the cell breakdown match the submodule instances in the graph?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "x_ct_biu_csr_req_arbiter"... | 8d1c5ad3240b | 2cdce96d9bad | 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_top.v",
"sha256": "aa986b784f17514dc08e4c8c131d701e58026b5019646dfcbec0b748ebdfe29c"
} |
For axi_dmac_reset_manager, the medium-level delay-optimized synthesis run reports a critical path of 205.29 and a gate count of 90 — how does this compare to the source complexity of the design, in terms of its 268 lines of code and cyclomatic complexity of 40, and do the sequential elements (23 DFFs and 4 sync bits) ... | Despite the axi_dmac_reset_manager source being fairly complex — 268 lines of code with a cyclomatic complexity of 40 and 611 operators — the synthesized netlist is small, at 90 gates with a critical path of 205.29. The synthesis produced 15 $_DFF_PP1_ plus 8 $_DFF_P_ flip-flops (23 total) against only 7 regs declared ... | github_repos/analogdevicesinc_hdl/library/axi_dmac/axi_dmac_reset_manager.v | axi_dmac_reset_manager | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "axi_dmac_reset_manager",
"port_count": {
"inputs": 15,
"outputs": 9,
"inouts": 0,
"total": 24
},
"signal_count": {
"wires": 6,
"regs": 7,
"parameters": 13,
"total": 13
},
"always_blocks": 7,
... | multi_tool | static_analyzer+synthesis_tool | compositional | 79e2925cf8c3 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For axi_dmac_reset_manager, the medium-level delay-optimized synthesis run reports a critical path of 205.29 and a gate count of 90 — how does this compare to the source complexity of the design, in terms of its 268 lines of code and cyclomatic complexity of 40, and do the sequential elements (23 DFFs and 4 s... | 84b1fd8470d7 | 2c42f036b5d6 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_dmac/axi_dmac_reset_manager.v",
"sha256": "0531706c60e6754a6460366dc4506b63292fea61dcff5ddbb038ff44938d6916"
} |
For ct_biu_top, given that every RTL signal mapped cleanly to the netlist, how suitable is the module for aggressive area optimization, and what cost in delay should I expect given its current structure and size? | ct_biu_top is a good candidate for area optimization: all 180 RTL signals mapped with an alignment score of 100.0 (0 unmapped), and the module is purely structural with 0 always blocks and cyclomatic complexity 2 across 1210 lines of code, so resource sharing should be safe. Applying the aggressive area recipes is esti... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/biu/rtl/ct_biu_top.v | ct_biu_top | cross_stage_mapper+optimization_advisor+static_analyzer | [
{},
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"lsu_biu_aw_vict_dp_req": [
"lsu_biu_aw_vict_dp_req"
],
"pad_biu_csr_cmplt": [
"pad_biu_csr_cmplt"
],
"pad_biu_acvalid": [
"pad_biu_acvalid"
],
"st_awvalid": [
"st_awvalid_gate",
...[9640 ... | multi_tool | cross_stage_mapper+optimization_advisor+static_analyzer | compositional | f02e39cc240c | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For ct_biu_top, given that every RTL signal mapped cleanly to the netlist, how suitable is the module for aggressive area optimization, and what cost in delay should I expect given its current structure and size?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"lsu_biu_aw_v... | 3a9e8d865a51 | 2cdce96d9bad | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/biu/rtl/ct_biu_top.v",
"sha256": "aa986b784f17514dc08e4c8c131d701e58026b5019646dfcbec0b748ebdfe29c"
} |
For the udp_ip_rx module, how well does the RTL-to-netlist signal mapping line up with the structure shown in its AIG graph — specifically, how many signals were mapped versus unmapped, what was the alignment score, and how many AIG nodes and edges does the graph contain? | The mapping covered 77 of 119 RTL signals with 42 unmapped, giving an alignment score of 64.71, while the AIG graph for udp_ip_rx contains 4682 nodes and 11772 edges with an average degree of 2.51. | github_repos/alexforencich_verilog-ethernet/rtl/udp_ip_rx.v | udp_ip_rx | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"m_udp_payload_axis_tready": [
"m_udp_payload_axis_tready_int_early",
"m_udp_payload_axis_tready"
],
"wire": [],
"m_ip_source_ip_reg": [],
"m_udp_payload_axis_tvalid": [
"m_udp_payload_axis_tvalid_int",
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | c3baaf91156f | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For the udp_ip_rx module, how well does the RTL-to-netlist signal mapping line up with the structure shown in its AIG graph — specifically, how many signals were mapped versus unmapped, what was the alignment score, and how many AIG nodes and edges does the graph contain?
[cross_stage_mapper {}]
{
"status"... | a3bdcdfeb5df | 2ce82be80f39 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/udp_ip_rx.v",
"sha256": "bed1fb03cabe705b9757bfa17e262dfc739ccf48700e04c234ebc276a5f527c1"
} |
For the emesh_decode module, given its CDFG structure and the area-focused optimization analysis, is the recommended resource-sharing strategy worthwhile, considering the estimated impact on area, delay, and power and the size of the control/dataflow graph? | The CDFG for emesh_decode is very small, with 14 nodes (1 $not gate, 1 input port, 12 output ports), only 2 edges, and an average node degree of 0.14, so there is essentially one logic operator available for the suggested sharing of arithmetic operators. The area optimization recommends recipes such as flattening and a... | github_repos/aolofsson_oh/emesh/hdl/emesh_decode.v | emesh_decode | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:35$not$1",
"type": "$not",
"attributes": {
"src": "<tmp>:35.30-35.40"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WID... | multi_tool | graph_extractor+optimization_advisor | compositional | 72fa533af7d6 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the emesh_decode module, given its CDFG structure and the area-focused optimization analysis, is the recommended resource-sharing strategy worthwhile, considering the estimated impact on area, delay, and power and the size of the control/dataflow graph?
[graph_extractor {"graph_type": "CDFG"}]
{
"statu... | fc89489aed46 | 2d56b739e903 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "emesh/hdl/emesh_decode.v",
"sha256": "fca480503a165cbe155bb9207bef37e41c85507a20c461436079d4348faff614"
} |
For the ct_had_sm module, how does the structure seen in its CDFG compare with its code-level complexity, and does anything suggest a mismatch between the module's port list in the graph and in the source? | The ct_had_sm module's CDFG has 63 nodes and 594 edges with an average degree of 9.43, dominated by 15 $eq nodes and 13 $mux nodes, consistent with its fairly high code complexity of cyclomatic complexity 43 and nesting depth 7 across 249 lines of code. However, the CDFG lists 9 port_input and 9 port_output nodes while... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/had/rtl/ct_had_sm.v | ct_had_sm | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:136$logic_and$5",
"type": "$logic_and",
"attributes": {
"src": "<tmp>:136.11-136.33"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",... | multi_tool | graph_extractor+static_analyzer | compositional | 6b6e68cdd2b7 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ct_had_sm module, how does the structure seen in its CDFG compare with its code-level complexity, and does anything suggest a mismatch between the module's port list in the graph and in the source?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
... | 239fdf21989d | 2da7af0c0d86 | 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_sm.v",
"sha256": "8e04c38b3727dd16acd6a55c20b688adc6dd16f408352fb9bc3e125f6a45a2ab"
} |
For the ad_edge_detect module, if I apply the suggested power optimizations, how would the estimated area and delay changes trade off against the current synthesized area and critical path delay, and what power reduction is expected? | The current implementation of ad_edge_detect has an area of 16.5, a delay of 79.58 (critical path estimate 79.58), and power of 0.004, built from 4 gates (1 $_ANDNOT_ and 3 $_SDFF_PP0_) plus 7 wires. Applying the clock gating and operand isolation suggestions for power is estimated to reduce power by -25.0 while improv... | github_repos/analogdevicesinc_hdl/library/common/ad_edge_detect.v | ad_edge_detect | optimization_advisor+synthesis_tool | [
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top ad_edge_detect",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_g... | multi_tool | optimization_advisor+synthesis_tool | compositional | 860c40d0d227 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ad_edge_detect module, if I apply the suggested power optimizations, how would the estimated area and delay changes trade off against the current synthesized area and critical path delay, and what power reduction is expected?
