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.
  ☆213Updated 3 months ago
• mobiusml / gemlite
  Fast low-bit matmul kernels in Triton
  ☆279Updated last week
• pytorch-labs / applied-ai
  Applied AI experiments and examples for PyTorch
  ☆256Updated 3 weeks ago
• Deep-Learning-Profiling-Tools / triton-viz
  ☆195Updated 2 weeks ago
• pytorch-labs / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆108Updated last week
• Dao-AILab / fast-hadamard-transform
  Fast Hadamard transform in CUDA, with a PyTorch interface
  ☆166Updated 10 months ago
• pytorch-labs / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆222Updated 8 months ago
• triton-lang / kernels
  ☆76Updated 5 months ago
• cchan / tccl
  extensible collectives library in triton
  ☆84Updated last week
• HanGuo97 / flute
  Fast Matrix Multiplications for Lookup Table-Quantized LLMs
  ☆236Updated last month
• gpu-mode / ring-attention
  ring-attention experiments
  ☆129Updated 5 months ago
• stanford-futuredata / stk
  ☆103Updated 7 months ago
• shawntan / scattermoe
  Triton-based implementation of Sparse Mixture of Experts.
  ☆210Updated 4 months ago
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆103Updated 8 months ago
• ColfaxResearch / cutlass-kernels
  ☆194Updated 8 months ago
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆190Updated last week
• ScalingIntelligence / KernelBench
  KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems
  ☆254Updated last week
• MekkCyber / CutlassAcademy
  A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS
  ☆156Updated 2 weeks ago
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆245Updated 5 months ago
• tgale96 / grouped_gemm
  PyTorch bindings for CUTLASS grouped GEMM.
  ☆78Updated 5 months ago
• ByteDance-Seed / Triton-distributed
  Distributed Triton for Parallel Systems
  ☆146Updated this week
• jundaf2 / INT8-Flash-Attention-FMHA-Quantization
  ☆157Updated last year
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆72Updated 7 months ago
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆213Updated last week
• andylolu2 / simpleGEMM
  The simplest but fast implementation of matrix multiplication in CUDA.
  ☆34Updated 8 months ago
• AlibabaResearch / flash-llm
  Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity
  ☆203Updated last year
• FlagOpen / FlagAttention
  A collection of memory efficient attention operators implemented in the Triton language.
  ☆259Updated 10 months ago
• microsoft / vattention
  Dynamic Memory Management for Serving LLMs without PagedAttention
  ☆345Updated 2 weeks ago
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆303Updated 9 months ago
• neuralmagic / compressed-tensors
  A safetensors extension to efficiently store sparse quantized tensors on disk
  ☆98Updated this week