Showing 29 open source projects for "distributed computing"

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  • 1

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    Dual Porosity Stokes model implemented with FEniCS

    ...Douglas, X. Hu, B. Bai, X. He, M. Wei and J. Hou, "A Data Assimilation Enabled Model for Coupling Dual Porosity Flow with Free Flow," 2018 17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES), Wuxi, 2018, pp. 304-307. doi: 10.1109/DCABES.2018.00085 2. Hu X., Douglas C.C. (2019) An Implementation of a Coupled Dual-Porosity-Stokes Model with FEniCS. In: Rodrigues J. et al. (eds) Computational Science – ICCS 2019. ICCS 2019. Lecture Notes in Computer Science, vol 11539. ...
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  • 2
    ============================= THIS CODE IS DEPRECATED ============================= For updated information about MTSA visit: http://mtsa.dc.uba.ar
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  • 3

    ReorJS

    Distributed Computing with JavaScript

    Create your own distributed computer that can distributed javascript based applications to any computer with a web browser, headless browser or node.js installation. For more information and updates please see our website - http://reorjs.com.
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  • 4
    An easy-to-use simulator for decentralized distributed scheduling in Clusters, Grids, and Cloud ecosystem MaGate 2.0 is now available from github! https://github.com/huangye177/magate
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  • 5
    A parallel system simulator kernel that support ultra-large scale computer system simulation.
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  • 6
    FlowVR
    FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines
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  • 7
    ShoX is a scalable simulator for wireless networks written in Java. It is easy to install, configure and use, so that reliable and expressive scientific results can be gathered in a short time. Documentation: http://sourceforge.net/apps/mediawiki/shox
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  • 8
    DReAMSim

    DReAMSim

    Dynamic Re-configurable Autonomous Many-task Simulator

    DReAMSim provides a simple simulation framework for modeling homogeneous and/or heterogeneous (re)-configurable processing elements in a large-scale distributed environment. In particular, DReAMSim enables users to model task scheduling techniques at a preliminary design stage in order to investigate their performance potential. The simulation framework makes it easy to extract various performance and resource utilization related statistics to study the behavior of different task...
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  • 9
    DASM is a new simple platform which helps programmer to implement and evaluate any distributed algorithm. Programmer can implement his/her distributed algorithm using DASM primitives and monitors the results in diagrams during execution.
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  • 10
    Java based multi-agent platform built on an organizational model (agent, group, role). MadKit provides general agent facilities (lifecycle management, message passing, distribution, ...), and allows high heterogeneity in agents.
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  • 11
    breve is a free, open-source 3D multi-agent simulation package designed for simulating decentralized systems and artificial life.
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  • 12
    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
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  • 13
    SimIS presents an agent-based simulation environment from multiagent research to simulate Internet-of-Services systems. The simulation environment bases on Repast Simphony 1.2 (http://repast.sourceforge.net/).
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  • 14
    Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
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  • 15
    Pydusa is a package for parallel programming using Python. It contains a module for doing MPI programming in Python. We have added parallel solver packages such as Parallel SuperLU for solving sparse linear systems.
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  • 16
    The CodeTime platform covers every aspect of parallel software from authoring, through distribution, to run-time. Its goals are: high programmer productivity; write once, run high performance anywhere; and wide acceptance.
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  • 17
    This project about providing run-time support for developing Decentralized Autonomic Computing systems (Eclipse Innovation Grand). Currently the project contains a automatic guided vehicle (AGV) simulator and an editor and visualisation as eclipse plugin
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  • 18
    hive provides a component-oriented plugin-based framework and a GUI system for distributed computing. Please look at the project website for more detailed informations.
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  • 19
    N-sim is a framework for studying and developing wireless sensor networks. It emulates the computation of sensor platforms, simulates the wireless communications, and allows plug-in models for source detection simulation. Intended for cluster computing.
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  • 20
    Poor Man's HPC is a framework that allows distributing and running code on a server farm. pmHPC is a scaled down and simplified version of distributed computing projects such as SETI, so is a perfect fit for enthusiasts and universities.
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  • 21
    PeerKit is a tool for rapidly creating new peer-to-peer programs, and designing and evaluating new peer-to-peer topologies.
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  • 22
    Mupisim is a simulator for distributed, mobile systems. Its primary purpose is the study of mobile processes (e.g. mobile agents) and their communication mechanisms. It may also be used to evaluate the efficiency of a given process migration scheme.
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  • 23
    This project aims to modify Parallel Virtual Machine (PVM) to use benefits of RDMA-capable network interconnects, commonly used in HPC clusters.
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  • 24
    GridSweeper makes it easy to perform batch runs of scientific simulation programs on computational grids/distributed resource management systems.
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  • 25
    RangeSim is a collection of classes for simulating distributed protocols for range search on P2P (peer-to-peer) network environments. It is based upon the PeerSim simulator, which offers easy configuration, extendability and high performance.
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