Alternatives and similar repositories for Awesome-Triton-Kernels

Users that are interested in Awesome-Triton-Kernels are comparing it to the libraries listed below

• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆242Updated 6 months ago
• mobiusml / gemlite
  Fast low-bit matmul kernels in Triton
  ☆330Updated this week
• Deep-Learning-Profiling-Tools / triton-viz
  ☆225Updated this week
• pytorch-labs / applied-ai
  Applied AI experiments and examples for PyTorch
  ☆281Updated last month
• pytorch-labs / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆184Updated this week
• Dao-AILab / quack
  A Quirky Assortment of CuTe Kernels
  ☆281Updated this week
• gpu-mode / ring-attention
  ring-attention experiments
  ☆144Updated 8 months ago
• triton-lang / kernels
  ☆83Updated 8 months ago
• cchan / tccl
  extensible collectives library in triton
  ☆87Updated 3 months ago
• tgale96 / grouped_gemm
  PyTorch bindings for CUTLASS grouped GEMM.
  ☆101Updated last month
• pytorch-labs / helion
  A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.
  ☆187Updated this week
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆255Updated 8 months ago
• pytorch-labs / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆224Updated 11 months ago
• Dao-AILab / fast-hadamard-transform
  Fast Hadamard transform in CUDA, with a PyTorch interface
  ☆201Updated last year
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆205Updated this week
• shawntan / scattermoe
  Triton-based implementation of Sparse Mixture of Experts.
  ☆224Updated 7 months ago
• stanford-futuredata / stk
  ☆106Updated 10 months ago
• MekkCyber / CutlassAcademy
  A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS
  ☆195Updated 2 months ago
• tspeterkim / paged-attention-minimal
  a minimal cache manager for PagedAttention, on top of llama3.
  ☆93Updated 10 months ago
• open-lm-engine / cute-kernels
  A bunch of kernels that might make stuff slower 😉
  ☆54Updated this week
• ColfaxResearch / cutlass-kernels
  ☆216Updated last year
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆290Updated 3 months ago
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆112Updated last year
• HazyResearch / Megakernels
  kernels, of the mega variety
  ☆441Updated last month
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆313Updated last year
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆80Updated 10 months ago
• ademeure / DeeperGEMM
  DeeperGEMM: crazy optimized version
  ☆69Updated 2 months ago
• FlagOpen / FlagAttention
  A collection of memory efficient attention operators implemented in the Triton language.
  ☆272Updated last year
• AlibabaResearch / flash-llm
  Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity
  ☆216Updated last year
• EfficientMoE / MoE-Infinity
  PyTorch library for cost-effective, fast and easy serving of MoE models.
  ☆207Updated last week