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submission 772214

Kernel-Zhang · python · License unknown

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Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 44 lines, June 9 Researcher Reciprocity License v1.0.

custom_0001.py
curl "https://kernelindex.com/api/v1/implementations/kernelbot-vectoradd-v2-772214?include=source"
interfacepython
Compatibility
measured onNVIDIA B200
declared hardwareNVIDIA B200
architecturessm_100
dtypesfp16

Benchmark evidence

1 measurement across 1 GPU, fastest first.

Operation / workload
Hardware
Latency
Rank
Observed
FP16 vector additionsuite of 5 cases
NVIDIA B200
402.8µs
#61 of 66
2026-04-16

Reported · How evidence levels are derived →

Source and license

sourceavailable
revision digestsha256:4a3cc1b3221e54e8826528b3f549a50ea9631647bfd9fe7bc95a9accadd3d62f
license declaredunknown
license concludedunknown
authorsKernel-Zhang
imported2026-08-15

Kernel source

custom_0001.py44 lines
from utils import make_match_reference, DeterministicContext
import torch
from task import input_t, output_t

def custom_kernel(data: input_t) -> output_t:
    A, B, output = data
    output[...] = A + B
    return output

def ref_kernel(data: input_t) -> output_t:
    """
    Reference implementation of vector addition using PyTorch.
    Args:
        data: Tuple of tensors [A, B] to be added.
    Returns:
        Tensor containing element-wise sums.
    """
    with DeterministicContext():
        A, B, output = data
        output[...] = A + B
        return output


def generate_input(size: int, seed: int) -> input_t:
    """
    Generates random input tensors of specified shapes.
    Returns:
        Tuple of tensors [A, B] to be added.
    """
    gen = torch.Generator(device="cuda")
    gen.manual_seed(seed)
    A = torch.randn(
        size, size, device="cuda", dtype=torch.float16, generator=gen
    ).contiguous()
    B = torch.randn(
        size, size, device="cuda", dtype=torch.float16, generator=gen
    ).contiguous()
    C = torch.empty(size, size, device="cuda", dtype=torch.float16).contiguous()
    return A, B, C


check_implementation = make_match_reference(ref_kernel)

scrolls · 44 lines total

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 772213.

Best evidence level for this revision: reported

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