microsoft / microxcalingLinks
PyTorch emulation library for Microscaling (MX)-compatible data formats
☆247Updated this week
Alternatives and similar repositories for microxcaling
Users that are interested in microxcaling are comparing it to the libraries listed below
Sorting:
- ☆149Updated 2 years ago
- ☆212Updated 11 months ago
- PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.☆110Updated 6 months ago
- A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores☆51Updated last year
- ☆98Updated last year
- A Easy-to-understand TensorOp Matmul Tutorial☆364Updated 9 months ago
- Shared Middle-Layer for Triton Compilation☆255Updated this week
- This repository contains integer operators on GPUs for PyTorch.☆205Updated last year
- Automatic Schedule Exploration and Optimization Framework for Tensor Computations☆176Updated 3 years ago
- ☆147Updated 11 months ago
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆109Updated 11 months ago
- SparseTIR: Sparse Tensor Compiler for Deep Learning☆138Updated 2 years ago
- ☆117Updated last month
- CUDA Matrix Multiplication Optimization☆196Updated 11 months ago
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆252Updated 7 months ago
- ☆101Updated last year
- Fast Hadamard transform in CUDA, with a PyTorch interface☆201Updated last year
- Experimental projects related to TensorRT☆105Updated this week
- ☆91Updated 5 months ago
- Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruct…☆421Updated 9 months ago
- Automatic Mapping Generation, Verification, and Exploration for ISA-based Spatial Accelerators☆112Updated 2 years ago
- Assembler for NVIDIA Volta and Turing GPUs☆222Updated 3 years ago
- Development repository for the Triton-Linalg conversion☆188Updated 4 months ago
- Magicube is a high-performance library for quantized sparse matrix operations (SpMM and SDDMM) of deep learning on Tensor Cores.☆89Updated 2 years ago
- Examples of CUDA implementations by Cutlass CuTe☆197Updated 4 months ago
- Fast low-bit matmul kernels in Triton☆322Updated this week
- ☆236Updated 2 years ago
- ☆154Updated 11 months ago
- llama INT4 cuda inference with AWQ☆54Updated 5 months ago
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆629Updated last month