submission 545222 · KernelIndex

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Vendorable · source mirrored · license unknownView source →

No package. Vendor the mirrored source: 29 lines, June 9 Researcher Reciprocity License v1.0.

vectoradd_v3.py

curl "https://kernelindex.com/api/v1/implementations/kernelbot-vectoradd-v2-545222?include=source"

interfacepython

Compatibility

measured onNVIDIA L4

declared hardwareNVIDIA L4

architecturessm_89

dtypesfp16

Benchmark evidence

1 measurement across 1 GPU, fastest first.

Operation / workload

Hardware

Latency

Rank

Observed

FP16 vector additionsuite of 5 cases

NVIDIA L4

6.92ms

#17 of 26

2026-03-13

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Reported · How evidence levels are derived →

Source and license

sourceavailable

revision digestsha256:0218fb3e8cb8c28ee03ff3c19d8a19df71ce0fd334da785cf91535fde6ebfc26

license declaredunknown

license concludedunknown

authorsrajesh0042

imported2026-08-15

Kernel source

vectoradd_v3.py29 lines

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

import torch
import triton
import triton.language as tl
from task import input_t, output_t

# Vectoradd with Triton for potential better scheduling
@triton.jit
def vectoradd_kernel(
    a_ptr, b_ptr, out_ptr, n_elements,
    BLOCK_SIZE: tl.constexpr,
):
    pid = tl.program_id(0)
    offsets = pid * BLOCK_SIZE + tl.arange(0, BLOCK_SIZE)
    mask = offsets < n_elements
    a = tl.load(a_ptr + offsets, mask=mask)
    b = tl.load(b_ptr + offsets, mask=mask)
    tl.store(out_ptr + offsets, a + b, mask=mask)

def custom_kernel(data: input_t) -> output_t:
    A, B, output = data
    n = A.numel()
    BLOCK_SIZE = 1024
    grid = ((n + BLOCK_SIZE - 1) // BLOCK_SIZE,)
    vectoradd_kernel[grid](A, B, output, n, BLOCK_SIZE=BLOCK_SIZE)
    return output

scrolls · 29 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 545070.

  ⋯ 5 unchanged lines
  import triton.language as tl
  from task import input_t, output_t
   
+ # Vectoradd with Triton for potential better scheduling
  @triton.jit
  def vectoradd_kernel(
      a_ptr, b_ptr, out_ptr, n_elements,

Best evidence level for this revision: reported

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