Alternatives and similar repositories for gemlite:

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

• pytorch-labs / applied-ai
  Applied AI experiments and examples for PyTorch
  ☆262Updated last week
• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆220Updated 3 months ago
• pytorch-labs / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆224Updated 9 months ago
• zinccat / Awesome-Triton-Kernels
  Collection of kernels written in Triton language
  ☆120Updated last month
• Deep-Learning-Profiling-Tools / triton-viz
  ☆202Updated last week
• pytorch-labs / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆120Updated this week
• Dao-AILab / fast-hadamard-transform
  Fast Hadamard transform in CUDA, with a PyTorch interface
  ☆183Updated 11 months ago
• ppl-ai / pplx-kernels
  Perplexity GPU Kernels
  ☆272Updated this week
• ColfaxResearch / cutlass-kernels
  ☆202Updated 9 months ago
• triton-lang / kernels
  ☆78Updated 5 months ago
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆248Updated 6 months ago
• MekkCyber / CutlassAcademy
  A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS
  ☆169Updated last month
• yifuwang / symm-mem-recipes
  ☆70Updated 4 months ago
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆252Updated last month
• cchan / tccl
  extensible collectives library in triton
  ☆85Updated last month
• stanford-futuredata / stk
  ☆104Updated 8 months ago
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆307Updated 10 months ago
• ScalingIntelligence / KernelBench
  KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems
  ☆288Updated last week
• spcl / QuaRot
  Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.
  ☆383Updated 5 months ago
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆194Updated this week
• Guangxuan-Xiao / torch-int
  This repository contains integer operators on GPUs for PyTorch.
  ☆203Updated last year
• microsoft / BitBLAS
  BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.
  ☆601Updated this week
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆73Updated 8 months ago
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆106Updated 9 months ago
• gpu-mode / ring-attention
  ring-attention experiments
  ☆132Updated 6 months ago
• tgale96 / grouped_gemm
  PyTorch bindings for CUTLASS grouped GEMM.
  ☆87Updated this week
• neuralmagic / compressed-tensors
  A safetensors extension to efficiently store sparse quantized tensors on disk
  ☆102Updated this week
• SqueezeAILab / KVQuant
  [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
  ☆346Updated 8 months ago
• BobMcDear / attorch
  A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.
  ☆536Updated this week
• triton-lang / triton-cpu
  An experimental CPU backend for Triton
  ☆109Updated last week