Jiarui Fang（方佳瑞）

Making large AI models cheaper, faster and more accessible

xDiT: A Scalable Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism

a fast and user-friendly runtime for transformer inference (Bert, Albert, GPT2, Decoders, etc) on CPU and GPU.

pytorch memory track code

Fast inference from large lauguage models via speculative decoding

PatrickStar enables Larger, Faster, Greener Pretrained Models for NLP and democratizes AI for everyone.

USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference

Analyze the inference of Large Language Models (LLMs). Analyze aspects like computation, storage, transmission, and hardware roofline model in a user-friendly interface.