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This project involves implementing simulations of Enigma machines and the Turing bombe on various parallel-computing systems including multi-processor PCs, Linux clusters, and modern enhanced graphic cards.
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.
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.
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.
ClusterIt is a collection of clustering tools to allow simple administration of groups of UNIX machines. It can also be used to facilitate parallel shell scripting, and compiling.
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.
The underlayer is a symmetric decentralized parallelcomputing and load balancing framework, providing c, perl and java APIs for distributed job management.
It is an implementation of Tuple-Space by using MPI library. Tuple-space is a logically shared memory in many parallelcomputing. It provides the appearance of a shared memory but do not require on underlying physical shared memory.
ProteinFinder - a C language parallelcomputing engine for tandem protein mass spectrometry database search. ProteinFinder is interfaced with MySQL relational database MassSpec that hosts the experimental data, predicted databases, and search results.
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.
Maui Scheduler is an advanced reservation HPC parallel batch scheduler for use with Linux and BSD clusters. Maui provides a complete scientific scheduling solution, supporting running custom parallel and MPI jobs over Myrinet and ethernet.
Simulator of massively parallel computer cluster with minimal nodes.
Loosely based around available information regarding Chuck Moore's c18/25x core/chip designs.
Machine Forth based MISC NOSC nodes, mesh interconnection.
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
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
In many parallel scientific applications the process of grid generation, decomposition, message passing, and performance measurements are of similar stucture. The projects intention is to develop a generic function library that will contain all these.
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
TOP-C is a library for easily writing parallel applications for both distributed and shared memory architectures. It hides the details of parallel programming, and presents the application programmer with a simple task-oriented interface.
The BCR flavor of Cooperative Data Sharing (CDS) is a scalable, portable, flexible C-based API and daemon for initiating and communicating between processes/threads in uniprocessor and multiprocessor (e.g. distributed, SMP, and parallel) platforms.