Trending repositories for topic distributed-computing
Making large AI models cheaper, faster and more accessible
Distributed DataFrame for Python designed for the cloud, powered by Rust
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Training and serving large-scale neural networks with auto parallelization.
An understandable, fast and scalable Raft Consensus implementation
Distributed DataFrame for Python designed for the cloud, powered by Rust
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
A curated list of awesome parallel computing resources
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Making large AI models cheaper, faster and more accessible
Training and serving large-scale neural networks with auto parallelization.
Making large AI models cheaper, faster and more accessible
Distributed DataFrame for Python designed for the cloud, powered by Rust
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of ti...
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
A crowdsourced distributed cluster for AI art and text generation
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
An understandable, fast and scalable Raft Consensus implementation
A next-generation dynamic and high-performance language for AI and IOT with natural born distributed computing ability.
IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练
The default client software to create images for the AI-Horde
Distributed DataFrame for Python designed for the cloud, powered by Rust
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Official implementation of "AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising"
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Arkouda (αρκούδα): Interactive Data Analytics at Supercomputing Scale :bear:
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Making large AI models cheaper, faster and more accessible
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Distributed DataFrame for Python designed for the cloud, powered by Rust
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of ti...
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
An understandable, fast and scalable Raft Consensus implementation
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
An understandable, fast and scalable Raft Consensus implementation
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
A Web Crawler based on LLMs implemented with Ray and Huggingface. The embeddings are saved into a vector database for fast clustering and retrieval. Use it for your RAG.
Create and control multiple Julia processes remotely for distributed computing. Ships as a Julia stdlib.
Unlock Unlimited Potential! Share Your GPU Power Across Your Local Network!
IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Official implementation of "AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising"
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
The default client software to create images for the AI-Horde
Modern web-based distributed hashcracking solution, built on hashcat
Distributed DataFrame for Python designed for the cloud, powered by Rust
A next-generation dynamic and high-performance language for AI and IOT with natural born distributed computing ability.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Official implementation of "AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising"
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
A Web Crawler based on LLMs implemented with Ray and Huggingface. The embeddings are saved into a vector database for fast clustering and retrieval. Use it for your RAG.
Unchained is a decentralized, federated network for data indexing, validation, analysis, processing, and delivery.
Unlock Unlimited Potential! Share Your GPU Power Across Your Local Network!
Create and control multiple Julia processes remotely for distributed computing. Ships as a Julia stdlib.
Making large AI models cheaper, faster and more accessible
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
Distributed DataFrame for Python designed for the cloud, powered by Rust
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
zenoh unifies data in motion, data in-use, data at rest and computations. It carefully blends traditional pub/sub with geo-distributed storages, queries and computations, while retaining a level of ti...
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
A crowdsourced distributed cluster for AI art and text generation
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
The current, performant & industrial strength version of Holochain on Rust.
Training and serving large-scale neural networks with auto parallelization.
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
A Golang based high performance, scalable and distributed workflow framework
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
IDDM (Industrial, landscape, animate...), support DDPM, DDIM, PLMS, webui and multi-GPU distributed training. Pytorch实现，生成模型，扩散模型，分布式训练
Tensor parallelism is all you need. Run LLMs on an AI cluster at home using any device. Distribute the workload, divide RAM usage, and increase inference speed.
An understandable, fast and scalable Raft Consensus implementation
Modern web-based distributed hashcracking solution, built on hashcat
The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
Automated Parallelization System and Infrastructure for Multiple Ecosystems
Distributed DataFrame for Python designed for the cloud, powered by Rust
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
An choreographer of core-domains, facilitating the abstraction of infrastructure, for a scalable domain model.
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
A tool to determine optimal projects for Gridcoin & BOINC crunchers. Maximize your magnitude!
Run GPU inference and training jobs on serverless infrastructure that scales with you.
Bounded-memory serverless distributed N-dimensional array processing
This project was a joint effort by Lucas De Oliveira, Chandrish Ambati, and Anish Mukherjee to create a song and playlist embeddings for recommendations in a distributed fashion using a 1M playlist da...
The PennyLane-Lightning plugin provides a fast state-vector simulator written in C++ for use with PennyLane