Showing 4 open source projects for "compute"

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  • 1
    AWS ParallelCluster Node

    AWS ParallelCluster Node

    Python package installed on the Amazon EC2 instances

    ...AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. AWS ParallelCluster facilitates both quick start proof of concepts (POCs) and production deployments. You can build higher-level workflows, such as a Genomics portal that automates the entire DNA sequencing workflow, on top of AWS ParallelCluster.
    Downloads: 0 This Week
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  • 2

    dispy

    Distributed and Parallel Computing 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.
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    Downloads: 8 This Week
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  • 3
    ClusterShell
    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.
    Downloads: 5 This Week
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  • 4

    RainforestCluster

    Dynamically manage Amazon EC2 clusters

    RainforestCluster is an Amazon EC2 python program that manages and load-balances dynamic clusters to allow for maximum workflow flexibility and speed at minimal cost. It enables one to quickly and cheaply create dynamic compute clusters in the cloud, which can then run computational pipelines generically. It is also able to optimize the use of spot instances - idle computers in Amazon's cloud that are available at drastically reduced cost (5x-10x cheaper) - but can be terminated at any moment if capacity drops or the bid price rises. It also provides pre-installed features such as GlusterFS distributed filesystems, ThunderstormDistributor queuing system, RAID 0 /scratch, password-less ssh, and automatic cluster management, for ease of use and maximum processing speed for computational tools. ...
    Downloads: 0 This Week
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