tspeterkim / mixed-precision-from-scratchLinks
Mixed precision training from scratch with Tensors and CUDA
☆25Updated last year
Alternatives and similar repositories for mixed-precision-from-scratch
Users that are interested in mixed-precision-from-scratch are comparing it to the libraries listed below
Sorting:
- ring-attention experiments☆149Updated 10 months ago
- ☆163Updated last year
- Learn CUDA with PyTorch☆67Updated this week
- Cataloging released Triton kernels.☆252Updated 7 months ago
- Load compute kernels from the Hub☆258Updated this week
- The simplest implementation of recent Sparse Attention patterns for efficient LLM inference.☆85Updated last month
- a minimal cache manager for PagedAttention, on top of llama3.☆119Updated last year
- ☆234Updated last week
- Code for studying the super weight in LLM☆115Updated 8 months ago
- Collection of kernels written in Triton language☆152Updated 4 months ago
- Flash-Muon: An Efficient Implementation of Muon Optimizer☆174Updated 2 months ago
- This repository contains the experimental PyTorch native float8 training UX☆224Updated last year
- Applied AI experiments and examples for PyTorch☆292Updated last week
- ☆123Updated 3 months ago
- ☆140Updated 6 months ago
- The evaluation framework for training-free sparse attention in LLMs☆91Updated 2 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆214Updated 3 months ago
- ☆118Updated last year
- Fast low-bit matmul kernels in Triton☆356Updated this week
- ☆39Updated 5 months ago
- Triton-based implementation of Sparse Mixture of Experts.☆233Updated last week
- [ICLR2025] Breaking Throughput-Latency Trade-off for Long Sequences with Speculative Decoding☆125Updated 8 months ago
- QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference☆119Updated last year
- QuTLASS: CUTLASS-Powered Quantized BLAS for Deep Learning☆71Updated last month
- ☆192Updated 7 months ago
- A repository to unravel the language of GPUs, making their kernel conversations easy to understand☆191Updated 3 months ago
- Small scale distributed training of sequential deep learning models, built on Numpy and MPI.☆136Updated last year
- A minimal implementation of vllm.☆52Updated last year
- Cold Compress is a hackable, lightweight, and open-source toolkit for creating and benchmarking cache compression methods built on top of…☆144Updated last year
- Tree Attention: Topology-aware Decoding for Long-Context Attention on GPU clusters☆129Updated 8 months ago