Search Results for "parallel programming frameworkc++"

dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.

A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. NeuraNEP emulates a distributed processing environment capable of handling millions of microthreads in parallel, for example running neural networks with millions of spiking cells.

Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programming language. Primarily targeted at evolutionary computing and similar master-slave configurations.

Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru

Roomy is a programming language extension for writing parallel disk-based applications. All details of parallelism and disk I/O are hidden within the Roomy library.

Meerkat is a distributed programming environment. It consists of a virtual machine which is suited to parallel processing. The data model is based on the concept of actors, although it is much more permissive than the traditional description.

LIME (Less-is-More) is parallel/concurrent programming environment based on C. Internally, it uses XML technology to describe tasks and their dependencies. Externally, it offers the ANSI C99 programming as well as a set of visually-oriented interfaces.

Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster

A data parallel scientific programming model. Compiles efficiently to different platforms like distributed memory (MPI), shared memory multi-processor (pthreads), Cell BE processor, Nvidia Cuda, SIMD vectorization (SSE, Altivec), and sequential C++ code.

TPO++ is an object-oriented message passing library intended for parallel programming. It is based on the Message Passing Interface (MPI) but allows to transmit objects and data structures of the standard template library.

The project is a “data-parallel” C++ library to teach parallel programming concepts. We intend to make this library portable, small, and easy to extend to work with real parallel message passing systems such as MPI and PVM. Darrell Raymond Ulm

This project is setup to maintain a set of Javaparty codes. This includes Javaparty benchmarks and applications. Javaparty (http://www.ipd.uka.de/JavaParty/) is a Java extension for easy and efficient parallel programming. It does so by extending the

TOP-C is a library for easily writing parallel applications for both distributed and shared memory architectures. It hides the details of parallel programming, and presents the application programmer with a simple task-oriented interface.

MassiveJava is a Java-based environment for parallel programming. Lithium is able to execute the parallel application using a cluster or a network of workstations. A user is able to program a parallel application without take in account problem like sche