[optimization_advisor {"target_metric": "power"}]
{
"status": "success",
... | c34c4556a9ed | 2d23a98befb5 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/common/ad_edge_detect.v",
"sha256": "7b7d2cca032f82a9e62c49da166a71925e0580963713d9921f65550dc6b5dcce"
} |
For the parallella_gpio module, how does the structure of its dataflow graph compare with its synthesis results — can you summarize the module's complexity using both the DFG connectivity and the resulting cell/area numbers? | The DFG for parallella_gpio has 49 nodes and 502 edges with an average degree of 10.24, dominated by 32 port_input nodes plus one axi_gpio and one pgpio instance. Synthesis at medium optimization kept that structure essentially intact, producing only 26 cells (24 $_NOT_ plus the axi_gpio and pgpio submodules) with an a... | github_repos/aolofsson_oh/gpio/hdl/parallella_gpio.v | parallella_gpio | graph_extractor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:110$not$1",
"type": "$not",
"attributes": {
"src": "<tmp>:110.18-110.38"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+synthesis_tool | compositional | 6d2dd50dd8cb | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the parallella_gpio module, how does the structure of its dataflow graph compare with its synthesis results — can you summarize the module's complexity using both the DFG connectivity and the resulting cell/area numbers?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DF... | dedae7d5e029 | 2da938e5142d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "gpio/hdl/parallella_gpio.v",
"sha256": "eb829c72da71605a580a0f9840240864ee90815e43325e0f6d0134bd0705211c"
} |
For the ram_based_cam module, if I run the area-focused optimization flow on its CDFG, what improvement should I expect and how might the structure of the module's control/data-flow graph relate to that? | The ram_based_cam CDFG has 46 nodes and 502 edges with an average degree of 10.91, including 32 $reduce_and nodes and 5 cam_ram_block nodes, so there is significant repeated reduction logic that resource sharing could target. The area optimization recipe estimates -15.0 area and -10.0 power but at the cost of a 5.0 inc... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/ram_based_cam.v | ram_based_cam | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "area"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:85$reduce_and$1",
"type": "$reduce_and",
"attributes": {
"src": "<tmp>:85.27-85.37"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
... | multi_tool | graph_extractor+optimization_advisor | compositional | 5485b2203abe | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}] | Question: For the ram_based_cam module, if I run the area-focused optimization flow on its CDFG, what improvement should I expect and how might the structure of the module's control/data-flow graph relate to that?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
... | b0537c31c829 | 2e1de44b22cf | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/ram_based_cam.v",
"sha256": "43a677371d2e8235aac8fa3bb68da5078c851dba81cd66d3544264faffea4524"
} |
For the ram_based_cam module, how does the structure shown in its DFG relate to the module's overall complexity — specifically, what do the node counts and operator count suggest about where the design complexity comes from? | The DFG for ram_based_cam has 46 nodes and 502 edges, dominated by 32 $reduce_and nodes plus 5 cam_ram_block instantiations, while the static analysis reports an operator_count of 192 with cyclomatic complexity 8 across 48 lines of code. This shows the complexity comes mainly from the many reduction operations (32 $red... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/storage/ram_based_cam.v | ram_based_cam | graph_extractor+static_analyzer | [
{
"graph_type": "DFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "$<tmp>:85$reduce_and$1",
"type": "$reduce_and",
"attributes": {
"src": "<tmp>:85.27-85.37"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
... | multi_tool | graph_extractor+static_analyzer | compositional | 2c3aff48f193 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ram_based_cam module, how does the structure shown in its DFG relate to the module's overall complexity — specifically, what do the node counts and operator count suggest about where the design complexity comes from?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DF... | 716bd81694fd | 2e1de44b22cf | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/storage/ram_based_cam.v",
"sha256": "43a677371d2e8235aac8fa3bb68da5078c851dba81cd66d3544264faffea4524"
} |
For the fpga module, I want a quick sanity check of the design: how well do the RTL and netlist signal mappings agree, what does the control/dataflow structure look like, and does the code-level complexity support that? Please pull together the mapping agreement figure, the CDFG size/connectivity, and the static code c... | The RTL-to-netlist mapping is in excellent agreement at 98.36% with 60 of 61 RTL signals mapped (only 'wire' unmapped), and the CDFG contains 13 nodes and 7223 edges with an average degree of 555.62, dominated by the fpga_core, debounce_switch, IBUFDS_GTE4, and pcie4_uscale_plus_0 instances. This structural connectivit... | github_repos/corundum_corundum/fpga/lib/pcie/example/VCU1525/fpga/rtl/fpga.v | fpga | cross_stage_mapper+graph_extractor+static_analyzer | [
{},
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"pcie_tx_p": [
"pcie_tx_p"
],
"cfg_max_read_req": [
"cfg_max_read_req"
],
"wire": [],
"status_error_cor": [
"status_error_cor"
],
"pcie_refclk_p": [
"pcie_refclk_p"
],
...[3109 ... | multi_tool | cross_stage_mapper+graph_extractor+static_analyzer | compositional | ce15cb528fb0 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the fpga module, I want a quick sanity check of the design: how well do the RTL and netlist signal mappings agree, what does the control/dataflow structure look like, and does the code-level complexity support that? Please pull together the mapping agreement figure, the CDFG size/connectivity, and the sta... | 88f020e0c765 | 2ec5484f4630 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/VCU1525/fpga/rtl/fpga.v",
"sha256": "6a1f3f3c727e9c586868bd1e1f311726c8cfc07653ef691daedd5e60eb17c222"
} |
For the fpga module, how does its structural composition as seen in the CDFG compare with the source-level analysis, and what does that suggest about the design style? | The CDFG shows 13 nodes and 7223 edges with an average degree of 555.62, dominated by a single fpga_core instance alongside blocks like debounce_switch and pcie4_uscale_plus_0, which matches the source analysis reporting 6 inputs, 3 outputs, 60 wires, 16 parameters, 375 lines of code, and cyclomatic complexity of 1 wit... | github_repos/corundum_corundum/fpga/lib/pcie/example/VCU1525/fpga/rtl/fpga.v | fpga | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "core_inst",
"type": "fpga_core",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:377.1-461.2"
},
"parameters": {
... | multi_tool | graph_extractor+static_analyzer | compositional | 0b2f47042447 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the fpga module, how does its structural composition as seen in the CDFG compare with the source-level analysis, and what does that suggest about the design style?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "core_inst",
"... | 734c72b9ff39 | 2ec5484f4630 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/VCU1525/fpga/rtl/fpga.v",
"sha256": "6a1f3f3c727e9c586868bd1e1f311726c8cfc07653ef691daedd5e60eb17c222"
} |
For the eth_mac_mii module, how do the structural complexity of its CDFG and the projected power-optimized design trade off against each other if I apply the recommended power optimizations? | The CDFG of eth_mac_mii contains 32 nodes and 89 edges (avg_degree 2.78), including one eth_mac_1g and one mii_phy_if instance plus 13 input and 17 output ports. Applying the recommended power-focused optimizations such as clock gating is estimated to improve power by -25.0 while affecting area by 5.0 and delay by 5.0,... | github_repos/corundum_corundum/fpga/lib/eth/rtl/eth_mac_mii.v | eth_mac_mii | graph_extractor+optimization_advisor | [
{
"graph_type": "CDFG"
},
{
"target_metric": "power"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "eth_mac_1g_inst",
"type": "eth_mac_1g",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:140.1-172.2"
},
"parameters": ... | multi_tool | graph_extractor+optimization_advisor | compositional | d8d9e21990a0 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}] | Question: For the eth_mac_mii module, how do the structural complexity of its CDFG and the projected power-optimized design trade off against each other if I apply the recommended power optimizations?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id... | c2f47370983b | 2eccdfe10a94 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/eth_mac_mii.v",
"sha256": "0de7c247c1d13b0069d969f4b0bbbf6377c5db380feff9eb87c99a0bd715daf7"
} |
For eth_mac_mii, how well do the RTL and netlist signals line up, and what does the module's control/data-flow structure look like — specifically, how many signals were mapped, how many RTL signals had no netlist counterpart, and which major submodules and ports make up the CDFG? | The RTL-to-netlist mapping covered 36 of 38 RTL signals with an alignment score of 94.74, leaving only 'wire' and 'style' unmapped. The CDFG of eth_mac_mii has 32 nodes and 89 edges (avg_degree 2.78), built around two submodule instances — one eth_mac_1g and one mii_phy_if — plus 13 input ports and 17 output ports. | github_repos/corundum_corundum/fpga/lib/eth/rtl/eth_mac_mii.v | eth_mac_mii | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rx_clk": [
"rx_clk",
"mii_rx_clk"
],
"tx_error_underflow": [
"tx_error_underflow"
],
"rst": [
"rst",
"tx_rst",
"rx_rst"
],
"wire": [],
"cfg_ifg": [
"cfg_ifg"
],
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 6e8e5d217cb1 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For eth_mac_mii, how well do the RTL and netlist signals line up, and what does the module's control/data-flow structure look like — specifically, how many signals were mapped, how many RTL signals had no netlist counterpart, and which major submodules and ports make up the CDFG?
