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lhao499 avatar

lhao499/RingAttention

0
View on GitHub↗
773 stars·53 forks·Python·Apache-2.0·4 views

RingAttention

Large Context Attention

Features

  • Attention Optimization - Distributes long-context attention across multiple devices.
  • Distributed Parallelism - Blockwise parallel attention for near-infinite context windows.

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Open-source alternatives to RingAttention

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  • bytedance/shadowkvbytedance avatar

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Frequently asked questions

What does lhao499/ringattention do?

Large Context Attention

What are the main features of lhao499/ringattention?

The main features of lhao499/ringattention are: Attention Optimization, Distributed Parallelism.

What are some open-source alternatives to lhao499/ringattention?

Open-source alternatives to lhao499/ringattention include: dmlc/mxnet — MXNet is a deep learning framework and distributed machine learning engine designed for training and deploying neural… modeltc/lightllm — LightLLM is a high-performance serving framework for deploying and executing large language models. It functions as a… stability-ai/stablelm — StableLM is a pre-trained transformer-based large language model designed for natural language generation and… bytedance/shadowkv — [ICML 2025 Spotlight] ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference. deepseek-ai/deepep — DeepEP is a distributed model accelerator and expert-parallel communication library designed to optimize the training… deepseek-ai/3fs — 3FS is a distributed file system and RDMA storage cluster designed for high-performance AI training and inference…