Showing 28 open source projects for "cluster computing"

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  • 1
    MicroK8s

    MicroK8s

    Single-package Kubernetes for developers, IoT and edge

    Low-ops, minimal production Kubernetes, for devs, cloud, clusters, workstations, Edge and IoT. MicroK8s automatically chooses the best nodes for the Kubernetes datastore. When you lose a cluster database node, another node is promoted. No admin needed for your bulletproof edge. MicroK8s is small, with sensible defaults that ‘just work’. A quick install, easy upgrades and great security make it perfect for micro clouds and edge computing. As the publishers of MicroK8s, we deliver the world’s most efficient multi-cloud, multi-arch Kubernetes. ...
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  • 2
    Covalent workflow

    Covalent workflow

    Pythonic tool for running machine-learning/high performance workflows

    Covalent is a Pythonic workflow tool for computational scientists, AI/ML software engineers, and anyone who needs to run experiments on limited or expensive computing resources including quantum computers, HPC clusters, GPU arrays, and cloud services. Covalent enables a researcher to run computation tasks on an advanced hardware platform – such as a quantum computer or serverless HPC cluster – using a single line of code. Covalent overcomes computational and operational challenges inherent in AI/ML experimentation.
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  • 3
    AWS ParallelCluster Node

    AWS ParallelCluster Node

    Python package installed on the Amazon EC2 instances

    aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. 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. ...
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  • 4
    Matrix

    Matrix

    Multi-Agent daTa geneRation Infra and eXperimentation framework

    Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. ...
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  • 5
    Mars Framework

    Mars Framework

    Mars is a tensor-based unified framework for large-scale data

    Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments.
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  • 6

    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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  • 7
    Nebula-Python-SDK

    Nebula-Python-SDK

    A python SDK for managing Nebula container orchestrator

    ...Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. Designed to connect to devices that are spread around the globe Nebula is tolerant of network connection issues and will resync the device when it reconnects. ...
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  • 8
    Nebula docs

    Nebula docs

    Documentation repo of nebula orchestration system

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual appliances located at clients data centers, edge computing, and POS systems. Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of it's edge locations? ...
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  • 9
    Nebula worker

    Nebula worker

    The worker node manager container which manages nebula nodes

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices, appliances\virtual appliances located at clients data centers, and edge computing. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. Designed to connect to devices that are spread around the globe Nebula is tolerant of network connection issues and will resync the device when it reconnects. ...
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  • 10
    Nebula reporter

    Nebula reporter

    The optional reporter container which reads nebula reports from Kafka

    Nebula is an open source-distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking effect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe. Ever wandered how your going to push an update...
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  • 11
    Python/xarray tutorial

    Python/xarray tutorial

    Python/xarray tutorial for GEOS-Chem users

    If the page is loaded successfully, you should see a Jupyter notebook interface. Then, click on the first notebook to get started. Jupyter combines Python code, execution results, plots, custom texts, and even Latex formulas in a single page. Besides using the Jupyter program, you can also view the static notebook on GitHub (e.g the first notebook). Python is free & open-source so can be easily installed on any machines. To best way to get the scientific Python environment is using the Conda...
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  • 12
    EvalAI

    EvalAI

    Evaluating state of the art in AI

    ...We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. If the challenge needs extra computational power, challenge organizers can easily add their own cluster of worker nodes to process participant submissions while we take care of hosting the challenge, handling user submissions, and maintaining the leaderboard. EvalAI lets participants submit code for their agent in the form of docker images which are evaluated against test environments on the evaluation server. ...
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  • 13
    Provides auxiliary tools for the Monte Carlo particle transport code FLUKA (www.fluka.org).
    Downloads: 0 This Week
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  • 14
    TaskManager

    TaskManager

    TaskManager manages calculation jobs in a computer cluster environment

    TaskManager is an open source infrastructure software for distributing and managing calculation jobs in a Unix computer cluster environment. The TaskManager was designed to control the utilization of a set of hosts even if you are not the administrator of the system. The hosts are embedded in a Unix environment and the user's home directories are mounted on each host. The hosts may have different numbers of CPUs/cores and different kernels. Keep in mind that a user is able to log into each...
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  • 15

    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...
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  • 16
    PBS Cluster Viz
    PBS Cluster Viz is a project to display information useful to admins and users about a computing cluster managed by a PBS-compatible resource manager. Information includes load and job distribution. Interactive as well as static output is available.
    Downloads: 2 This Week
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  • 17
    cloudFlu
    HPC cloud computing for OpenFOAM (R) users
    Downloads: 0 This Week
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  • 18
    SnowFlock enables high performance computing on virtual machine (VM)-based cloud environments. In SnowFlock, a VM transparently becomes a cluster of VMs by cloning in sub-second time into multiple copies executing on different physical hosts.
    Downloads: 0 This Week
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  • 19
    KestrelHPC
    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.
    Downloads: 0 This Week
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  • 20
    balloon-foam
    was moved to http://sourceforge.net/projects/cloudflu
    Downloads: 0 This Week
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  • 21
    Service Sharing Facility
    This modular software package forms an integration point for Grid/Cloud/Cluster products. If provides several adapters which can easily be used to build complete Services/integrate products. It enables federation between multiple sites.
    Downloads: 0 This Week
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  • 22
    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
    Downloads: 0 This Week
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  • 23
    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.
    Downloads: 0 This Week
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  • 24
    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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  • 25
    sharq is a batch-queueing system that allows for multiple users to make effective use of a beowulf cluster. sharq allows for prioritization based on a user's funding, and also based on the size of the job. sharq is very light-weight and easy to learn.
    Downloads: 0 This Week
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