Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.
 
Ray AI Runtime (AIR) is an open-source toolkit for building ML applications. It provides libraries for distributed data processing, model training, tuning, reinforcement learning, model serving, and more.
 
Ray Core provides a simple and flexible API for building and running your distributed applications. You can often parallelize single machine code with little to zero code changes.
 
With a Ray cluster you can deploy your workloads on AWS, GCP, Azure or on premise. You can also use Ray cluster managers to run Ray on your existing Kubernetes, YARN, or Slurm clusters.

Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.


Ray - A unified framework for scaling AI and Python applications

The fastest, most reliable, Redis-based queue for Node. Carefully written for rock solid stability and atomicity. 
<ul>
<li> Minimal CPU usage due to a polling-free design.</li>
<li> Robust design based on Redis.</li>
<li> Delayed jobs.</li>
<li> Schedule and repeat jobs according to a cron specification.</li>
<li> Rate limiter for jobs.</li>
<li> Retries.</li>
<li> Priority.</li>
<li> Concurrency.</li>
<li> Pause/resume—globally or locally.</li>
<li> Multiple job types per queue.</li>
<li> Threaded (sandboxed) processing functions.</li>
<li> Automatic recovery from process crashes.</li>
</ul>

The fastest, most reliable, Redis-based queue for Node. Carefully written for rock solid stability and atomicity. 

Bull - Premium package for handling jobs and messages in NodeJS

Rayon is a data-parallelism library for Rust. It is extremely lightweight and makes it easy to convert a sequential computation into a parallel one. It also guarantees data-race freedom. Rayon makes it drop-dead simple to convert sequential iterators into parallel ones: usually, you just change your foo.iter() call into foo.par_iter(), and Rayon does the rest.
 
Parallel iterators take care of deciding how to divide your data into tasks; it will dynamically adapt for maximum performance. If you need more flexibility than that, Rayon also offers the join and scope functions, which let you create parallel tasks on your own. For even more control, you can create custom threadpools rather than using Rayon's default, global threadpool.

Rayon is a data-parallelism library for Rust. It is extremely lightweight and makes it easy to convert a sequential computation into a parallel one. It also guarantees data-race freedom. Rayon makes it drop-dead simple to convert sequential iterators into parallel ones: usually, you just change your foo.iter() call into foo.par_iter(), and Rayon does the rest.

Rayon - A data parallelism library for Rust

ArrayFire is a high performance software library for parallel computing with an easy-to-use API. Its array based function set makes parallel programming simple. ArrayFire's multiple backends (CUDA, OpenCL and native CPU) make it platform independent and highly portable. A few lines of code in ArrayFire can replace dozens of lines of parallel computing code, saving you valuable time and lowering development costs.

ArrayFire - Parallel Computing Library

MPJ Express is an open source Java message passing library that allows application developers to write and execute parallel applications for multicore processors and compute clusters/clouds. It allows writing parallel Java applications using an MPI-like API.

MPJ Express - Parallel Programming in Java

Functional Java is an open source library facilitating functional programming in Java. The library implements numerous basic and advanced programming abstractions that assist composition oriented development. Functional Java also serves as a platform for learning functional programming concepts by introducing these concepts using a familiar language.


Functional java - A Library for Functional Programming in Java

The Stratosphere System is an open-source cluster/cloud computing framework for Big Data analytics. It comprises of An extensible higher level language (Meteor) to quickly compose queries for common and recurring use cases, A parallel programming model (PACT, an extension of MapReduce) to run user-defined operations, An efficient massively parallel runtime (Nephele) for fault tolerant execution of acyclic data flows. 
 
Stra­tosphere (named after the layer of the atmosphere above the clouds) explores the power of massively parallel computing for complex information manage­ment applications.

The Stratosphere System is an open-source cluster/cloud computing framework for Big Data analytics. It comprises of An extensible higher level language (Meteor) to quickly compose queries for common and recurring use cases, A parallel programming model (PACT, an extension of MapReduce) to run user-defined operations, An efficient massively parallel runtime (Nephele) for fault tolerant execution of acyclic data flows. 

StratoSphere - Cloud Computing Framework for Big Data Analytics

TymeacDSE is a full-feature, multi-threading, Data Parallel framework for Java SE development (RMI and internal server). TymeacDSE provides a high performance queuing facility, professional thread management and recursive processing that is easy to use.

TymeacDSE - Data Parallel framework for Java development

There is a lot of intellectual fog around the concept of genetic algorithms (GAs). It's important to appreciate the fact that GAs are composed of many nuts and bolts. There isn't a single definition of genetic algorithms. gago is intended to be a toolkit where one may run many kinds of genetic algorithms, with different evolution models and various genetic operators.

gago - An extensible toolkit for conceiving and running genetic algorithms

Napa.js is a multi-threaded JavaScript runtime built on V8, which was originally designed to develop highly iterative services with non-compromised performance in Bing. As it evolves, we find it useful to complement Node.js in CPU-bound tasks, with the capability of executing JavaScript in multiple V8 isolates and communicating between them. Napa.js is exposed as a Node.js module, while it can also be embedded in a host process without Node.js dependency.

Napa.js - A multi-threaded JavaScript runtime

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