Search Results for "parallel computing"

Membrane Computing is a new research area (within Natural Computing) that aims to provide computing devices abstracted from the functioning and structure of living cells. These devices are called P systems. The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g.

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. Microthreads are general processing elements that can also represent non-neural elements, such as cell populations, extracellular space, emulating...

Mapgraph is SYSTAP’s disruptive new technology to exploit the main memory bandwidth advantages of GPUs. The early work was co-developed with the University of Utah SCI Institute and has its pedigree in the UINTAH software running on over 750M cores on the TITAN Super Computer. Today, SYSTAP has commercialized this technology into it’s Blazegraph Accelerator and Blazegraph HPC products. Checkout our options for GPU acceleration of graphs or contact us to learn more: ...

RT-BOINC stands for a Real-Time BOINC. It was designed for managing highly-interactive, short-term, and massively-parallel real-time applications. We implemented RT-BOINC on top of the recent BOINC server source codes.

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.

Numerical package Parallel EXECution. Using a numerical package like Octave, 'npexec' distribute computation of a math formula among various network elements, collecting result automatically. ->y=npexec('fft(x.^m)', 'm=-8:8','x=ARG');

Pydusa is a package for parallel programming using Python. It contains a module for doing MPI programming in Python. We have added parallel solver packages such as Parallel SuperLU for solving sparse linear systems.

Parallel File Compressor Compatible With bzip2

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.

Personal supercomputer on a disk! The Science by FlashMob project creates specialized live booting CDs that create a single user supercomputer from a set of handy laptop or desktop machines. Suitable for MPI, CHARM++, and pyMPI parallel programs.

MPIRuby is a Ruby version of the MPI supercomputing standard interface. It enables massively parallel and distributed algorithms to be written in a platform-independent manner suitable for large-scale computation-intensive experiments. MPI is the \"Mes

RAFT-Net is a Fault Tolerant Parallel Distributed Framework. Using a Master-Worker scheme, the framework transparently distributes workunits to workers (drones). These workers can join and leave and as such, the network is very flexible. A modified