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PelicanHPC is an iso-hybrid (CD or USB) image that let's you set up a high performance computing cluster in a few minutes. A Pelican cluster allows you to do parallelcomputing using MPI. You can run Pelican on a single multiple core machine to use all cores to solve a problem, or you can network multiple computers together to make a cluster. The frontend node (either a real computer or a virtual machine) boots from the image.
Distributed and ParallelComputing with/for Python.
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.
PyDSH is a remote administration tool, consisting of pydsh and pydcp. Pydsh allows you to run a command on multiple hosts in parallel over RSH, SSH or Telnet, OR manage your SSH public keys. The pydcp command allows copying files to/from multiple hosts.
GridSim allows modeling and simulation of entities in parallel and distributed computing systems such as users, applications, resources, and resource brokers/schedulers for design and evaluation of scheduling algorithms. http://www.gridbus.org/gridsim
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.
BSPonMPI is an implementation of the BSPlib standard on top of MPI. Both MPI and BSPlib are API's of communication routines meant for parallelcomputing, but BSPlib is easier to learn and its performance easier to predict.
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.
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
PPIV is a parallel software application used in Particle Image Velocimetry (PIV) analysis. The software will compute the vector field for one image pair or multiple image pairs. PPIV can run on a single desktop machine or in a cluster environment.
A data parallel scientific programming model. Compiles efficiently to different platforms like distributed memory (MPI), shared memory multi-processor (pthreads), Cell BE processor, Nvidia Cuda, SIMD vectorization (SSE, Altivec), and sequential C++ code.
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.
SimParEx executes a program(command) on many computers (farm) in parallel and collects the results (task farming). Major features: minimal requirements (TCP, SSH, Perl), flexible task definition, web interface.
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.
The software provides a means to form a simple Java cluster. It can be also viewed
as a parallelcomputing library in Java. The project is based on the following
<a href='http://www-106.ibm.com/developerworks/java/library/j-super.html'>article</a>
This project is setup to maintain a set of Javaparty codes.
This includes Javaparty benchmarks and applications.
Javaparty (http://www.ipd.uka.de/JavaParty/) is a Java extension for easy and efficient parallel programming.
It does so by extending the
Web Textual eXtraction Tools C++ Parallel web crawler, noun phrase idenification, Multi-lingual Part of Speech Tagging, Tarjan's Algorithm, Co-RelationShip Mappings...
MassiveJava is a Java-based environment for parallel programming. Lithium is able to execute the parallel application using a cluster or a network of workstations. A user is able to program a parallel application without take in account problem like sche
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.
Provide a common portal platform to join Internet Service Providers users into a community, both including personalization using "portlets" as the building blocks of .NET type applications and using a Parallel Portal Engine to overcome such demanding use