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submission 554068

idanbeck · python · License unknown
Kernel source · 14 lines ↓

Use it

Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 14 lines, June 9 Researcher Reciprocity License v1.0.

submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-matmul-v2-554068?include=source"
interfacepython
Compatibility
measured onNVIDIA A100
declared hardwareNVIDIA A100
architecturessm_80
dtypesfp16

Benchmark evidence

1 measurement across 1 GPU, fastest first.

Operation / workload
Hardware
Latency
Rank
Observed
FP16 matmulsuite of 8 cases
NVIDIA A100
676.5µs
#10 of 27
2026-03-14
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Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:1ec30cae787bc1661cf3fd78e154ee7d86de8630a317f6474a4d2791055dfddc
license declaredunknown
license concludedunknown
authorsidanbeck
imported2026-08-15

Kernel source

submission.py14 lines
#!POPCORN leaderboard matmul_v2
#!POPCORN gpu A100
import os
os.environ.setdefault("CUBLAS_WORKSPACE_CONFIG", ":4096:8")
from task import input_t, output_t
import torch

@torch.inference_mode()
def custom_kernel(data: input_t) -> output_t:
    torch.use_deterministic_algorithms(True)
    a, b, c = data
    c[...] = torch.mm(a, b)
    return c

Source code from GPU Mode and the KernelBot dataset · June 9 Researcher Reciprocity License v1.0

Changes from previous submission

Against this author's previous submission submission 554041.

  ⋯ 3 unchanged lines
  os.environ.setdefault("CUBLAS_WORKSPACE_CONFIG", ":4096:8")
  from task import input_t, output_t
  import torch
- _F = None
   
- def _build():
-     def f(a, b, c):
-         c[...] = torch.mm(a, b)
-         return c
-     try:
-         return torch.compile(f, fullgraph=False, mode="max-autotune-no-cudagraphs")
-     except Exception:
-         return f
-  
  @torch.inference_mode()
  def custom_kernel(data: input_t) -> output_t:
-     global _F
      torch.use_deterministic_algorithms(True)
-     if _F is None:
-         _F = _build()
      a, b, c = data
-     return _F(a, b, c)
+     c[...] = torch.mm(a, b)
+     return c
scrolls · 25 diff lines total

Best evidence level for this revision: reported

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