Open Source Python Distributed Computing Software - Page 3
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Python Distributed Computing Software
View 395 business solutionsBrowse free open source Python Distributed Computing Software and projects below. Use the toggles on the left to filter open source Python Distributed Computing Software by OS, license, language, programming language, and project status.
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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Network Management Software and Tools for Businesses and Organizations | Auvik NetworksReduce IT headaches and save time with a proven solution for automated network discovery, documentation, and performance monitoring. Choose Auvik because you'll see value in minutes, and stay with us to improve your IT for years to come.
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Freenomalism is a free, community based fork of the Enomalism web-based virtual infrastructure/cloud computing platform. The dashboard can help with issues including deployment planning, load balancing, migration, configuration management, and capacity.
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GRIDportal is a web-based application portal for High Performance Computing. It facilitates easier access to GRID applications through a comfortable web interface. It was designed for use with NorduGrid, but is very generic by nature.
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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).
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Ganglia Job Monarch
Batch system monitoring and archiving
Job Monarch is an addon to the Ganglia Monitoring System that provides batch job monitoring and archiving plus a graphical overview of clusters and assorted batch systems. Fully supported batch system: Torque, PBS and SLURM. Experimental: LSF, SGE -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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The goal of this project is to make possible to access Progress database from any external program that can use sockets. The server (broker and agents) are written in Progress 4GL and made use of sockets capabilities of Progress V9.
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A novel Grid System which is Python based and Cell powered. By extending Namespace into GridSpace, any objects are accesable throughout the Grid. And the codes are distributed executed and be JIT compiled into Cell SPE instructions automatically.
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Gug is an Grid Computing environment based on the Service Oriented Architecure (SOA). It provides a set of web services to build simple grid system using different resources from supercomputers to desktop PCs.
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HaDeS is a deployment system for large scale installation. Designed to be scalable with respect the number of nodes and agnostic with respect the OS deployed, it has a Web Service interface that allows an easy integration in complex SOA systems.
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IDEAIS is a enteprise service bus integration plataform for software development tools and activities. It uses Web Services (SOAP/HTTP) to integrate best of the breed software development tools (Eclipse, Subversion, Bugzilla, dotProject, vTiger).
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SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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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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iROS is a meta-operating system for technology-rich "interactive rooms". The core components (Event Heap, DataHeap, iCrafter) provide communication, data storage, and service management for an iRoom.
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JFIPA is intended to be a scalable, easy-to-deploy router and parser of messages between agents using the FIPA Agent Communication Language represented as XML
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Java Hibernation Package is an experimental implementation of Java thread serialization mechanism based on the Java Platform Debugger Architecture (JPDA). It is designed to support serialization of synchronizing multiple threads.
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The Job Jar is a simple batch queuing system for Unix. Its main distinguishing feature is that there is no central daemon. Instead, an arbitrary set of workers cooperatively claim jobs from a central directory. A job is any Unix executable file.
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Python based framework for multi-agent distributed applications. Provides XML-based network messaging through an easy to use event architecture.
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KestrelHPC is a software developed to make life easier to the people that want to have a Diskless Cluster. This Cluster is Multi-User and it has got many tools to configure your cluster. This software can be installed in a Debian or Ubuntu.
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LemFS is a distributed, redundant data storage system, designed to utilize unused disk space on networked work stations and desktop PCs.
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A lightweight, platform-neutral framework for decoupled communications. Development has moved to http://github.com/lwes/
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LinuxTuples is an open-source implementation of David Gelernter's idea of a tuple space, designed to run on a networked cluster of Linux machines.
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This Project aims to create a Linux Distribution focused on the IBM zOS system, it includes a set of Mainframe tools, based all in Linux Kernel modules, C and Python. -MainFrame Access Methods -ISPF menus -REXX scripting -RACF security -JCL Batch Job
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A transparent network messaging system for offloading computations to other possibly more capable machines when they are available. The intended use of the system is for when the results of a computation aren't needed immediately.
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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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MPY is an MPI implementation for Python using MPICH (or any other MPI implementation). MPY also provides helper functions for ease of programming, and a simple plug-in interface.
