Statistics for topic distributed-computing

The open-source serverless GPU container runtime.

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.

Making large AI models cheaper, faster and more accessible

Small scale distributed training of sequential deep learning models, built on Numpy and MPI.

Distributed DataFrame for Python designed for the cloud, powered by Rust

The open-source serverless GPU container runtime.

Small scale distributed training of sequential deep learning models, built on Numpy and MPI.

AI for all: Build the large graph of the language models

Modern web-based distributed hashcracking solution, built on hashcat

A Web Crawler based on LLMs implemented with Ray and Huggingface. The embeddings are saved into a vector database for fast clustering and retrieval

The open-source serverless GPU container runtime.

Distributed DataFrame for Python designed for the cloud, powered by Rust

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.

AI for all: Build the large graph of the language models

The open-source serverless GPU container runtime.

Small scale distributed training of sequential deep learning models, built on Numpy and MPI.

Modern web-based distributed hashcracking solution, built on hashcat

AI for all: Build the large graph of the language models

A Web Crawler based on LLMs implemented with Ray and Huggingface. The embeddings are saved into a vector database for fast clustering and retrieval

AI for all: Build the large graph of the language models

Making large AI models cheaper, faster and more accessible

AI for all: Build the large graph of the language models

Distributed DataFrame for Python designed for the cloud, powered by Rust

Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

AI for all: Build the large graph of the language models

Modern web-based distributed hashcracking solution, built on hashcat

The open-source serverless GPU container runtime.

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

Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.

The open-source serverless GPU container runtime.

AI for all: Build the large graph of the language models

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

Automated Parallelization System and Infrastructure for Multiple Ecosystems

Making large AI models cheaper, faster and more accessible

Distributed DataFrame for Python designed for the cloud, powered by Rust

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.

Chains stable-diffusion-webui instances together to facilitate faster image generation.

Modern web-based distributed hashcracking solution, built on hashcat

AI for all: Build the large graph of the language models

Automated Parallelization System and Infrastructure for Multiple Ecosystems