Skip to content
KernelIndex
Search⌘K

submission 545146

rajesh0042 · python · License unknown

Use it

Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 19 lines, June 9 Researcher Reciprocity License v1.0.

conv2d_v2.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-conv2d-v2-545146?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
18.8ms
#9 of 40
2026-03-13

Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:acd44b96d2ea450fbcd09fb92530cb6914b83630014ada6c11cb39a0a0889dda
license declaredunknown
license concludedunknown
authorsrajesh0042
imported2026-08-15

Kernel source

conv2d_v2.py19 lines
import os
os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8"

import torch
import torch.nn.functional as F
from task import input_t, output_t

# Deterministic for correctness, but with benchmark to find fastest algorithm
torch.backends.cudnn.allow_tf32 = False
torch.backends.cuda.matmul.allow_tf32 = False
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = True  # Find fastest deterministic algo

def custom_kernel(data: input_t) -> output_t:
    input_tensor, kernel, output = data
    result = F.conv2d(input_tensor, kernel, stride=1, padding=0)
    output[...] = result
    return output

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 545145.

Best evidence level for this revision: reported

JSON