DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Making large AI models cheaper, faster and more accessible
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πA curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.π
Minimalistic large language model 3D-parallelism training
xDiT: A Scalable Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism
A Python stream processing engine modeled after Yahoo! Pipes
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
A PyTorch-native inference engine with cache, parallelism, quantization and cpu offload for DiTs.
A scalable, agentic-first, and HuggingFace-native RL framework for research (9k lines).
MoonEP: A Perfectly Balanced Expert Parallelism Library via Dynamic Redundant Experts
Halo is an open-source framework built by White Circle for training large language and multimodal models
Benchmark of federated learning. Dedicated to the community. π€
Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
DeepSeek-V4-Flash-0731 on 4x CMP 170HX (sm_80): 98 tok/s decode, ~5300 tok/s prefill. DSpark speculative decoding under pipeline parallelism, which vLLM does not support upstream.
Typed RPC over a warm pool of PEP 734 subinterpreters β real parallelism, real error propagation, no hanging calls.
Switchless RoCE collectives, NCCL profiles and fabric tooling for DGX Spark inference recipes
MiniMax-H3 multi-GPU parallel inference for ComfyUI | ε€ε‘εΉΆθ‘ε ιθηΉ:2-8 GPU Ulysses sequence parallel, bit-identical video+audio generation