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Showing 9 open source projects for "python distributed list"
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slurm-roll
Slurm Resource Manager for Rocks Clusters
Slurm is a replacement for other resource management software and schedulers like gridengine or torque. The slurm roll integrates very well into a rocks clusters installation. In the folder addons, there are a lot of useful rolls for rocks clusters 6.1 and 6.2. These rolls do not depend on slurm. Please see Discussion for further information and support -
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Ganglia
Scalable, distributed monitoring system for high-performance computing
Ganglia is a scalable distributed monitoring system for high-performance computing systems such as clusters and Grids. It is based on a hierarchical design targeted at federations of clusters. Supports clusters up to 2000 nodes in size. -
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XtreemOS project aims at building a Linux-based operating system to support virtual organizations for next generation Grids.
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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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SSS-OSCAR is an integrated release of the SciDAC:Scalable System Software (SSS) suite using the OSCAR cluster installation framework. The SSS project seeks to provide a standard interface for effective management and utilization of terascale systems.
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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.
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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.
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Zeus Grid is a Grid Computing environment usefull to run systems in heterogenous machines at same time. In this first step, it will only compile, run and collect application results and file storage.
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This package provides Python bindings to the OpenPBS C API. All functions of the OpenPBS C library can be accessed in Python through the use of this package. We provide extensive documentation on the usage and lots of examples.
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