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...When creating a new rendering method in vuVolume it is possible to just concentrate on the actual algorithm and let the framework take care of the more administrative tasks.
P2P software for distributed computing. This is open source, scalable software for solving various tasks, which can be splitted between different computers.
EmGeeGen is a server-client information distribution system, tailored for use with the EmGee role playing system (though the theoretical platform should be useful for a variety of tasks).
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Java package containing architecture to distribute CPU intensive processing tasks across the internet. A generic client will be capable of running any task the server provides it, automatically updating the code it runs.
distX is a script which can be used to distribute CPU intensive tasks to a cluster of machines. For example, distX has been used for distributed encoding of ogg vorbis files.
QADPZ or Q2ADPZ ['kwäd "pE-'sE] is a C++ implementation of a system for
distributed computing. The system allows the management/use of the
computational power of idle computers in a network.
system can send computing tasks to these computers to
Netcluster is a framework for writing parallel programs. Its main objective is to utilize the idle time of computers on a LAN by distributing tasks amongst them. The package consists of a daemon running on all volunteering machines, and a library to provi
This project aims at developping a shared tasks computing system using Java, Jini and javaspaces. A master can split a big task in several tasks which will be executed by workers which have joined the federation using thier idle CPU time. A monitoring app
jvmShare is aiming to provide a server-client system that shares resources across the network. Since it is written in Java, clients shares their resources by providing their JVMs to the central server. The server will schedule tasks to these clients.
The goal of Gossamer is to provide a set of libraries & tools for distributed, fault tolerant, computing. This is done by breaking tasks up into small units which are then processed by seperate servers, which may reside locally or across a network.