Driving DistCC-based distributed compilation in a smarter way, without having to deal with DISTCC_HOSTS intricacies and without stalling your dev machine
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Updated
May 23, 2024 - Shell
Driving DistCC-based distributed compilation in a smarter way, without having to deal with DISTCC_HOSTS intricacies and without stalling your dev machine
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 distributed Satellite to Ground Station communication system built in C using MPI
Distributed computing is the field of study that deals with the division of tasks between multiple computers connected in a network.
mirai - Minimalist Async Evaluation Framework for R
Standard implementation of client-side-validation APIs
Making large AI models cheaper, faster and more accessible
The current, performant & industrial strength version of Holochain on Rust.
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 time and space efficiency that is well beyond any of the mainstream stacks.
An experimental platform for federated learning.
Deep reinforcement learning for smart calibration of radio telescopes. Automatic hyper-parameter tuning.
Arkouda (αρκούδα): Interactive Data Analytics at Supercomputing Scale 🐻
Run LLMs on weak devices or make powerful devices even more powerful by distributing the workload and dividing the RAM usage.
Open-source software for volunteer computing and grid computing.
The open-source serverless GPU container runtime.
Multi-platform Scheduling and Workflows Engine
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
The PennyLane-Lightning plugin provides a fast state-vector simulator written in C++ for use with PennyLane
🚀 R package: future: Unified Parallel and Distributed Processing in R for Everyone
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