Yong Wu

Open deep learning compiler stack for cpu, gpu and specialized accelerators

FlashInfer: Kernel Library for LLM Serving

TVM FFI

Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.

No description.

Virtualized Elastic KV Cache for Dynamic GPU Sharing and Beyond

Open Source Continuous Inference Benchmarking Qwen3.5, DeepSeek, GPTOSS - GB200 NVL72 vs MI355X vs B200 vs GB300 NVL72 vs H100 & soon™ TPUv6e/v7/Trainium2/3

Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels.

Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞

No description.

Our first fully AI generated deep learning system

Terraform module for scalable GitHub action runners on AWS

A Datacenter Scale Distributed Inference Serving Framework

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

Building the Virtuous Cycle for AI-driven LLM Systems

Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels

A standalone GEMM kernel for fp16 activation and quantized weight, extracted from FasterTransformer

SGLang is a fast serving framework for large language models and vision language models.

CUDA Templates for Linear Algebra Subroutines

A generative world for general-purpose robotics & embodied AI learning.

Repository which handles configuration of TVM CI infrastructure.

No description.

Development repository for the Triton language and compiler

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Empowering everyone to build reliable and efficient software.

Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

A high-throughput and memory-efficient inference and serving engine for LLMs

LLM training in simple, raw C/CUDA

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

No description.

Bringing large-language models and chat to web browsers. Everything runs inside the browser with no server support.

Backward compatible ML compute opset inspired by HLO/MHLO

Temp repo for prototyping relax(relay next), the effort will be upstreamed. We use the wiki pages on this repo to host design docs.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Deep Learning Examples

Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure

Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms

Model Serving on PyTorch

TensorFlow documentation

a language for fast, portable data-parallel computation

A Flexible and Powerful Parameter Server for large-scale machine learning

PyRobot: An Open Source Robotics Research Platform

Computation using data flow graphs for scalable machine learning

"Multi-Level Intermediate Representation" Compiler Infrastructure

The repo to host all the web data including images for documents in dmlc projects.

Kubernetes Native Edge Computing Framework (project under CNCF)

No description.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

《动手学深度学习》

A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

Programming exercises for learning Q# and quantum computing

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

No description.

Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

Fooling neural based speech recognition systems.

No description.