| { |
| "recorded_date": "2026-05-18", |
| "platform": "RTX 3070 Ti Laptop (GA104, sm_86, Ampere)", |
| "note": "Local production-library reference baselines measured on this exact machine. Only locally available reference stacks are recorded here; unsupported kernels are marked unavailable instead of estimated.", |
| "default_valid_when": { |
| "require_no_throttle": true, |
| "allow_throttle": ["GpuIdle"], |
| "comment": "Same fair-run policy as data/baselines.json." |
| }, |
| "schema": { |
| "exe": "(optional) path to reference bench executable", |
| "library": "(optional) local reference stack used by this bench, e.g. cuBLAS", |
| "match": "(optional) substring of the bench-output line that holds this reference value", |
| "project_kernel": "(required for comparisons) path to the project-kernel baseline entry in data/baselines.json", |
| "project_config": "(required for comparisons) config key in data/baselines.json to compare against", |
| "label": "(optional) human-readable row label for compare_reference.R output" |
| ,"peak": "(optional) hardware peak for this workload's precision class, in the same unit as the stored metric" |
| }, |
| "unsupported": [ |
| { |
| "label": "Flash Attention seq=1024 b=8 h=8 d=64", |
| "library": "cuDNN SDPA", |
| "reason": "Installed cuDNN headers on this machine do not expose the graph-based SDPA frontend used for a direct local attention reference, so this row remains unmeasured locally." |
| }, |
| { |
| "label": "GroupNorm SD 320ch", |
| "library": "cuDNN", |
| "reason": "No direct local cuDNN GroupNorm harness is implemented yet, so this row remains unmeasured locally." |
| } |
| ], |
| "kernels": { |
| "kernels/reference/cublas_hgemm/bench.cu": { |
| "exe": "kernels/reference/cublas_hgemm/bench", |
| "library": "cuBLAS", |
| "2048_2048_2048": { |
| "ms": 0.600, |
| "gflops": 28631, |
| "match": "cublas_hgemm", |
| "peak": 174000, |
| "project_kernel": "kernels/gemm/hgemm/hgemm_16warp.cu", |
| "project_config": "2048_2048_2048", |
| "label": "HGEMM 16-warp 2048^3" |
| }, |
| "4096_4096_4096": { |
| "ms": 4.626, |
| "gflops": 29708, |
| "match": "cublas_hgemm", |
| "peak": 174000, |
| "project_kernel": "kernels/gemm/hgemm/hgemm_16warp.cu", |
| "project_config": "4096_4096_4096", |
| "label": "HGEMM 16-warp 4096^3" |
| } |
| }, |
| "kernels/reference/cublas_igemm/bench.cu": { |
| "exe": "kernels/reference/cublas_igemm/bench", |
| "library": "cuBLAS", |
| "4096_4096_4096": { |
| "ms": 4.668, |
| "tops": 29.44, |
| "match": "cublas_igemm", |
| "peak": 348, |
| "project_kernel": "kernels/gemm/igemm/igemm_pipelined_cpasync.cu", |
| "project_config": "4096_4096_4096", |
| "label": "IGEMM pipelined cp.async 4096^3" |
| } |
| }, |
| "kernels/reference/cusparselt_igemm_sparse/bench.cu": { |
| "exe": "kernels/reference/cusparselt_igemm_sparse/bench", |
| "library": "cuSPARSELt", |
| "2048_2048_2048": { |
| "ms": 0.138, |
| "tops": 124.28, |
| "match": "cusparselt_igemm_sparse", |
| "peak": 348, |
| "project_kernel": "kernels/gemm/igemm/igemm_sparse_tiled.cu", |
| "project_config": "2048_2048_2048", |
| "label": "Sparse IGEMM tiled 2048^3" |
| }, |
| "4096_4096_4096": { |
| "ms": 0.808, |
| "tops": 170.11, |
| "match": "cusparselt_igemm_sparse", |
| "peak": 348, |
| "project_kernel": "kernels/gemm/igemm/igemm_sparse_tiled.cu", |
| "project_config": "4096_4096_4096", |
| "label": "Sparse IGEMM tiled 4096^3" |
| } |
| }, |
| "kernels/reference/cudnn_conv2d/bench.cu": { |
| "exe": "kernels/reference/cudnn_conv2d/bench", |
| "library": "cuDNN", |
| "1_64_64_320_320": { |
| "ms": 0.446, |
| "gflops": 16910, |
| "match": "cudnn_conv2d", |
| "tolerance": 0.20, |
| "peak": 174000, |
| "project_kernel": "kernels/convolution/conv2d/conv2d_implicit_gemm.cu", |
| "project_config": "1_64_64_320_320", |
| "label": "Conv2d implicit GEMM 1x64x64x320x320", |
| "note": "Median of repeated local cuDNN runs clusters around ~16.9 TFLOPS, but first invocation from an idle laptop state can dip into the mid-14 TFLOPS range; use a wider tolerance to avoid false regressions." |
| } |
| } |
| } |
| } |
|
|