[cross_stage_mapper {}]
{
... | c843bb27d025 | 2eccdfe10a94 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/eth_mac_mii.v",
"sha256": "0de7c247c1d13b0069d969f4b0bbbf6377c5db380feff9eb87c99a0bd715daf7"
} |
For the oh_oa221 module, how does the code complexity compare with the structural content, and what does that suggest about how it should be handled in verification? | The oh_oa221 module is structurally simple, with cyclomatic complexity 1, nesting depth 0, 11 lines of code, and a single assign statement driving 25 operators, yet it contains no RTL ports or signals and instantiates an array. After netlist mapping there are 18 netlist wires but 0 mapped signals and an alignment score... | github_repos/aolofsson_oh/stdlib/rtl/oh_oa221.v | oh_oa221 | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 0,
"netlist_wires": 18,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 0
},
"error": null
}
[static_analyz... | multi_tool | cross_stage_mapper+static_analyzer | compositional | e6ac7d83b495 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the oh_oa221 module, how does the code complexity compare with the structural content, and what does that suggest about how it should be handled in verification?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mappin... | 1b784b1ed3e0 | 2f27706bbe50 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_oa221.v",
"sha256": "04202bb49a3890696f7d108958aacedfe869ed1b44d08ecc647e95f0e9683c3e"
} |
For the ct_idu_rf_pipe2_decd module, how does the structure shown in its CDFG compare with the source-level complexity metrics when judging how hard this decoder is to maintain and verify? | The CDFG for ct_idu_rf_pipe2_decd has 35 nodes and 664 edges, including 26 $eq nodes, 3 $pmux nodes, and an average degree of 18.97, which points to dense comparison/multiplexing logic. This aligns with the static analysis showing 3 always blocks, 9 assign statements, an operator_count of 1239, and a cyclomatic complex... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/idu/rtl/ct_idu_rf_pipe2_decd.v | ct_idu_rf_pipe2_decd | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:107$eq$8",
"type": "$eq",
"attributes": {
"src": "<tmp>:107.43-107.64"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+static_analyzer | compositional | 22396965f215 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ct_idu_rf_pipe2_decd module, how does the structure shown in its CDFG compare with the source-level complexity metrics when judging how hard this decoder is to maintain and verify?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id":... | 38c5212f21b7 | 2f3094fcc47a | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/idu/rtl/ct_idu_rf_pipe2_decd.v",
"sha256": "3816b89282e1050d4f99f8377a85357fdeaf4e504a979d10edf623982c7527da"
} |
For the udp module, given its area-focused optimization suggestions and the synthesized netlist results, is applying the area optimization recipes worthwhile, and what are the trade-offs in delay and power I should expect? | Yes: the area optimization for udp is estimated to improve area by -15.0 and power by -10.0, at the cost of a delay increase of 5.0. The current synthesized design at optimization level medium has an area of 3.0, delay of 69.52, and power of 0.003, so the delay penalty should be weighed against the already existing cri... | github_repos/alexforencich_verilog-ethernet/rtl/udp.v | udp | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top udp -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"type"... | multi_tool | optimization_advisor+synthesis_tool | compositional | f562342f9fa0 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the udp module, given its area-focused optimization suggestions and the synthesized netlist results, is applying the area optimization recipes worthwhile, and what are the trade-offs in delay and power I should expect?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_me... | 1a386c6d1052 | 2f077ff4fb94 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/udp.v",
"sha256": "750d3cf657463e28cab742eaf2309022840f3d00b45e3b668153b7fd63254cd7"
} |
For IBUF_IBUFDISABLE, given that area-focused optimization is recommended, how would the estimated area, delay, and power changes trade off, and does the synthesized result currently show any area or cells to optimize? | The area optimization is estimated to reduce area by -15.0 and power by -10.0, but at the cost of a 5.0 increase in delay, with aggressive sharing raising routing complexity. However, synthesis currently reports area 0, gate_count 0, and wire_count 0 for IBUF_IBUFDISABLE, so there is no logic to optimize yet. | github_repos/aolofsson_oh/xilibs/dv/IBUF_IBUFDISABLE.v | IBUF_IBUFDISABLE | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top IBUF_IBUFDISABLE -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{... | multi_tool | optimization_advisor+synthesis_tool | compositional | 5628698e1a14 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For IBUF_IBUFDISABLE, given that area-focused optimization is recommended, how would the estimated area, delay, and power changes trade off, and does the synthesized result currently show any area or cells to optimize?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric... | 7be771d23341 | 30083fddeb5d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "xilibs/dv/IBUF_IBUFDISABLE.v",
"sha256": "b84f6f5f0d2f7d4881dbcb8dc9539552e7978a1e82c3a36bf1111434212446fe"
} |
For the sync_signal module, the source code analysis gives its structure and complexity, and the medium-level delay/power-optimized synthesis gives its implementation results: how do the two views compare, e.g. does the number of flip-flops in the netlist match what you'd expect from the RTL, and how do complexity figu... | The RTL for sync_signal has 6 ports, 1 always block, 1 assign statement, and a cyclomatic complexity of 2 across 47 lines of code, and synthesis maps this to just 2 gates (2 $_DFF_P_ flip-flops) with area 8.0, delay 184.67, and power 0.002. The single clocked always block in the RTL corresponds exactly to the 2 flip-fl... | github_repos/corundum_corundum/fpga/lib/pcie/example/ZCU106/fpga/rtl/sync_signal.v | sync_signal | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "sync_signal",
"port_count": {
"inputs": 3,
"outputs": 3,
"inouts": 0,
"total": 6
},
"signal_count": {
"wires": 1,
"regs": 0,
"parameters": 2,
"total": 1
},
"always_blocks": 1,
"assign_state... | multi_tool | static_analyzer+synthesis_tool | compositional | f7c754f5ccc1 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the sync_signal module, the source code analysis gives its structure and complexity, and the medium-level delay/power-optimized synthesis gives its implementation results: how do the two views compare, e.g. does the number of flip-flops in the netlist match what you'd expect from the RTL, and how do compl... | ccb63ec230f3 | 2fcea52f0ec4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/ZCU106/fpga/rtl/sync_signal.v",
"sha256": "a89c005b14019c94f72fee6308e370044333742bec9494df1fbdd3096988f919"
} |
For xilinx_true_dual_port_read_first_2_clock_ram, how does the module's CDFG structure compare with its overall code complexity, considering the graph's node/edge counts and port counts versus the complexity metrics? | The CDFG for xilinx_true_dual_port_read_first_2_clock_ram has 31 nodes and 596 edges with an average degree of 19.23, including 2 $sdffe nodes, 12 $mux nodes, and 1 $mem_v2 node. The module has 31 ports total (15 inputs, 16 outputs), matching the node count, and its 101 lines of code carry a cyclomatic complexity of 26... | github_repos/pConst_basic_verilog/dual_port_single_port_ram_templates/xilinx_true_dual_port_read_first_2_clock_ram.v | xilinx_true_dual_port_read_first_2_clock_ram | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$auto$ff.cc:337:slice$3192",
"type": "$sdffe",
"attributes": {
"src": "<tmp>:86.7-90.35"
},
"parameters": {
"CLK_POLARITY": "00000000000000000000000000000001"... | multi_tool | graph_extractor+static_analyzer | compositional | 0a6a1543648e | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For xilinx_true_dual_port_read_first_2_clock_ram, how does the module's CDFG structure compare with its overall code complexity, considering the graph's node/edge counts and port counts versus the complexity metrics?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
... | 5bc914466f86 | 2f8f50061532 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "dual_port_single_port_ram_templates/xilinx_true_dual_port_read_first_2_clock_ram.v",
"sha256": "28c5a6fcd6caea99d3316ceca3f812e94ccca64cf4c8507f77b1d7ffe34354fc"
} |
For dma_ram_demux, how does the port structure seen in the CDFG compare with the static analysis, and what does that suggest about the module's internal complexity? | Both the CDFG and the static analysis agree that dma_ram_demux has 16 input ports and 14 output ports. The CDFG shows the module consists of two submodule instances, one dma_ram_demux_rd and one dma_ram_demux_wr, connected across 986 edges with 32 nodes and an average degree of 30.81. Despite this dense connectivity, t... | github_repos/corundum_corundum/fpga/lib/pcie/rtl/dma_ram_demux.v | dma_ram_demux | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "dma_ram_demux_rd_inst",
"type": "dma_ram_demux_rd",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:139.1-164.2"
},
"p... | multi_tool | graph_extractor+static_analyzer | compositional | 1ca81cd0f7d9 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For dma_ram_demux, how does the port structure seen in the CDFG compare with the static analysis, and what does that suggest about the module's internal complexity?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "dma_ram_demux_rd_inst"... | 2db242c61de1 | 303533c0dd82 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/rtl/dma_ram_demux.v",
"sha256": "32950ea2cdbfdfab35bbd6a741754150505fc8aaf84086144c6fd1c2c0923f7b"
} |
For the axi_crossbar module, how does the RTL-to-netlist signal mapping coverage relate to the structure shown in its CDFG — specifically, do the mapped and unmapped signals line up with the module's I/O port counts, and what does that suggest about the mapping quality? | The mapping only aligned 2 of 3 RTL signals for a 66.67 alignment score, leaving 'wire' unmapped, while the CDFG shows the axi_crossbar is dominated by I/O with 44 port_input and 44 port_output nodes plus one axi_crossbar_rd and one axi_crossbar_wr instance (90 nodes, 1948 edges, avg degree 21.64). This suggests the lo... | github_repos/corundum_corundum/fpga/lib/axi/rtl/axi_crossbar.v | axi_crossbar | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "CDFG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"rst": [
"m_axi_awburst",
"s_axi_arburst",
"rst",
"m_axi_arburst",
"s_axi_awburst"
],
"clk": [
"clk"
],
"wire": []
},
"alignment_score": 66.67,
"unmapped_elements": [
"wire"
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 8f8796d47817 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}] | Question: For the axi_crossbar module, how does the RTL-to-netlist signal mapping coverage relate to the structure shown in its CDFG — specifically, do the mapped and unmapped signals line up with the module's I/O port counts, and what does that suggest about the mapping quality?
