matmul

Deadline

42 days 3 hours (2025-06-30 00:00 UTC)

Language

Python

GPU Types

A100, H100, L4, T4

Description

Implement a custom matmul function that matches the reference implementation. The function should handle a tuple of input tensors and apply matmul The shapes of all outer and inner dimensions of tensors are multiples of 16

Reference Implementation

import torch
from task import input_t, output_t
from utils import make_match_reference


def generate_input(m: int, n: int, k: int, seed: int) -> input_t:
    gen = torch.Generator(device='cuda')
    gen.manual_seed(seed)
    a = torch.empty(m, k, device='cuda', dtype=torch.float16)
    a.uniform_(0, 1, generator=gen)
    b = torch.empty(k, n, device='cuda', dtype=torch.float16)
    b.uniform_(0, 1, generator=gen)
    return (a, b)


def ref_kernel(data: input_t) -> output_t:
    a, b = data
    return a @ b


check_implementation = make_match_reference(ref_kernel)

Rankings

L4

nikhilap 🥇	2272.513μs	matmul.py
ajhinh 🥈	2344.244μs +71.732μs	l4.py
symlon 🥉	49335.120μs +46990.876μs	submission.py

T4

siclait 🥇	5959.204μs	submission.py
hatoo 🥈	6340.941μs +381.737μs	matmul.py
siro 🥉	6795.622μs +454.681μs	submission.py
salad	6881.867μs +86.246μs	ref.py
Shlok	6907.271μs +25.404μs	matmul.py
DizzleRama	7136.877μs +229.606μs	submission_cuda_inline_matmul.py
ajhinh	7938.621μs +801.744μs	t4.py

A100

ajhinh 🥇	661.865μs	a100.py
salad 🥈	724.330μs +62.466μs	matmul_triton.py
AM 🥉	728.589μs +4.259μs	my_submission.py
mashisong	731.574μs +2.985μs	matmul_triton.py
dtad	745.251μs +13.677μs	matmul_triton.py
mobicham	810.114μs +64.862μs	gemm_a100_v1.py
Nadav Timor	838.150μs +28.036μs	matmul.py
Bob	8157.397μs +7319.247μs	matmul.py

H100

tomaszki 🥇	249.341μs	submission.py
👾ubeai 🥈	251.279μs +1.938μs	matmul.py
ajhinh 🥉	258.918μs +7.639μs	h100.py
guoliang	289.560μs +30.643μs	dp-mm.py
AM	306.678μs +17.118μs	my_submission.py
salad	306.699μs +0.021μs	matmul_triton.py
dtad	343.679μs +36.979μs	matmul_triton.py
Nadav Timor	1823.825μs +1480.146μs	matmul.py