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submission 554193

idanbeck · python · License unknown

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Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 18 lines, June 9 Researcher Reciprocity License v1.0.

submission.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-conv2d-v2-554193?include=source"
interfacepython
Compatibility
measured onNVIDIA A100
declared hardwareNVIDIA A100
architecturessm_80
dtypesfp32

Benchmark evidence

1 measurement across 1 GPU, fastest first.

Operation / workload
Hardware
Latency
Rank
Observed
2D convolutionsuite of 5 cases
NVIDIA A100
2.57s
#37 of 40
2026-03-14

Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:2deebff94e6e131f4170dd5ef1f9fd9c70f6856a8078f530c8c4be07a76c3978
license declaredunknown
license concludedunknown
authorsidanbeck
imported2026-08-15

Kernel source

submission.py18 lines
#!POPCORN leaderboard conv2d_v2
#!POPCORN gpu A100
from task import input_t, output_t
import torch
import torch.nn.functional as F

@torch.inference_mode()
def custom_kernel(data: input_t) -> output_t:
    input_tensor, kernel, output = data
    torch.use_deterministic_algorithms(True)
    torch.set_float32_matmul_precision("highest")
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.deterministic = True
    torch.backends.cuda.matmul.allow_tf32 = False
    torch.backends.cudnn.allow_tf32 = False
    output[...] = F.conv2d(input_tensor, kernel, stride=1, padding=0)
    return output

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

Best evidence level for this revision: reported

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