[cross_stage_mapper {}]
{
"status": ... | d5a3a289ef62 | 30cd597c9d7b | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/axi/rtl/axi_crossbar.v",
"sha256": "f2e5177a8c8bbe4ed844554eece7abd207365a8a7a20796e0654e08362b51b3d"
} |
For the gmii_phy_if module, considering the area-focused optimization recommendations and the code complexity from a full static analysis, is applying aggressive resource sharing worthwhile, and what trade-offs and code characteristics should I keep in mind? | For gmii_phy_if, aggressive resource sharing is recommended by the area optimization, which estimates an area improvement of -15.0 percent but warns it may increase delay (estimated +5.0) and routing complexity. The static analysis shows the module is moderately complex with 120 lines of code, cyclomatic complexity of ... | github_repos/alexforencich_verilog-ethernet/rtl/gmii_phy_if.v | gmii_phy_if | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top gmii_phy_if -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 00a40556b4bf | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the gmii_phy_if module, considering the area-focused optimization recommendations and the code complexity from a full static analysis, is applying aggressive resource sharing worthwhile, and what trade-offs and code characteristics should I keep in mind?
[optimization_advisor {"target_metric": "area"}]
{... | 052787513163 | 30f04f473f48 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "rtl/gmii_phy_if.v",
"sha256": "9da180f3c5e7036c8cdc81a157315789c409cbf7c63f672ad3fec37ac966afc3"
} |
For the chain_delay_rand module, how does the control/dataflow structure of its CDFG compare with the results of the full static analysis, and is anything inconsistent between them? | The static analysis of chain_delay_rand reports 5 ports total (1 input, 4 outputs), 5 signals, and a fairly complex body with cyclomatic complexity 11, nesting depth 8, and 164 operators, while the CDFG contains 29 nodes and 104 edges with an average degree of 3.59. The CDFG node types agree with the static results on ... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/random/chain_delay_rand.v | chain_delay_rand | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:82$and$3",
"type": "$and",
"attributes": {
"src": "<tmp>:82.7-82.25"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WIDT... | multi_tool | graph_extractor+static_analyzer | compositional | 5927023ecde5 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the chain_delay_rand module, how does the control/dataflow structure of its CDFG compare with the results of the full static analysis, and is anything inconsistent between them?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp... | b8ea83f13315 | 30ee38bffe8f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/random/chain_delay_rand.v",
"sha256": "b6591a2103aa020c9f0da2e895ba320fc5936e221a761b87bde95b17348a73ff"
} |
For the module int_test, how does its structural complexity in the CDFG compare with its code-level complexity, and does the graph structure suggest any risk of unexpected connectivity given the lint results? | The int_test CDFG contains only 4 nodes (1 RAMB4_S16, 2 inputs, 1 output) and 44 edges with an average degree of 11.0, which is dense connectivity centered on the RAM instance. Meanwhile the code itself is simple—30 lines of code, cyclomatic complexity 1, nesting depth 0, and zero lint warnings—so the heavy graph conne... | github_repos/pConst_basic_verilog/pacoblaze-2.2/pacoblaze/int_test.v | int_test | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "ram_256_x_16",
"type": "RAMB4_S16",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:5.11-13.2"
},
"parameters": {}
... | multi_tool | graph_extractor+static_analyzer | compositional | 15d4356aadaa | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module int_test, how does its structural complexity in the CDFG compare with its code-level complexity, and does the graph structure suggest any risk of unexpected connectivity given the lint results?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes":... | e47b8f7d726d | 31422015a566 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "pacoblaze-2.2/pacoblaze/int_test.v",
"sha256": "9b47efdd19057b42d68b747a173420026a2344ca84f39b10190a1b22a956aa6b"
} |
For the module asic_dmux3, how do the structural complexity and the delay-optimized synthesis results compare in terms of gates and wiring, and is that consistent with its complexity metrics? | The module asic_dmux3 is structurally simple with a cyclomatic complexity of 1 and 19 operators across 13 lines of code, which matches the small synthesized netlist of 5 gates (1 AND and 4 NAND), an area of 5.0, and a critical path delay of 68.07. The netlist uses 11 wires (11 wire bits), consistent with the 7 total po... | github_repos/aolofsson_oh/asiclib/hdl/asic_dmux3.v | asic_dmux3 | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "asic_dmux3",
"port_count": {
"inputs": 6,
"outputs": 1,
"inouts": 0,
"total": 7
},
"signal_count": {
"wires": 0,
"regs": 0,
"parameters": 1,
"total": 0
},
"always_blocks": 0,
"assign_statem... | multi_tool | static_analyzer+synthesis_tool | compositional | 90d148a8db64 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module asic_dmux3, how do the structural complexity and the delay-optimized synthesis results compare in terms of gates and wiring, and is that consistent with its complexity metrics?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "asic_dmux3",
"port_count": {... | 6d6994bf5ab8 | 311237dde33f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_dmux3.v",
"sha256": "03c56cb0ed95677f7c0a6029b57cfffd7584179417d7c34dfea8dc3bc0135ff3"
} |
For the module ct_hpcp_adder_sel, given that the source has low cyclomatic complexity but a fairly large operator count, how does that translate into the synthesized area and gate count, and does the delay look reasonable for that size? | ct_hpcp_adder_sel has a cyclomatic complexity of just 3 with nesting depth 1, but it contains 78 operators across 236 lines of code, which elaborates into 401 gates (220 $_AND_, 172 $_NAND_, 3 $_NOR_, 6 $_ANDNOT_) occupying an area of 404.0. The resulting critical path delay of 276.49 with power of 0.401 suggests the d... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/pmu/rtl/ct_hpcp_adder_sel.v | ct_hpcp_adder_sel | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ct_hpcp_adder_sel",
"port_count": {
"inputs": 1,
"outputs": 0,
"inouts": 0,
"total": 1
},
"signal_count": {
"wires": 1,
"regs": 0,
"parameters": 0,
"total": 1
},
"always_blocks": 1,
"assign... | multi_tool | static_analyzer+synthesis_tool | compositional | 3646912ee27f | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module ct_hpcp_adder_sel, given that the source has low cyclomatic complexity but a fairly large operator count, how does that translate into the synthesized area and gate count, and does the delay look reasonable for that size?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"... | 76d601749a5e | 3161f170f52b | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/pmu/rtl/ct_hpcp_adder_sel.v",
"sha256": "b87fae62644e1e98ed00a286121d09e75c37211a9830e7bc707a61fcbb939c42"
} |
For the debounce_switch module, if I apply the recommended power-focused optimization flow, what results should I expect, and how does the projected power saving compare against the current synthesized design's power and area? | The synthesized debounce_switch design currently uses 127 cells with an area of 139.0, a delay of 219.91, and power of 0.127. The power optimization recipe (including clock gating and operand isolation) projects a power improvement of -25.0, with an estimated 5.0 change in both area and delay, at the cost of possible a... | github_repos/corundum_corundum/fpga/lib/pcie/example/DE10_Agilex/fpga/rtl/debounce_switch.v | debounce_switch | optimization_advisor+synthesis_tool | [
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top debounce_switch",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_... | multi_tool | optimization_advisor+synthesis_tool | compositional | 026f1f11cc03 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the debounce_switch module, if I apply the recommended power-focused optimization flow, what results should I expect, and how does the projected power saving compare against the current synthesized design's power and area?
[optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"targ... | 342fac4915fc | 3179a7699e7b | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/DE10_Agilex/fpga/rtl/debounce_switch.v",
"sha256": "02d6ba80136cb9be942347e33c43881f465acbfc4f41b6af3a32d41c86b4ef5a"
} |
For the module int_test, I'm considering applying the recommended area optimization flow — how would that affect delay, and given the module's structure (complexity and instantiations), is it a reasonable choice? | The area optimization for int_test is estimated to improve area by -15.0 and power by -10.0, but at the cost of a delay increase of 5.0. Since the module is structurally very simple (cyclomatic complexity 1, 0 always blocks, 30 lines of code) and consists mainly of a single RAMB4_S16 instantiation with 2 inputs and 1 o... | github_repos/pConst_basic_verilog/pacoblaze-2.2/pacoblaze/int_test.v | int_test | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top int_test -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
"... | multi_tool | optimization_advisor+static_analyzer | compositional | 1cdc626cff62 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module int_test, I'm considering applying the recommended area optimization flow — how would that affect delay, and given the module's structure (complexity and instantiations), is it a reasonable choice?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "ar... | fd1edc89c25b | 31422015a566 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "pacoblaze-2.2/pacoblaze/int_test.v",
"sha256": "9b47efdd19057b42d68b747a173420026a2344ca84f39b10190a1b22a956aa6b"
} |
For the ct_spsram_8192x32 module, how do the structural connectivity seen in its DFG and the current synthesis results compare, and what area-oriented optimization would you consider given those results? | The DFG for ct_spsram_8192x32 shows 8 nodes and 112 edges with 6 input ports and 1 output port, and synthesis at medium optimization maps it to a single ct_f_spsram_8192x32 cell with 1 gate, area 1.0, delay 50.0, and power 0.001. If area reduction is pursued, aggressive resource sharing is suggested with an estimated a... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_spsram_8192x32.v | ct_spsram_8192x32 | graph_extractor+optimization_advisor+synthesis_tool | [
{
"graph_type": "DFG"
},
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
{
"id": "x_ct_f_spsram_8192x32",
"type": "ct_f_spsram_8192x32",
"attributes": {
"module_not_derived": "00000000000000000000000000000001",
"src": "<tmp>:65.22-73.2"
},
...[12... | multi_tool | graph_extractor+optimization_advisor+synthesis_tool | compositional | 764894726a94 | [{"tool": "graph_extractor", "parameters": {"graph_type": "DFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ct_spsram_8192x32 module, how do the structural connectivity seen in its DFG and the current synthesis results compare, and what area-oriented optimization would you consider given those results?
