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
  ☆249Updated this week
• HanGuo97 / flute
  Fast Matrix Multiplications for Lookup Table-Quantized LLMs
  ☆232Updated 3 weeks ago
• pytorch-labs / float8_experimental
  This repository contains the experimental PyTorch native float8 training UX
  ☆222Updated 7 months ago
• gpu-mode / triton-index
  Cataloging released Triton kernels.
  ☆204Updated 2 months ago
• Deep-Learning-Profiling-Tools / triton-viz
  ☆190Updated last month
• zinccat / Awesome-Triton-Kernels
  Collection of kernels written in Triton language
  ☆114Updated last month
• cchan / tccl
  extensible collectives library in triton
  ☆83Updated 5 months ago
• efeslab / Atom
  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
  ☆298Updated 8 months ago
• ColfaxResearch / cutlass-kernels
  ☆190Updated 8 months ago
• usyd-fsalab / fp6_llm
  An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).
  ☆239Updated 4 months ago
• Dao-AILab / fast-hadamard-transform
  Fast Hadamard transform in CUDA, with a PyTorch interface
  ☆152Updated 9 months ago
• pranjalssh / fast.cu
  Fastest kernels written from scratch
  ☆191Updated 2 weeks ago
• IST-DASLab / Sparse-Marlin
  Boosting 4-bit inference kernels with 2:4 Sparsity
  ☆70Updated 6 months ago
• foundation-model-stack / foundation-model-stack
  🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.
  ☆189Updated this week
• ScalingIntelligence / KernelBench
  KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems
  ☆234Updated this week
• wangsiping97 / FastGEMV
  High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.
  ☆100Updated 8 months ago
• triton-lang / kernels
  ☆73Updated 4 months ago
• pytorch-labs / tritonbench
  Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.
  ☆104Updated this week
• spcl / QuaRot
  Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.
  ☆361Updated 3 months ago
• yifuwang / symm-mem-recipes
  ☆55Updated 2 months ago
• SqueezeBits / QUICK
  QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference
  ☆116Updated last year
• neuralmagic / compressed-tensors
  A safetensors extension to efficiently store sparse quantized tensors on disk
  ☆91Updated this week
• shawntan / scattermoe
  Triton-based implementation of Sparse Mixture of Experts.
  ☆207Updated 3 months ago
• microsoft / vattention
  Dynamic Memory Management for Serving LLMs without PagedAttention
  ☆317Updated this week
• 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…
  ☆595Updated 2 weeks ago
• stanford-futuredata / stk
  ☆101Updated 6 months ago
• microsoft / BitBLAS
  BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.
  ☆551Updated last month
• SqueezeAILab / KVQuant
  [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization
  ☆336Updated 7 months ago
• AlibabaResearch / flash-llm
  Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity
  ☆201Updated last year