Search Results for "parallel-sudoku-solver"

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 parallel computing 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. The compute nodes boot by PXE, using the frontend node as the server...

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.

PRLL HAS MOVED TO GITHUB https://github.com/exzombie/prll A utility for parallelizing the execution of shell functions. Focuses on convenience in interactive use, but is just as usable in shell scripts. Put your multicore to good use, or combine prll with ssh to create an instant cluster.

Manage node sets, node groups and execute commands on cluster nodes in parallel. Provides an event-based Python library to improve administration of large compute clusters or server farms. Command line tools: clush and nodeset included.

Genetic Programming Classifier is a distributed evolutionary data classification program. It uses the ensemble method implemented under a parallel co-evolutionary Genetic Programming technique.

Postgres-XC is a write-scalable synchronous multi-master PostgreSQL cluster with the following features. 1) Both read and write scalability. 2) Configured with more than one server. 3) Complete global transaction and visibility management.

Hrothgar is a parallel minimizer and Markov Chain Monte Carlo generator by Andisheh Mahdavi of San Francisco State University. It has been used to solve optimization problems in astrophysics (galaxy cluster mass profiles) as well as in experimental particle physics (hadronic tau decays). It is probably adaptable enough to be applied to your merit function if you can write it in C.

PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it.

LaunchMON is a software infrastructure that enables HPC run-time tools to co-locate tool daemons with a parallel job. Its API allows a tool to identify all the remote processes of a job and to scalably launch daemons into the relevant nodes.

PuSSH is Pythonic, Ubiquitous SSH, a Python wrapper/script that runs commands in parallel on clusters/ranges of linux/unix machines via SSH, ideally where SSH is configured to use Kerberos, RSA/DSA keys, or ssh-agent as to avoid password authentication.

GXP is a parallel/distributed shell, plus a parallel task execution engine that runs your Makefile in parallel on distributed machines. Very easy to install (no need to compile. install it on YOUR machine and use it on ALL machines).

Cbench is intended as a relatively straightforward toolbox of tests, benchmarks, applications, utilities, and framework to hold them together with the goal to facilitate scalable testing, benchmarking, and analysis of a Linux parallel compute cluster.

Open ActiveWrl is a software development toolkit based on a generic software development approach that allows the implementation of parallel immersive VRML/X3D browsers on heterogenous cluster systems. It supports systems running Win NT/2000/XP and Linux

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.

Cleo is written on perl5 and works on Linux and hopely on most UNIXes. This is the batch system for computational clusters, which supports possibly most parallel envinronments.

EPSILON is a powerful Open Source wavelet image compressor. The project is aimed on parallel and robust image processing.

Parallel Secure Shell (pssh) is an ssh wrapper that makes it easy to execute commands on multiple remote systems in parallel. pssh accepts lists of host names, system attributes and exclusions.

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.

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.

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.

pdo allows users to run SSH commands on multiple remote hosts in parallel, or run commands (such as rsync etc.) locally against multiple remote hosts in parallel.

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