[graph_extractor {"graph_type": "DFG"}]
{
"status": "success",
"graph_type": "DFG",
"nodes": [
... | 8e6fa2efe9d8 | 310f723aebce | 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_8192x32.v",
"sha256": "69afea0afe6258350d603c7c5f9a3445ebc1877c6c25d2ea2c62f148e0ab0c4d"
} |
For the axis_register module, considering its current code complexity from full static analysis, is the delay optimization worth pursuing, and what does each analysis suggest? Use the delay-targeted optimization results, the full static analysis summary, and the suggested recipes. | The delay optimization of axis_register is estimated to improve delay by -20.0 (i.e., reduce it) at the cost of 10.0 more area and 5.0 more power, using a recipe sequence of synth -top axis_register, opt -fast, abc -fast -liberty stdcells.lib, and opt_clean, plus suggestions for register retiming and logic duplication ... | github_repos/corundum_corundum/fpga/lib/pcie/example/ADM_PCIE_9V3/fpga_axi/rtl/axis_register.v | axis_register | 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_register",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"... | multi_tool | optimization_advisor+static_analyzer | compositional | 034c46dee208 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axis_register module, considering its current code complexity from full static analysis, is the delay optimization worth pursuing, and what does each analysis suggest? Use the delay-targeted optimization results, the full static analysis summary, and the suggested recipes.
[optimization_advisor {"tar... | 7968673fb0fb | 31b6d5ba0adf | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/pcie/example/ADM_PCIE_9V3/fpga_axi/rtl/axis_register.v",
"sha256": "ebb03f4f7184b4c45f47ee4448e627f8c40348d08f98e727eb9e7f86f4402fea"
} |
For the fpga module, if I apply the recommended power-focused optimization flow, how would the estimated improvements compare against the current synthesized results, and what trade-offs should I watch out for? | The current synthesis of fpga reports 15.5 area, 110.56 delay, and 0.016 power with 16 gates, while the power optimization is estimated to reduce power by -25.0 (with area and delay each changed by 5.0). However, the trade-offs warn that power optimization may add area overhead and that clock gating adds timing complex... | github_repos/corundum_corundum/fpga/lib/eth/example/RV901T/fpga/rtl/fpga.v | fpga | optimization_advisor+synthesis_tool | [
{
"target_metric": "power"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top fpga",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gating",
... | multi_tool | optimization_advisor+synthesis_tool | compositional | 394674cdc270 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fpga module, if I apply the recommended power-focused optimization flow, how would the estimated improvements compare against the current synthesized results, and what trade-offs should I watch out for?
[optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "pow... | ec287a8521f4 | 31d560688780 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/example/RV901T/fpga/rtl/fpga.v",
"sha256": "fc71a44c191c0dca25fdec1547ef0598e30ec54f458b71c51d218259a4f4b258"
} |
For the fpga module, given its RTL-to-netlist mapping quality and its post-synthesis results, summarize how well the implementation matches the RTL and what the cost looks like in terms of area, delay, and power. | The fpga module maps well: 27 of 29 RTL signals were mapped (with only "wire" and "frequency" unmapped) for an alignment score of 93.1, though the netlist has 30 wires versus 28 reported in synthesis. The synthesized design is small and cheap, with an area of 15.5, a gate count of 16, a critical-path delay of 110.56, a... | github_repos/corundum_corundum/fpga/lib/eth/example/RV901T/fpga/rtl/fpga.v | fpga | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"wire": [],
"clk_125mhz_pll_out": [
"clk_125mhz_pll_out"
],
"phy_1_rxd_delay": [
"phy_1_rxd_delay"
],
"phy_1_rx_ctl": [
"phy_1_rx_ctl_delay",
"phy_1_rx_ctl"
],
"frequency": [],
"rst... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 84fb29215bed | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fpga module, given its RTL-to-netlist mapping quality and its post-synthesis results, summarize how well the implementation matches the RTL and what the cost looks like in terms of area, delay, and power.
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"wire": [],
... | 32d22dfe6a40 | 31d560688780 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/example/RV901T/fpga/rtl/fpga.v",
"sha256": "fc71a44c191c0dca25fdec1547ef0598e30ec54f458b71c51d218259a4f4b258"
} |
For the asic_clkbuf module, does the RTL-to-netlist mapping fully account for all of the module's ports and signals, and does the structural complexity of the RTL match what the mapping found? | Yes — asic_clkbuf has 1 input and 1 output (2 ports total) per the structural analysis, and the RTL-to-netlist mapping shows 2 RTL signals and 2 netlist wires with 2 mapped signals, 0 unmapped signals, 0 netlist cells, and an alignment score of 100.0. This is consistent with the RTL's simplicity: 1 assign statement, 0 ... | github_repos/aolofsson_oh/asiclib/hdl/asic_clkbuf.v | asic_clkbuf | cross_stage_mapper+static_analyzer | [
{},
{
"analysis_type": "full"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"z": [
"z"
],
"a": [
"a"
]
},
"alignment_score": 100.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 2,
"netlist_wires": 2,
"netlist_cells": 0,
"mapped_signals": 2,
"... | multi_tool | cross_stage_mapper+static_analyzer | compositional | 04b8290f7d77 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the asic_clkbuf module, does the RTL-to-netlist mapping fully account for all of the module's ports and signals, and does the structural complexity of the RTL match what the mapping found?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"z": [
"z"
],
"a": ... | e1e51b89c89d | 322fb4579020 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_clkbuf.v",
"sha256": "d20ccf86e53578f3b654ff595732b8f3059ff6e78e1b4d510a64fc5d68f4451e"
} |
For the fpga module, the source is purely structural with no procedural blocks, so how does that show up in the synthesized netlist, and what are the resulting area, delay, and power figures? | The fpga module has 0 always blocks and 20 assign statements across 1040 lines of code, and the synthesized netlist reflects this purely combinational/structural style with just 33 cells including 2 BUFG and 1 IBUFG alongside the submodule instances. Synthesis at medium optimization gives an area of 34.0, a delay of 13... | github_repos/alexforencich_verilog-ethernet/example/HTG640/fpga/rtl/fpga.v | fpga | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "fpga",
"port_count": {
"inputs": 76,
"outputs": 60,
"inouts": 4,
"total": 140
},
"signal_count": {
"wires": 294,
"regs": 0,
"parameters": 0,
"total": 294
},
"always_blocks": 0,
"assign_stat... | multi_tool | static_analyzer+synthesis_tool | compositional | f5b60883d30a | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fpga module, the source is purely structural with no procedural blocks, so how does that show up in the synthesized netlist, and what are the resulting area, delay, and power figures?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "fpga",
"port_count": {
"... | bda33e90e994 | 32a2b5f92d2e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/HTG640/fpga/rtl/fpga.v",
"sha256": "7c95f5b3c52f4ce0be5c5e40817ec56fe74af785e696199175a68f6a52e50c14"
} |
For i2c_master, the area-focused optimization advice estimates trade-offs — how would those estimates compare against the current post-synthesis results, and what are the current figures and risks? | The current synthesis of i2c_master reports an area of 1088.0, delay of 384.43, and power of 0.887 with 887 gates, while the area optimization recommends recipes like 'share -aggressive' and 'abc -g gates -liberty stdcells.lib', estimating an area improvement of -15.0 and power of -10.0 but a delay penalty of 5.0. The ... | github_repos/alexforencich_verilog-ethernet/example/HTG9200/fpga_25g/rtl/i2c_master.v | i2c_master | optimization_advisor+synthesis_tool | [
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top i2c_master -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+synthesis_tool | compositional | e9620ba4cffd | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For i2c_master, the area-focused optimization advice estimates trade-offs — how would those estimates compare against the current post-synthesis results, and what are the current figures and risks?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recomme... | 5b42aac8eff2 | 327634abce30 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/HTG9200/fpga_25g/rtl/i2c_master.v",
"sha256": "ec735fe59297c73dc165ca127cfd487ca19fe051f3dbecebd98e13589f77cd86"
} |
For the fpga module, the RTL-to-netlist cross-check shows a very high alignment score — is the mapping clean enough to trust the post-synthesis figures, and what are the key numbers? | Yes — the mapping for fpga achieved an alignment score of 98.31 with 290 of 295 RTL signals mapped (only 5 unmapped, mainly the DDR3/user clock pins), so the synthesis results are reliable. At the medium optimization level, synthesis reports 33 gates (including 6 eth_gth_phy_quad instances and 2 BUFGs), a delay of 138.... | github_repos/alexforencich_verilog-ethernet/example/HTG640/fpga/rtl/fpga.v | fpga | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"uart_dsr_int": [
"uart_dsr_int"
],
"eth_r8_rxd": [
"eth_r8_rxd"
],
"eth_l7_rxd": [
"eth_l7_rxd"
],
"eth_r4_txc": [
"eth_r4_txc"
],
"gth_quad_F_rxn_3": [
"gth_quad_F_rxn_3"
... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | aa4c45da33d7 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the fpga module, the RTL-to-netlist cross-check shows a very high alignment score — is the mapping clean enough to trust the post-synthesis figures, and what are the key numbers?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"uart_dsr_int": [
"uart_dsr_int"
... | c695f57d3891 | 32a2b5f92d2e | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/HTG640/fpga/rtl/fpga.v",
