Alternatives and similar repositories for cuda-mnist

Users that are interested in cuda-mnist are comparing it to the libraries listed below

• linjames0 / Transformer-CUDA
  An implementation of the transformer architecture onto an Nvidia CUDA kernel
  ☆190Updated 2 years ago
• siboehm / ShallowSpeed
  Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
  ☆142Updated last year
• jax-ml / ml_dtypes
  A stand-alone implementation of several NumPy dtype extensions used in machine learning.
  ☆299Updated last week
• gpu-mode / profiling-cuda-in-torch
  ☆172Updated last year
• salykova / sgemm.cu
  High-Performance SGEMM on CUDA devices
  ☆103Updated 8 months ago
• andreinechaev / nvcc4jupyter
  A plugin for Jupyter Notebook to run CUDA C/C++ code
  ☆244Updated last year
• lessw2020 / triton_kernels_for_fun_and_profit
  Custom kernels in Triton language for accelerating LLMs
  ☆25Updated last year
• eduardoleao052 / Autograd-from-scratch
  Documented and Unit Tested educational Deep Learning framework with Autograd from scratch.
  ☆120Updated last year
• gau-nernst / learn-cuda
  Learn CUDA with PyTorch
  ☆84Updated this week
• salykova / sgemm.c
  Multi-Threaded FP32 Matrix Multiplication on x86 CPUs
  ☆356Updated 5 months ago
• hidet-org / hidet
  An open-source efficient deep learning framework/compiler, written in python.
  ☆728Updated 3 weeks ago
• CisMine / Guide-NVIDIA-Tools
  NVIDIA tools guide
  ☆142Updated 8 months ago
• andylolu2 / simpleGEMM
  The simplest but fast implementation of matrix multiplication in CUDA.
  ☆39Updated last year
• BobMcDear / attorch
  A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.
  ☆576Updated last month
• Deep-Learning-Profiling-Tools / triton-viz
  ☆240Updated this week
• gevtushenko / llm.c
  LLM training in simple, raw C/CUDA
  ☆104Updated last year
• gpu-mode / reference-kernels
  Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!
  ☆96Updated 2 weeks ago
• MekkCyber / TritonAcademy
  A repository to unravel the language of GPUs, making their kernel conversations easy to understand
  ☆194Updated 3 months ago
• tgautam03 / xGeMM
  Accelerated General (FP32) Matrix Multiplication from scratch in CUDA
  ☆139Updated 8 months ago
• mlops-discord / gpu-optimization-workshop
  Slides, notes, and materials for the workshop
  ☆331Updated last year
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆355Updated last week
• NVIDIA / accelerated-computing-hub
  NVIDIA curated collection of educational resources related to general purpose GPU programming.
  ☆716Updated this week
• mobiusml / gemlite
  Fast low-bit matmul kernels in Triton
  ☆373Updated this week
• Quentin-Anthony / nanoMPI
  Simple MPI implementation for prototyping or learning
  ☆279Updated last month
• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆260Updated 2 weeks ago
• unixpickle / learn-ptx
  Learning about CUDA by writing PTX code.
  ☆135Updated last year
• ulrichstern / cuda-convnet
  Alex Krizhevsky's original code from Google Code
  ☆198Updated 9 years ago
• srush / triton-autodiff
  Experiment of using Tangent to autodiff triton
  ☆81Updated last year
• clu0 / unet.cu
  UNet diffusion model in pure CUDA
  ☆647Updated last year
• mlcommons / algorithmic-efficiency
  MLCommons Algorithmic Efficiency is a benchmark and competition measuring neural network training speedups due to algorithmic improvement…
  ☆398Updated this week