pytorch / PiPPy
Pipeline Parallelism for PyTorch
☆749Updated 5 months ago
Alternatives and similar repositories for PiPPy:
Users that are interested in PiPPy are comparing it to the libraries listed below
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆514Updated this week
- A Python-level JIT compiler designed to make unmodified PyTorch programs faster.☆1,029Updated 10 months ago
- A library to analyze PyTorch traces.☆332Updated this week
- Large Context Attention☆682Updated 3 weeks ago
- This repository contains the experimental PyTorch native float8 training UX☆221Updated 6 months ago
- Microsoft Automatic Mixed Precision Library☆566Updated 4 months ago
- Helpful tools and examples for working with flex-attention☆635Updated this week
- A CPU+GPU Profiling library that provides access to timeline traces and hardware performance counters.☆767Updated this week
- Implementation of a Transformer, but completely in Triton☆257Updated 2 years ago
- Zero Bubble Pipeline Parallelism☆336Updated last week
- Ring attention implementation with flash attention☆674Updated 2 months ago
- Tutel MoE: An Optimized Mixture-of-Experts Implementation☆765Updated last week
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆723Updated 5 months ago
- 🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…☆221Updated last week
- A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs…☆2,182Updated this week
- Applied AI experiments and examples for PyTorch☆224Updated this week
- depyf is a tool to help you understand and adapt to PyTorch compiler torch.compile.☆581Updated 2 months ago
- An open-source efficient deep learning framework/compiler, written in python.☆681Updated last week
- A throughput-oriented high-performance serving framework for LLMs☆737Updated 4 months ago
- Implementation of 💍 Ring Attention, from Liu et al. at Berkeley AI, in Pytorch☆501Updated 3 months ago
- QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving☆496Updated this week
- Puzzles for learning Triton☆1,403Updated 3 months ago
- FlashInfer: Kernel Library for LLM Serving☆2,078Updated this week
- [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models☆1,339Updated 7 months ago
- A performant, memory-efficient checkpointing library for PyTorch applications, designed with large, complex distributed workloads in mind…☆154Updated 2 months ago
- 🚀 Collection of components for development, training, tuning, and inference of foundation models leveraging PyTorch native components.☆187Updated this week
- TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and sup…☆345Updated this week
- Mirage: Automatically Generating Fast GPU Kernels without Programming in Triton/CUDA☆743Updated last week
- Kernl lets you run PyTorch transformer models several times faster on GPU with a single line of code, and is designed to be easily hackab…☆1,556Updated last year
- USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference☆424Updated this week