"sha256": "7c95f5b3c52f4ce0be5c5e40817ec56fe74af785e696199175a68f6a52e50c14"
} |
For the oh_and4 module, how does the synthesized gate-level result compare to the RTL-to-netlist mapping statistics — specifically, do the cell, wire, and signal counts line up, and what are the area, delay, and power figures after synthesis? | Synthesis of oh_and4 produced 3 AND gates (area 3.0, delay 69.52, power 0.003) with 7 wires and 7 wire bits, while the RTL-to-netlist mapping reports 0 mapped RTL signals but 14 netlist wires and 0 netlist cells with an alignment score of 0.0, so the mapping's 14 netlist wires and 0 cells do not line up with the synthe... | github_repos/aolofsson_oh/stdlib/rtl/oh_and4.v | oh_and4 | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 0,
"netlist_wires": 14,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 0
},
"error": null
}
[synthesis_too... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | 8549d3a9a67b | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_and4 module, how does the synthesized gate-level result compare to the RTL-to-netlist mapping statistics — specifically, do the cell, wire, and signal counts line up, and what are the area, delay, and power figures after synthesis?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist... | a68159bb7d19 | 3359888ef8fc | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_and4.v",
"sha256": "222b5438b2d945d0484d1723fdacc480e0b931c10759466960037b75c4fe1dc5"
} |
For the module oh_and4, how does the structure shown by its CDFG compare with the code-level statistics, and is there anything in the lint results that would complicate a delay-focused optimization of this chain of AND gates? | The CDFG of oh_and4 contains 8 nodes and 9 edges, made up of 3 $and operations plus 4 input ports and 1 output port with an average degree of 1.12, which matches the code statistics of 1 assign statement, 24 operators, and 10 lines of code with cyclomatic complexity 1 and nesting depth 0. No lint warnings were reported... | github_repos/aolofsson_oh/stdlib/rtl/oh_and4.v | oh_and4 | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:17$and$1",
"type": "$and",
"attributes": {
"src": "<tmp>:17.16-17.19"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WID... | multi_tool | graph_extractor+static_analyzer | compositional | ae5bb67f09d2 | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module oh_and4, how does the structure shown by its CDFG compare with the code-level statistics, and is there anything in the lint results that would complicate a delay-focused optimization of this chain of AND gates?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "... | 6c2fa774e508 | 3359888ef8fc | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_and4.v",
"sha256": "222b5438b2d945d0484d1723fdacc480e0b931c10759466960037b75c4fe1dc5"
} |
For the ct_f_spsram_4096x32 module, the RTL-to-netlist mapping shows one unmapped signal, addr_holding, and the area-focused optimization flow predicts trade-offs; given the current synthesis results, how do these fit together, and is the area optimization worth pursuing? | In ct_f_spsram_4096x32, 12 of 13 RTL signals mapped (alignment score 92.31) with only addr_holding unmapped, and synthesis produced area 101.0, delay 233.66, power 0.057 with 57 gates and 4 fpga_ram blocks. The area recipes (e.g., share -aggressive, muxcover) are estimated to improve area by -15.0 and power by -10.0, b... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/fpga/rtl/ct_f_spsram_4096x32.v | ct_f_spsram_4096x32 | cross_stage_mapper+optimization_advisor+synthesis_tool | [
{},
{
"target_metric": "area"
},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"D": [
"D"
],
"addr_holding": [],
"ram3_wen": [
"ram3_wen"
],
"CEN": [
"CEN"
],
"ram0_wen": [
"ram0_wen"
],
"addr": [
"addr"
],
"WEN": [
"GWEN",
"WEN"
... | multi_tool | cross_stage_mapper+optimization_advisor+synthesis_tool | compositional | 02f3e508b17b | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ct_f_spsram_4096x32 module, the RTL-to-netlist mapping shows one unmapped signal, addr_holding, and the area-focused optimization flow predicts trade-offs; given the current synthesis results, how do these fit together, and is the area optimization worth pursuing?
[cross_stage_mapper {}]
{
"status"... | beeaf985618d | 33d5e2e13ec0 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/fpga/rtl/ct_f_spsram_4096x32.v",
"sha256": "89b1da8d8420dfe5593a4f55bc84887d41eff090a473ab642e39f6721f277d9b"
} |
For the test_axis_tap module, how do the code characteristics relate to the delay optimization advice, and what improvement and trade-offs should I expect? | test_axis_tap is a simple 114-line testbench-style module (cyclomatic complexity 2, nesting depth 1, 63 operators, 7 regs and 2 wires) with no always blocks or assignments, yet the delay optimization pass suggests pipelining arithmetic operations and logic duplication, estimating a delay improvement of -20.0 at the cos... | github_repos/corundum_corundum/fpga/lib/eth/lib/axis/tb/test_axis_tap.v | test_axis_tap | optimization_advisor+static_analyzer | [
{
"target_metric": "delay"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top test_axis_tap",
"opt -fast",
"abc -fast -liberty stdcells.lib",
"opt_clean"
],
"optimization_suggestions": [
{
"type": "pipeline_insertion",
"... | multi_tool | optimization_advisor+static_analyzer | compositional | 739e316358dd | [{"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the test_axis_tap module, how do the code characteristics relate to the delay optimization advice, and what improvement and trade-offs should I expect?
[optimization_advisor {"target_metric": "delay"}]
{
"status": "success",
"target_metric": "delay",
"recommended_recipes": [
"synth -top test_ax... | d732372e739b | 336e091264e8 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/lib/axis/tb/test_axis_tap.v",
"sha256": "0bc80288f20464db30145cfc1b709912d1bdb11a904624eca3cb598c5fd5520d"
} |
For the module asic_oa211, compare the structure of the original RTL with the synthesized netlist: how many lines of code and operators does the source use, and how many gates and what delay results after medium-level delay-oriented optimization? | The RTL for asic_oa211 is a small combinational design with 9 lines of code, 1 assign statement, and 16 operators. After synthesis at medium optimization, it maps to just 3 gates (2 AND and 1 OR), achieving a critical-path delay of 69.52 with 3.0 area and 0.003 power. | github_repos/aolofsson_oh/asiclib/hdl/asic_oa211.v | asic_oa211 | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "asic_oa211",
"port_count": {
"inputs": 4,
"outputs": 1,
"inouts": 0,
"total": 5
},
"signal_count": {
"wires": 0,
"regs": 0,
"parameters": 1,
"total": 0
},
"always_blocks": 0,
"assign_statem... | multi_tool | static_analyzer+synthesis_tool | compositional | a002f287ae2b | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the module asic_oa211, compare the structure of the original RTL with the synthesized netlist: how many lines of code and operators does the source use, and how many gates and what delay results after medium-level delay-oriented optimization?
[static_analyzer {"analysis_type": "full"}]
{
"status": "suc... | 1d618ba04373 | 345f596fa4a9 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "asiclib/hdl/asic_oa211.v",
"sha256": "15d363555bb8d9bc871e9ac04510b3eca6117b2f31300e8bd1f23be5479c88d1"
} |
For the XORCY module, how well do the RTL signals carry over to the gate-level representation, and how does that compare structurally to the AIG representation of the same logic? | The RTL-to-netlist mapping for XORCY is perfect: both RTL signals (CI and O) mapped with an alignment score of 100.0 and no unmapped elements, out of 2 RTL signals and 6 netlist wires. In the AIG representation, that same XOR logic expands into a larger graph of 10 nodes and 17 edges with an average degree of 1.7, comp... | github_repos/pConst_basic_verilog/pacoblaze-2.2/xilinx/unisims/XORCY.v | XORCY | cross_stage_mapper+graph_extractor | [
{},
{
"graph_type": "AIG"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"CI": [
"CI"
],
"O": [
"O"
]
},
"alignment_score": 100.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 2,
"netlist_wires": 6,
"netlist_cells": 0,
"mapped_signals": 2,
... | multi_tool | cross_stage_mapper+graph_extractor | compositional | 8bfe63d62fa6 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}] | Question: For the XORCY module, how well do the RTL signals carry over to the gate-level representation, and how does that compare structurally to the AIG representation of the same logic?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"CI": [
"CI"
],
"O": [
"O"
... | 9e420a909ef3 | 34d6750ee978 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "pacoblaze-2.2/xilinx/unisims/XORCY.v",
"sha256": "6b9d23c770c5303173e302332857b33ae0c880368d08bc4d0067a0dcbe57343e"
} |
For the ptp_ts_extract module, how does its structural complexity compare with the hardware cost it actually needs — for example, is the register and combinational logic in the RTL consistent with what synthesis produces in terms of cells, area and delay? | The RTL of ptp_ts_extract has 1 always block, 2 assign statements and 40 operators across 58 lines of code, yet it is structurally quite simple with just 1 reg and no lint warnings. Synthesis confirms this simplicity, mapping it to only 3 gates (one $_ANDNOT_, one $_NOT_, one $_SDFFE_PP0P_ flip-flop) with an area of 3.... | github_repos/corundum_corundum/fpga/lib/eth/rtl/ptp_ts_extract.v | ptp_ts_extract | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "ptp_ts_extract",
"port_count": {
"inputs": 5,
"outputs": 2,
"inouts": 0,
"total": 7
},
"signal_count": {
"wires": 5,
"regs": 1,
"parameters": 3,
"total": 6
},
"always_blocks": 1,
"assign_st... | multi_tool | static_analyzer+synthesis_tool | compositional | fa2384b96c6d | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the ptp_ts_extract module, how does its structural complexity compare with the hardware cost it actually needs — for example, is the register and combinational logic in the RTL consistent with what synthesis produces in terms of cells, area and delay?
