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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Halo is an open-source framework built by White Circle for training large language and multimodal models
Making large AI models cheaper, faster and more accessible
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
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
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
A Python stream processing engine modeled after Yahoo! Pipes