jundaf2 / INT8-Flash-Attention-FMHA-QuantizationLinks
☆159Updated last year
Alternatives and similar repositories for INT8-Flash-Attention-FMHA-Quantization
Users that are interested in INT8-Flash-Attention-FMHA-Quantization are comparing it to the libraries listed below
Sorting:
- High-speed GEMV kernels, at most 2.7x speedup compared to pytorch baseline.☆114Updated last year
- This repository contains the experimental PyTorch native float8 training UX☆224Updated last year
- ☆110Updated last year
- An efficient GPU support for LLM inference with x-bit quantization (e.g. FP6,FP5).☆263Updated last month
- This repository contains integer operators on GPUs for PyTorch.☆215Updated last year
- Fast Hadamard transform in CUDA, with a PyTorch interface☆231Updated last week
- PyTorch bindings for CUTLASS grouped GEMM.☆113Updated 3 months ago
- Applied AI experiments and examples for PyTorch☆295Updated 3 weeks ago
- ☆81Updated 7 months ago
- Reorder-based post-training quantization for large language model☆195Updated 2 years ago
- ☆154Updated 2 years ago
- A collection of memory efficient attention operators implemented in the Triton language.☆277Updated last year
- Tritonbench is a collection of PyTorch custom operators with example inputs to measure their performance.☆221Updated this week
- ☆158Updated 2 years ago
- extensible collectives library in triton☆88Updated 5 months ago
- llama INT4 cuda inference with AWQ☆54Updated 7 months ago
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆118Updated last year
- ☆230Updated last year
- pytorch-profiler☆51Updated 2 years ago
- Triton-based implementation of Sparse Mixture of Experts.☆238Updated 2 weeks ago
- Fast low-bit matmul kernels in Triton☆357Updated this week
- Benchmark code for the "Online normalizer calculation for softmax" paper☆98Updated 7 years ago
- PyTorch extension for emulating FP8 data formats on standard FP32 Xeon/GPU hardware.☆111Updated 9 months ago
- The official implementation of the EMNLP 2023 paper LLM-FP4☆214Updated last year
- A Python library transfers PyTorch tensors between CPU and NVMe☆120Updated 9 months ago
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆319Updated last year
- Collection of kernels written in Triton language☆154Updated 5 months ago
- ☆74Updated 5 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆209Updated last week
- Boosting 4-bit inference kernels with 2:4 Sparsity☆82Updated last year