Search Results for "parallel programming frameworkc++" - Page 3

PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it.

The giServer is an easy-to-use integration server for process automation and event-driven or scheduled execution of batch jobs. Instead of using complex XML configuration files an elaborate GUI for batch job management is included. Some possible usage scenarios are: - Automatic processing of incoming data files - Big Data applications - Process automation - Data Mining/Aggregation applications - Automatic Reporting - Processing and analysis of database records

prog89S52 is a utility for Linux on the PC, allowing programming of Atmel's AT89S52 microcontroller via the parallel printer port. Atmel's 89S are programmable via an SPI port and therefore require absolutely no additional components in order to program them in-system. This program requires a standard "Centronics" type PC parallel port (a bidirectional, EPP or ECP port is not required).

Please participate in the SURVEY on rgedit's future: https://www.surveymonkey.com/s/VNMMJMJ your answers are much appreciated! Gedit (Gnome editor, www.gedit.org) plug-in allowing it to become an easy-to-use and yet light-weight IDE for the statistical programming environment, R (www.r-project.org).

An implementation of Dantzig-Wolfe decomposition built upon the GNU Linear Programming Kit. This is a command line tool for solving properly decomposed linear programs. There are several examples and some documentation to guide the use of this solver. Forked over to GitHub (see link).

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. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons.

CDIV GAMES STUDIO is a programming environment for multimedia applications mostly games using the power of the C/C++ and the graphics library ALLEGRO two are combined in the library CDIV that provides a parallel processing system based on processes style DIV2. Each process is an independent, each running a separate code to other processes and can be assigned graphics, rotation angles, execution priority, etc ...

A modest extension to C, XMTC allows representing parallel (PRAM) algorithms as parallel programs, and run XMTC code using a compiler and cycle accurate simulator of the University of Maryland explicit multi-threaded (XMT) many-core architecture.

Tsunami is an open-source high performance computing language. With it you can write streaming data-parallel algorithms that utilize GPGPUs for orders-of-magnitude speed-up with the ease of writing sequential algorithms.

GridABM is an easy-to-use toolkit to develop high-performance agent-based models (ABMs) in Repast. GridABM facilitates large-scale simulation of ABM on multicore computers, local computing clusters, or computational grids.

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.

Python bindings for OpenCL, the open standard for parallel programming of heterogeneous systems

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.

Parallel multithreaded programming language based on ANSI C. Easy to use, comes with a compiler and a runtime system.

42 has six primary goals: foster extreme code reuse; run faster than C; compile to both software and hardware; run faster on reconfigurable computers; support parallel programming; and allow users to extend the language.

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

PyGWA is a GPGPU library for Python. It contains Python bindings for AMD CAL and PyGWA.DP - a toy data-parallel programming API.

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.

pRPL is a general-purpose parallel Raster Processing C++ programming Library. It enables the implementation of parallel raster-based algorithms without requiring a deep understanding of parallel computing, and greatly reduces the development complexity.

MapReduce is a simple and flexible parallel programming model initially proposed by Google for large scale data processing in a distributed computing environment. This project implements the MapReduce runtime and API for the Cell processor platform.

Brook is an ANSI C like general purpose stream programming language and is designed to incorporate the ideas of data parallel computing and arithmetic intensity into a familiar, efficient language. Has OpenMP CPU, OpenGL, DirectX 9 and AMD CTM backends.

The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.

PyLife is an implementation of the game of life algorithm featuring parallel programming. It uses MPI and python to achieve a consistent software architecture and reliably performance.