Search Results for "parallel" - Page 15

Rensselaer's Optimistic Simulation System, or ROSS, is a parallel discrete event simulator employing optimistic synchronization for multiple processors. ROSS has demonstrated scalability to 131,072 processors. ROSS implements reverse computation.

Schemik is an implicitly-parallel dialect of Scheme, this means the parallel execution of programs is done independently of the programmer.

On open source MPI implementation of parallel bucket sorting. This implementation is scalable and gives linear speedup on SGI(Altix). The program sorts at using the bits and hence is stronger than other sorters which make assumptions about keys.

Pypar is an efficient but easy-to-use module that allows programs written in Python to run in parallel on multiple processors and communicate using MPI. Pypar development has moved to http://code.google.com/p/pypar/

Open BEAGLE is a C++ Evolutionary Computation (EC) framework. It provides an high-level software environment to do any kind of EC, with support for tree-based genetic programming; bit string, integer-valued vector, and real-valued vector genetic algorithms; and evolution strategy. The Open BEAGLE architecture follows strong principles of object oriented programming, where abstractions are represented by loosely coupled objects and where it is common and easy to reuse code. Open BEAGLE is...

fpsc is a Fast Parallel Stream Compressor. It can use multiple CPUs to compress (gzip or bzip2) a data stream. (from stdin to stdout) It is built to achieve maximum throughput, everything else (especially memory usage) can be sacrified.

A framework for doing asynchronous socket communications - useful for connecting to a large number of hosts in parallel from a single thread. Builds on top of Java NIO library and hides all socket, buffer details.

Simple text editor for editing multiple language files in parallel. Corresponding translations are automatically highlighted in order to aid reviewing against multiple sources. Supports gettext PO and key = value format. Highly recommended for polyglots.

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.

Shared Questionnaire System(SQS) is a full-functional Optical Mark Reader(OMR) form processing system implemented in Java-Swing, XSL-FO and AJAX with straightforward GUIs. It is aimed at developing social platform to share knowledge about questionnaire.

Library is a C++ wrapper for libcURL. It adds multi-threading support, jobs based parallel request processing and high level class encapsulation.

There are a lot of create command line tools out there. But many of them are only using one core of a multicore system. With the parallel runner tools you can easyly start one application per core.

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.

NetWorkSpaces, developed by Scientific Computing Associates Inc., provides a framework to coordinate programs written in R. It allows users to write parallel programs in R easily.

A free software made to control the parallel port on linux systems. Programmed in C em GTK the software allows to control, monitore em automatize the old printer port, and made it useful again.

Originally made to crack /etc/passwd files from *nix utilizing the GPU. Uses GLSL and OpenGL. Acts as a parallel to John the Ripper, but for the GPU. Supports both ATI and nVidia, anywhere OpenGL can run.

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

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.

The intention of this project is to develop a library and framework which enables Java applications to use multicore processors. Several Ideas to help developers are as follows: Parallel For Work-Stealing Profiler for Parallel Applications ...

hardware log monitor that will display log behaviour via various hardware (parallel port, USB devices, ...). You can specify pattern(regexp) in log(s) on which hardware will turn on. It has also some unique ways of visualization of log files.

hwnetmon is hardware network monitor. It will display RX/TX/Collisions via various hardware (parallel port, USB devices, etc).

A Java library that provides accelerated downloads of HTTP/HTTPS URIs via the GET and POST methods. Works similar to download managers as requests are made in parallel and chunked for speed.

Using the CUDA API this project modifies the AutoDock software to run in parallel on NVIDIA GPUs. Users will be able to download and compile the code and use AutoDock on CUDA capable Graphics Cards. Autodock is located at http://autodock.scripps.edu/

The CodeTime platform covers every aspect of parallel software from authoring, through distribution, to run-time. Its goals are: high programmer productivity; write once, run high performance anywhere; and wide acceptance.