Search Results for "parallel computing datamaning" - Page 2
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Showing 96 open source projects for "parallel computing datamaning"
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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.
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SECTOR: A Distributed Data Storage and Processing Platform
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Project provides a set of concurrent building blocks (Java & C/C++) that can be used to develop parallel/multi-threaded applications. Components are grouped into 4 categories: 1.Data Structures 2. Parallel Patterns 3.Parallel functions 4.Atomics and STM
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Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
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A scripting language and reference implementation to allow command line tools to be chained into complex parallel workflows.
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Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
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Microbase is a Grid infrastructure for deploying massively parallel applications. Our notification-driven task scheduler supports the enactment of complex data processing workflows, such as those commonly used in bioinformatics.
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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
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HadoopDB is a hybrid of parallel database and MapReduce technologies. It approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce systems.
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Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programming language. Primarily targeted at evolutionary computing and similar master-slave configurations.
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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.
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SimKernel controls parameter scans and iterations for any given C++ code / scientific simulation. Parameters, iteration ranges, settings and dependencies are specified in Mathematica syntax. Parallel processing of parameter scanning via MPI.
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Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru
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Roomy is a programming language extension for writing parallel disk-based applications. All details of parallelism and disk I/O are hidden within the Roomy library.
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PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
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BSPonMPI is an implementation of the BSPlib standard on top of MPI. Both MPI and BSPlib are API's of communication routines meant for parallel computing, but BSPlib is easier to learn and its performance easier to predict.
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Parallelizable is a tiny framework in complement for java.util.conccurent api. Parallelizable is an abstract class to extend for making asynchronous parallel execution on a synchronous task. Very usefull if task often calls a very long process.
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Numerical package Parallel EXECution. Using a numerical package like Octave, 'npexec' distribute computation of a math formula among various network elements, collecting result automatically. ->y=npexec('fft(x.^m)', 'm=-8:8','x=ARG');
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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.
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DKU is an embedded parallel language, or "piggy-back" language that uses function calls to invoke the language's execution model. It tunes task-size to the hardware while hiding hardware details for high performance portability of parallel code.
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The Application Agent (AA) is a software providing the platform and mechanism for the distributed/parallel applications to interact and negotiate with the underlying grid resource infrastructure such as Condor and SGE on one-to-one and dynamic basis.
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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.
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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.
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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.
