microsoft / BitBLAS
BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.
☆612Updated last week
Alternatives and similar repositories for BitBLAS
Users that are interested in BitBLAS are comparing it to the libraries listed below
Sorting:
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆666Updated 2 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆248Updated 6 months ago
- Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.☆384Updated 5 months ago
- Fast low-bit matmul kernels in Triton☆299Updated this week
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆818Updated 8 months ago
- Dynamic Memory Management for Serving LLMs without PagedAttention☆366Updated 3 weeks ago
- Distributed Triton for Parallel Systems☆677Updated last week
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆308Updated 10 months ago
- Mirage: Automatically Generating Fast GPU Kernels without Programming in Triton/CUDA☆828Updated this week
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆352Updated 9 months ago
- Fast Hadamard transform in CUDA, with a PyTorch interface☆187Updated 11 months ago
- ☆319Updated last year
- A throughput-oriented high-performance serving framework for LLMs☆806Updated this week
- A Easy-to-understand TensorOp Matmul Tutorial☆353Updated 7 months ago
- Perplexity GPU Kernels☆281Updated 2 weeks ago
- Analyze the inference of Large Language Models (LLMs). Analyze aspects like computation, storage, transmission, and hardware roofline mod…☆454Updated 8 months ago
- Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels☆1,167Updated this week
- Applied AI experiments and examples for PyTorch☆265Updated 2 weeks ago
- Microsoft Automatic Mixed Precision Library☆595Updated 7 months ago
- A collection of memory efficient attention operators implemented in the Triton language.☆266Updated 11 months ago
- This repository contains integer operators on GPUs for PyTorch.☆204Updated last year
- flash attention tutorial written in python, triton, cuda, cutlass☆349Updated this week
- Puzzles for learning Triton, play it with minimal environment configuration!☆307Updated 5 months ago
- PyTorch emulation library for Microscaling (MX)-compatible data formats☆224Updated 3 weeks ago
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆536Updated this week
- FlagGems is an operator library for large language models implemented in the Triton Language.☆528Updated this week
- The official implementation of the EMNLP 2023 paper LLM-FP4☆199Updated last year
- Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity☆206Updated last year
- Fastest kernels written from scratch☆261Updated last month
- ☆202Updated 10 months ago