Search Results for "data processing"

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.

FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines

distributedPHP client is a simple PHP script that can simultaneously activate/send data to as many web scripts as you want. You must open and configure the distributedPHP .php file prior to running it. ditributedPHP client supports activating scripts without data, sending the same data to all scripts, sending unique data to each script or sending user input to each script. Examples of use include: distributed math computation, encryption breaking, SETI@home/folding@home (well, if they made the projects in php..) distributed bruteforce attacks, ddos attacks, distributed processing, etc.. ...

The Simple, Scalable, Script-based Science Processor for Measurements (S4PM) is a system for highly automated processing of science data, scalable up to large processing systems and scalable down to small, special-purpose processing strings.

This project aims to create a method able to determine the most frequent word phrases in a large source of text data (>5 Gb) using the computational power of multiple processors.

Open Source Remote Sensing OSSIM project, pronounced "awesome", will leverage existing algorithms/tools/packages from the open source community in construction of the ultimate Remote Sensing/Image Processing/GIS package. osgPlanet extends OSSIM and Op

Collection of Java tools and packages related to server-side (web application-oriented) XML processing, such as Adaptive XML Inclusions system with demo. Tools for personalization of XML content, Java-XML data binding and others will come later.

A Middleware for Distrubted Data Stream Processing

The DataTime Process Framework is intended to support the processing of time-based data in a modular, concurrent, distributed and extensible manner. C++, using YARP, ACE, Qt and MUSCLE on Linux, OSX, Windows and Solaris.

Allows creation of a distributed data processing system. Provided is a pluggable Daemon and a framework for writing custom plugins. Plugins can be changed and configured remotely and on the fly. Configurations with example plugins are provided.

An implementation of a high performance distributed storage and processing system for large amounts of structured data.