Alternatives and similar repositories for calm

Users that are interested in calm are comparing it to the libraries listed below

• andrewkchan / yalm
  Yet Another Language Model: LLM inference in C++/CUDA, no libraries except for I/O
  ☆549Updated 4 months ago
• HazyResearch / Megakernels
  kernels, of the mega variety
  ☆657Updated 4 months ago
• tspeterkim / flash-attention-minimal
  Flash Attention in ~100 lines of CUDA (forward pass only)
  ☆1,058Updated last year
• perplexityai / pplx-kernels
  Perplexity GPU Kernels
  ☆554Updated 2 months ago
• salykova / sgemm.cu
  High-Performance FP32 GEMM on CUDA devices
  ☆117Updated last year
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆528Updated 4 months ago
• dropbox / gemlite
  Fast low-bit matmul kernels in Triton
  ☆424Updated this week
• Deep-Learning-Profiling-Tools / triton-viz
  ☆277Updated this week
• Dao-AILab / quack
  A Quirky Assortment of CuTe Kernels
  ☆772Updated this week
• gpu-mode / reference-kernels
  Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!
  ☆200Updated this week
• ROCm / aiter
  AI Tensor Engine for ROCm
  ☆348Updated this week
• kuterd / nv_isa_solver
  Nvidia Instruction Set Specification Generator
  ☆310Updated last year
• NVIDIA / tilus
  Tilus is a tile-level kernel programming language with explicit control over shared memory and registers.
  ☆440Updated last month
• microsoft / BitBLAS
  BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.
  ☆749Updated 5 months ago
• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆291Updated 4 months ago
• meta-pytorch / applied-ai
  Applied AI experiments and examples for PyTorch
  ☆314Updated 5 months ago
• NVIDIA / TileGym
  Helpful kernel tutorials and examples for tile-based GPU programming
  ☆617Updated this week
• microsoft / ArchProbe
  A profiler to disclose and quantify hardware features on GPUs.
  ☆175Updated 3 years ago
• mit-han-lab / omniserve
  [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…
  ☆807Updated 10 months ago
• BobMcDear / attorch
  A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.
  ☆596Updated 5 months ago
• neuralmagic / AutoFP8
  ☆206Updated 8 months ago
• IST-DASLab / marlin
  FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.
  ☆992Updated last year
• Jokeren / Awesome-GPU
  Awesome resources for GPUs
  ☆608Updated 2 years ago
• bertmaher / simplegemm
  ☆129Updated 3 months ago
• unixpickle / learn-ptx
  Learning about CUDA by writing PTX code.
  ☆151Updated last year
• efeslab / Nanoflow
  A throughput-oriented high-performance serving framework for LLMs
  ☆943Updated 3 months ago
• triton-lang / triton-cpu
  An experimental CPU backend for Triton
  ☆173Updated 2 months ago
• leimao / CUDA-GEMM-Optimization
  CUDA Matrix Multiplication Optimization
  ☆256Updated last year
• salykova / sgemm.c
  Multi-Threaded FP32 Matrix Multiplication on x86 CPUs
  ☆376Updated 9 months ago
• staghado / vit.cpp
  Inference Vision Transformer (ViT) in plain C/C++ with ggml
  ☆306Updated last year