awesome-repositories.com
博客
MCP
awesome-repositories.com

通过 AI 驱动的搜索,发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目MCP 服务器关于排名机制媒体报道
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
flexflow avatar

flexflow/FlexFlow

0
View on GitHub↗
1,889 星标·252 分支·C++·Apache-2.0·6 次浏览flexflow.ai↗

FlexFlow

Automatically Discovering Fast Parallelization Strategies for Distributed Deep Neural Network Training

Features

  • Inference Frameworks - Framework for speculative inference and token verification.

Star 历史

flexflow/flexflow 的 Star 历史图表flexflow/flexflow 的 Star 历史图表

AI 搜索

探索更多 awesome 仓库

用简单的语言描述您的需求 —— AI 将根据相关性为您从数千个精选开源项目中进行排序。

Start searching with AI

FlexFlow 的开源替代方案

相似的开源项目,按与 FlexFlow 的功能重合度排序。
  • efeslab/nanoflowefeslab 的头像

    efeslab/Nanoflow

    965在 GitHub 上查看↗

    A throughput-oriented high-performance serving framework for LLMs

    Jupyter Notebookcudainferencellama2
    在 GitHub 上查看↗965
  • flashinfer-ai/flashinferflashinfer-ai 的头像

    flashinfer-ai/flashinfer

    4,996在 GitHub 上查看↗

    FlashInfer is a library of high-performance GPU kernels purpose-built for accelerating large language model inference. It provides optimized implementations for attention operations (including flash attention, page attention, multi-head latent attention, and cascade attention) using paged key-value caches, fused kernel composition, and just-in-time compilation. The library also includes specialized kernels for mixture-of-experts layers, block-scaled low-precision quantization (FP8, FP4), and distributed collective communication. What distinguishes FlashInfer is its fused all-reduce communicat

    Pythonattentioncudadistributed-inference
    在 GitHub 上查看↗4,996
  • fminference/flexgenFMInference 的头像

    FMInference/FlexGen

    9,366在 GitHub 上查看↗

    FlexGen is an inference engine for large language models designed for high-throughput execution on single or multiple GPUs. It functions as a framework for managing model execution through a combination of memory offloading, weight compression, and pipeline orchestration. The system enables the execution of models that exceed available GPU memory by moving tensors and caches between GPU memory, system RAM, and disk storage. It utilizes 4-bit weight quantization to reduce the memory footprint of model parameters, allowing for increased batch processing capacity. The project covers distributed

    Python
    在 GitHub 上查看↗9,366
  • bigscience-workshop/petalsbigscience-workshop 的头像

    bigscience-workshop/petals

    10,208在 GitHub 上查看↗

    Petals is a decentralized framework and inference engine for running large language models across a peer-to-peer network. It enables the execution of models that exceed the memory of any single machine by splitting computations and model layers across a collaborative swarm of GPUs. The system functions as a collaborative compute network where participants share local GPU resources and host model weights. It supports distributed prompt-tuning to adapt massive models to specific tasks and allows for the establishment of private compute swarms to process sensitive data within restricted, trusted

    Python
    在 GitHub 上查看↗10,208
查看 FlexFlow 的所有 19 个替代方案→

常见问题解答

flexflow/flexflow 是做什么的?

Automatically Discovering Fast Parallelization Strategies for Distributed Deep Neural Network Training

flexflow/flexflow 的主要功能有哪些?

flexflow/flexflow 的主要功能包括:Inference Frameworks。

flexflow/flexflow 有哪些开源替代品?

flexflow/flexflow 的开源替代品包括: efeslab/nanoflow — A throughput-oriented high-performance serving framework for LLMs. flashinfer-ai/flashinfer — FlashInfer is a library of high-performance GPU kernels purpose-built for accelerating large language model inference.… fminference/flexgen — FlexGen is an inference engine for large language models designed for high-throughput execution on single or multiple… ggerganov/llama.cpp — llama.cpp is a high-performance C++ inference engine and runtime for executing large language models locally across… inferflow/inferflow — Inferflow is an efficient and highly configurable inference engine for large language models (LLMs). bigscience-workshop/petals — Petals is a decentralized framework and inference engine for running large language models across a peer-to-peer…