Trending repositories for topic distributed-computing
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
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...
Making large AI models cheaper, faster and more accessible
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Distributed data engine for Python/SQL designed for the cloud, powered by Rust
Scheduler for sub-node tasks for HPC systems with batch scheduling
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
A crowdsourced distributed cluster for AI art and text generation
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 unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
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.
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
Scheduler for sub-node tasks for HPC systems with batch scheduling
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...
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Distributed data engine for Python/SQL designed for the cloud, powered by Rust
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
A crowdsourced distributed cluster for AI art and text generation
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.
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
Making large AI models cheaper, faster and more accessible
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.
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
Making large AI models cheaper, faster and more accessible
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...
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Distributed data engine for Python/SQL 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
MooseFS Distributed Storage – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System / Software-Defined Storage
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.
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
Scheduler for sub-node tasks for HPC systems with batch scheduling
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
A Golang based high performance, scalable and distributed workflow framework
Fast, efficient, and scalable distributed map/reduce system, DAG execution, in memory or on disk, written in pure Go, runs standalone or distributedly.
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".
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...
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
Scheduler for sub-node tasks for HPC systems with batch scheduling
IDDM (Industrial, landscape, animate, spectrogram...), 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
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.
The PennyLane-Lightning plugin provides a fast state-vector simulator written in C++ for use with PennyLane
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Distributed data engine for Python/SQL 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 front-end GUI for interacting with the AI Horde / Stable Diffusion distributed cluster
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Arkouda (αρκούδα): Interactive Data Analytics at Supercomputing Scale :bear:
MooseFS Distributed Storage – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System / Software-Defined Storage
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
Distributed data engine for Python/SQL designed for the cloud, powered by Rust
Making large AI models cheaper, faster and more accessible
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
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.
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...
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.
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Gliimly is a new programming language and framework for writing high-performance web services and web applications, with focus on simplicity.
A Golang based high performance, scalable and distributed workflow framework
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
MooseFS Distributed Storage – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System / Software-Defined Storage
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
A crowdsourced distributed cluster for AI art and text generation
Gliimly is a new programming language and framework for writing high-performance web services and web applications, with focus on simplicity.
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
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.
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
The PennyLane-Lightning plugin provides a fast state-vector simulator written in C++ for use with PennyLane
The default client software to create images for the AI-Horde
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 23 datasets.
📦 Collect some Asynchronous Federated Learning papers.
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 data engine for Python/SQL designed for the cloud, powered by Rust
[NeurIPS 2024] AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
IDDM (Industrial, landscape, animate, spectrogram...), 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
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...
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
Scheduler for sub-node tasks for HPC systems with batch scheduling
[NeurIPS 2024] AsyncDiff: Parallelizing Diffusion Models by Asynchronous Denoising
Super-Efficient RLHF Training of LLMs with Parameter Reallocation
Unlock Unlimited Potential! Share Your GPU Power Across Your Local Network!
Gliimly is a new programming language and framework for writing high-performance web services and web applications, with focus on simplicity.
the small distributed language model toolkit; fine-tune state-of-the-art LLMs anywhere, rapidly
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 data engine for Python/SQL 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 23 datasets.
Run serverless GPU workloads with fast cold starts on bare-metal servers, anywhere in the world
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...
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
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.
A list of papers about distributed consensus.
Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang
A crowdsourced distributed cluster for AI art and text generation
A Golang based high performance, scalable and distributed workflow framework
A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
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.
The default client software to create images for the AI-Horde
An understandable, fast and scalable Raft Consensus implementation
Modern web-based distributed hashcracking solution, built on hashcat
Create and control multiple Julia processes remotely for distributed computing. Ships as a Julia stdlib.
Unchained is a decentralized, federated network for data indexing, validation, analysis, processing, and delivery.
Small scale distributed training of sequential deep learning models, built on Numpy and MPI.
IDDM (Industrial, landscape, animate, spectrogram...), 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
Gliimly is a new programming language and framework for writing high-performance web services and web applications, with focus on simplicity.
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
A next-generation dynamic and high-performance language for AI and IOT with natural born distributed computing ability.
Distributed data engine for Python/SQL designed for the cloud, powered by Rust
The is the official implementation of ICML 2023 paper "Revisiting Weighted Aggregation in Federated Learning with Neural Networks".