[static_analyzer {"analysis_type": "full"}]
{
"stat... | ab70a885516c | 34f8551f1208 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/corundum/corundum",
"commit": "1ca0151b97af85aa5dd306d74b6bcec65904d2ce",
"path": "fpga/lib/eth/rtl/ptp_ts_extract.v",
"sha256": "6373a8982dae454eb6b3275a007901ac6d658c10c1976848f751348008c8abaa"
} |
For the module ct_lsu_vb_sdb_data_entry, how does its CDFG structure relate to the RTL-to-netlist mapping results, and if I follow the delay optimization advice, what trade-offs should I expect? | The CDFG for ct_lsu_vb_sdb_data_entry has 128 nodes and 6905 edges with an average degree of 53.95, while the mapping shows 78 of 79 RTL signals mapped to netlist wires (98.73 alignment) with only sdb_bypass_readonce unmapped. The delay optimization is estimated to improve delay by -20.0 at the cost of 10.0 more area a... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/lsu/rtl/ct_lsu_vb_sdb_data_entry.v | ct_lsu_vb_sdb_data_entry | cross_stage_mapper+graph_extractor+optimization_advisor | [
{},
{
"graph_type": "CDFG"
},
{
"target_metric": "delay"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"vb_data_entry_dirty_x": [
"vb_data_entry_dirty_x"
],
"sdb_entry_data_v": [
"sdb_entry_data_v"
],
"vb_data_normal_pop": [
"vb_data_normal_pop"
],
"vb_data_entry_normal_pop_x": [
"
...[5903 ... | multi_tool | cross_stage_mapper+graph_extractor+optimization_advisor | compositional | 52d9b39b69d2 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For the module ct_lsu_vb_sdb_data_entry, how does its CDFG structure relate to the RTL-to-netlist mapping results, and if I follow the delay optimization advice, what trade-offs should I expect?
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"vb_data_entry_dirty_x": [
... | 3f8ef976453e | 3508dfe0b1b6 | 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_lsu_vb_sdb_data_entry.v",
"sha256": "8b8be3a663c23ff022bdcb9b2f609a9309847fdcd847f4a1d67200b7f0f311da"
} |
For csky_apb_1tox_matrix, how do the synthesized area and power figures compare with the area-optimization guidance, and what code characteristics might make that optimization worthwhile? | The medium-effort synthesis of csky_apb_1tox_matrix gives an area of 1091.0 and power of 1.051 with 1051 gates, while the area-focused optimization advice (including mux sharing and aggressive resource sharing) estimates an area improvement of -15.0 and power improvement of -10.0 at the cost of a delay increase of 5.0.... | github_repos/XUANTIE-RV_openc910/C910_RTL_FACTORY/gen_rtl/plic/rtl/csky_apb_1tox_matrix.v | csky_apb_1tox_matrix | 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 csky_apb_1tox_matrix -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 | 06cac8384009 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For csky_apb_1tox_matrix, how do the synthesized area and power figures compare with the area-optimization guidance, and what code characteristics might make that optimization worthwhile?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recip... | ad131edb213b | 356589f9e67f | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/XUANTIE-RV/openc910",
"commit": "b91c90914c19f114d35c8f6b73408eb241ed847c",
"path": "C910_RTL_FACTORY/gen_rtl/plic/rtl/csky_apb_1tox_matrix.v",
"sha256": "6dbf8b4f07214f179e4e1d92d5d6239e6a6a582378de6f9a515254fd92145229"
} |
For the module oh_dffrqn, how does its control/dataflow structure (shown in its CDFG) compare with its measured code complexity, and does the structural view suggest the sequential logic is simple despite the cyclomatic complexity of 3? | The CDFG for oh_dffrqn is very small, with 6 nodes and 6 edges covering one $not, one $adff, 3 input ports and 1 output port, i.e., a single resettable flip-flop with an inverted data path. The source-level analysis of 13 lines of code, cyclomatic complexity 3, nesting depth 0 and 27 operators with no lint warnings sho... | github_repos/aolofsson_oh/stdlib/rtl/oh_dffrqn.v | oh_dffrqn | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:20$not$3",
"type": "$not",
"attributes": {
"src": "<tmp>:20.14-20.16"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WID... | multi_tool | graph_extractor+static_analyzer | compositional | 5960a582c08f | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the module oh_dffrqn, how does its control/dataflow structure (shown in its CDFG) compare with its measured code complexity, and does the structural view suggest the sequential logic is simple despite the cyclomatic complexity of 3?
[graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"gra... | 4e227b897650 | 35229439ce1f | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_dffrqn.v",
"sha256": "783b829af476bad8ed4949cff108d5fe7aaa8675137e5114ebae959e1c6eaccc"
} |
For the hex_display module, is the power optimization suggested worth applying given the code characteristics — please summarize the estimated power saving, the main trade-offs, and the lint risk that could interact with the clock-gating suggestion? | The power optimization for hex_display is estimated to improve power by -25.0 percent (with 5.0 area and 5.0 delay changes), at the cost of possible area overhead and added timing complexity from clock gating. However, the static analysis flags a combinational block that may infer a latch due to a missing else, which s... | github_repos/alexforencich_verilog-ethernet/example/DE2-115/fpga/rtl/hex_display.v | hex_display | optimization_advisor+static_analyzer | [
{
"target_metric": "power"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "power"}]
{
"status": "success",
"target_metric": "power",
"recommended_recipes": [
"synth -top hex_display",
"opt; share; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean; clockgate"
],
"optimization_suggestions": [
{
"type": "clock_gati... | multi_tool | optimization_advisor+static_analyzer | compositional | 726a327cc72c | [{"tool": "optimization_advisor", "parameters": {"target_metric": "power"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the hex_display module, is the power optimization suggested worth applying given the code characteristics — please summarize the estimated power saving, the main trade-offs, and the lint risk that could interact with the clock-gating suggestion?
[optimization_advisor {"target_metric": "power"}]
{
"stat... | 050578e967ea | 35bd3ec8a770 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/alexforencich/verilog-ethernet",
"commit": "77320a9471d19c7dd383914bc049e02d9f4f1ffb",
"path": "example/DE2-115/fpga/rtl/hex_display.v",
"sha256": "ea22655727a677b17d5fa73929ef535aca235915a18d69e9091dd31b98efec1c"
} |
For the ecc_16bit_tb module, is applying aggressive resource sharing to reduce area worthwhile given its code complexity, and what should I watch out for? | Yes, aggressive sharing of arithmetic operators is recommended for ecc_16bit_tb with an estimated area improvement of -15.0 and power improvement of -10.0, though delay increases by 5.0 and routing complexity grows. This is worth considering despite the module's high complexity—649 operators, cyclomatic complexity of 4... | github_repos/pConst_basic_verilog/Advanced Synthesis Cookbook/ecc/ecc_16bit_tb.v | ecc_16bit_tb | optimization_advisor+static_analyzer | [
{
"target_metric": "area"
},
{
"analysis_type": "full"
}
] | [optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ecc_16bit_tb -flatten",
"opt -full; share -aggressive; opt",
"abc -g gates -liberty stdcells.lib",
"opt_clean -purge"
],
"optimization_suggestions": [
{
... | multi_tool | optimization_advisor+static_analyzer | compositional | 3d94dfa209f6 | [{"tool": "optimization_advisor", "parameters": {"target_metric": "area"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the ecc_16bit_tb module, is applying aggressive resource sharing to reduce area worthwhile given its code complexity, and what should I watch out for?
[optimization_advisor {"target_metric": "area"}]
{
"status": "success",
"target_metric": "area",
"recommended_recipes": [
"synth -top ecc_16bit_... | 2e246b7afbbd | 356d4eb9b918 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/pConst/basic_verilog",
"commit": "2654273b2c4e556a98e806f3a19b52c9b3c74614",
"path": "Advanced Synthesis Cookbook/ecc/ecc_16bit_tb.v",
"sha256": "11843ebd4711ddccbd069206813a70da532fb641d25a1bafa6d00a80ac54fae5"
} |
For the oh_mxi4 module, the synthesis results with medium delay and power optimization report a certain gate count and cell mix, but the RTL-to-netlist mapping shows a different picture — can you reconcile the two and summarize what the netlist actually contains? | Synthesis of oh_mxi4 produced an area of 6.5, a delay of 82.74, a power of 0.006, and 6 cells (2 $_AND_, 2 $_NAND_, 1 $_ORNOT_, 1 $_OR_) with 12 wires, yet the cross-stage mapping shows 0 mapped RTL signals and 0 netlist cells against 30 netlist wires, meaning no RTL-to-netlist correspondence was established even thoug... | github_repos/aolofsson_oh/stdlib/rtl/oh_mxi4.v | oh_mxi4 | cross_stage_mapper+synthesis_tool | [
{},
{
"optimization_level": "medium"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {},
"alignment_score": 0.0,
"unmapped_elements": [],
"mapping_statistics": {
"rtl_signals": 0,
"netlist_wires": 30,
"netlist_cells": 0,
"mapped_signals": 0,
"unmapped_signals": 0
},
"error": null
}
[synthesis_too... | multi_tool | cross_stage_mapper+synthesis_tool | compositional | c924b12523b0 | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the oh_mxi4 module, the synthesis results with medium delay and power optimization report a certain gate count and cell mix, but the RTL-to-netlist mapping shows a different picture — can you reconcile the two and summarize what the netlist actually contains?
[cross_stage_mapper {}]
{
"status": "succes... | 120c58e01483 | 3628bba1e2be | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/aolofsson/oh",
"commit": "7edfcb5f0506fb854449fbe09598a7ec88bb2067",
"path": "stdlib/rtl/oh_mxi4.v",
"sha256": "0909f6632a9934b1fc112e28ccf380e78ad42bfce132fa724c9273fdfd0ee656"
} |
For the sync_event module, how does its structural complexity from the source-level analysis compare with the area and delay results after medium-level delay/power optimization — is it a complex module despite the small synthesized circuit? | Although sync_event has 67 lines of code, a cyclomatic complexity of 11, a nesting depth of 14, and 4 always blocks, the optimized circuit is quite small with 12 gates, an area of 27.0, and a delay of 159.81. Its 2 sync_bits instantiations and 6 signals explain how the modest source maps to a compact netlist consuming ... | github_repos/analogdevicesinc_hdl/library/util_cdc/sync_event.v | sync_event | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "sync_event",
"port_count": {
"inputs": 2,
"outputs": 1,
"inouts": 0,
"total": 3
},
"signal_count": {
"wires": 4,
"regs": 2,
"parameters": 2,
"total": 6
},
"always_blocks": 4,
"assign_statem... | multi_tool | static_analyzer+synthesis_tool | compositional | 6767ca34f0a0 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the sync_event module, how does its structural complexity from the source-level analysis compare with the area and delay results after medium-level delay/power optimization — is it a complex module despite the small synthesized circuit?
[static_analyzer {"analysis_type": "full"}]
{
"status": "success",... | 427f89ac0e1c | 366bdaf53b2d | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/util_cdc/sync_event.v",
"sha256": "da21cc018ba5b8caae72a36490ec06813d131d3f725d59a08b6a4fd2ae0c99dd"
} |
For the axi_ad9265 module, how does the structure seen in its control/data-flow graph (CDFG) compare with the source-level complexity metrics — specifically, does the high connectivity in the CDFG reflect a complex codebase, and how do the submodule instances in the graph relate to the instantiation list? | Despite the CDFG having 51 nodes and 1292 edges with an average degree of 25.33, the source code is fairly simple: 254 lines of code, cyclomatic complexity of 3, and nesting depth of 3. The high edge count is driven by connectivity rather than logic, since the graph contains only 6 $or cells, 6 $adff cells, and 21 inpu... | github_repos/analogdevicesinc_hdl/library/axi_ad9265/axi_ad9265.v | axi_ad9265 | graph_extractor+static_analyzer | [
{
"graph_type": "CDFG"
},
{
"analysis_type": "full"
}
] | [graph_extractor {"graph_type": "CDFG"}]
{
"status": "success",
"graph_type": "CDFG",
"nodes": [
{
"id": "$<tmp>:151$or$3",
"type": "$or",
"attributes": {
"src": "<tmp>:151.19-151.48"
},
"parameters": {
"A_SIGNED": "00000000000000000000000000000000",
"A_WI... | multi_tool | graph_extractor+static_analyzer | compositional | ecb142a951dc | [{"tool": "graph_extractor", "parameters": {"graph_type": "CDFG"}}, {"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}] | Question: For the axi_ad9265 module, how does the structure seen in its control/data-flow graph (CDFG) compare with the source-level complexity metrics — specifically, does the high connectivity in the CDFG reflect a complex codebase, and how do the submodule instances in the graph relate to the instantiation list?
[g... | 269a42c0865e | 3667e5fd08a4 | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9265/axi_ad9265.v",
"sha256": "cb8c6d666b9fc34cd5b63f4408d2762dd740fb04fa38499e98e3223da794c1f0"
} |
For axi_ad9265, considering the AIG structure, the RTL-to-netlist signal mapping quality, and the delay optimization advice, how well is the design aligned and what would pipelining cost? Summarize the key figures from each analysis. | The AIG of axi_ad9265 has 348 nodes and 1762 edges with an average degree of 5.06, including 68 AND nodes, 204 NOT nodes, and 37 DFF nodes. Cross-stage mapping aligned 47 of 53 RTL signals for a score of 88.68, leaving 6 unmapped signals such as up_wack and up_rdata. The delay-focused optimization suggests register ret... | github_repos/analogdevicesinc_hdl/library/axi_ad9265/axi_ad9265.v | axi_ad9265 | cross_stage_mapper+graph_extractor+optimization_advisor | [
{},
{
"graph_type": "AIG"
},
{
"target_metric": "delay"
}
] | [cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping": {
"up_rstn": [
"up_rstn"
],
"up_wreq_s": [
"up_wreq_s"
],
"s_axi_arvalid": [
"s_axi_arvalid"
],
"up_wack": [],
"up_dwdata_s": [
"up_dwdata_s"
],
"up_status_pn_err_s": [
...[2041 ... | multi_tool | cross_stage_mapper+graph_extractor+optimization_advisor | compositional | 6f7215d1f14b | [{"tool": "cross_stage_mapper", "parameters": {}}, {"tool": "graph_extractor", "parameters": {"graph_type": "AIG"}}, {"tool": "optimization_advisor", "parameters": {"target_metric": "delay"}}] | Question: For axi_ad9265, considering the AIG structure, the RTL-to-netlist signal mapping quality, and the delay optimization advice, how well is the design aligned and what would pipelining cost? Summarize the key figures from each analysis.
[cross_stage_mapper {}]
{
"status": "success",
"rtl_to_netlist_mapping"... | e4579e9854d7 | 3667e5fd08a4 | train | glm-5.3 | 3 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9265/axi_ad9265.v",
"sha256": "cb8c6d666b9fc34cd5b63f4408d2762dd740fb04fa38499e98e3223da794c1f0"
} |
For the axi_ad9671 module, how do the structural characteristics of the source code compare with the results after medium-level delay and power optimization — specifically, given its complexity metrics and instantiated channel blocks, what did synthesis achieve in area, delay, power, and gate count? | The axi_ad9671 source is 249 lines of code with a cyclomatic complexity of 4, nesting depth of 4, and 494 operators, and it instantiates 8 axi_ad9671_channel blocks plus one up_axi, one axi_ad9671_if, and one up_adc_common. After medium-level delay and power optimization, synthesis produced an area of 358.0, a critical... | github_repos/analogdevicesinc_hdl/library/axi_ad9671/axi_ad9671.v | axi_ad9671 | static_analyzer+synthesis_tool | [
{
"analysis_type": "full"
},
{
"optimization_level": "medium"
}
] | [static_analyzer {"analysis_type": "full"}]
{
"status": "success",
"module_name": "axi_ad9671",
"port_count": {
"inputs": 11,
"outputs": 9,
"inouts": 0,
"total": 20
},
"signal_count": {
"wires": 11,
"regs": 5,
"parameters": 6,
"total": 16
},
"always_blocks": 1,
"assign_st... | multi_tool | static_analyzer+synthesis_tool | compositional | 85caac62d163 | [{"tool": "static_analyzer", "parameters": {"analysis_type": "full"}}, {"tool": "synthesis_tool", "parameters": {"optimization_level": "medium"}}] | Question: For the axi_ad9671 module, how do the structural characteristics of the source code compare with the results after medium-level delay and power optimization — specifically, given its complexity metrics and instantiated channel blocks, what did synthesis achieve in area, delay, power, and gate count?
[static_... | 1459e138faf0 | 3686dbb8f6da | train | glm-5.3 | 2 | 3,300 | {
"repository": "https://github.com/analogdevicesinc/hdl",
"commit": "c9a501d87a420d2e28aa9d931557bdb4122f3c4f",
"path": "library/axi_ad9671/axi_ad9671.v",
"sha256": "754cb470f9be16835c7b753eb88dc6c37face9ffad3a7acfe7b719b7d1c74d75"
} |
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