Showing 415 open source projects for "parallel"

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  • 1

    neuranep

    Neural Network Engineering Platform

    A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. NeuraNEP emulates a distributed processing environment capable of handling millions of microthreads in parallel, for example running neural networks with millions of spiking cells.
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  • 2

    mobiQ Lab

    Create your own mobile test lab using popular opensource tools

    You can create your own mobile testing lab using some of the popular opensource mobile testing tools. A client server approach let you submit tests from anywhere within your network. You can run tests in parallel on multiple devices, access reports and configure devices. The comprehensive reference guide will help you understand MobiQ in depth. Go to Files to download it.
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  • 3
    Java OpenBase

    Java OpenBase

    Java all purpose Library

    A small library with some day to day problemsolving classes. Database, XML, Parallel, Math, String, ...
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  • 4

    instantFSM

    C++ inline state machine library

    instantFSM is a header-only C++ state machine library. Its goal is to make state machine declaration and use easy enough that it can be integrated into your projects painlessly. Have a look atp the wiki where you will find a tutorial, samples, and a cheatsheet to get accustomed with instantFSM. The only instantFSM header file is downloadable from the files section or you can check it out from the git repository.
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    SIEM | API Security | Log Management Software

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  • 5

    STMX

    High-performance transactional memory for Common Lisp

    ...Instead of traditional lock-based programming, one programs with atomic memory transactions: if a memory transaction returns normally it gets committed, if instead it signals an error (Lisp slang for throwing an exception) it is rolled back. Memory transactions can safely run in parallel in different threads, are re-executed from the beginning in case of conflicts or if consistent reads cannot be guaranteed, and effects of a transaction are not visible from other threads until it commits. STMX gives freedom from deadlocks, automatic rollback on failure, and it aims at resolving the tension between granularity and concurrency.
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  • 6
    LABjs

    LABjs

    Loading And Blocking JavaScript

    LABjs is a lightweight JavaScript loader focused on speeding up page performance by controlling how and when scripts download and execute. It provides an expressive API to load multiple files in parallel while guaranteeing execution order, so dependent scripts don’t break. By decoupling fetch from execute, it avoids the blocking behavior of traditional tags and helps reduce perceived load time. LABjs embraces a “load groups, then wait” model that makes dependency management clear without a separate build step. It’s designed to work across a wide range of browsers, including older ones, which is why it relies on robust feature detection and time-tested loading techniques. ...
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  • 7
    Perl System Test
    Perl System Test (PEST) is a test harness, written in Perl, for running processes on a distributed testbed via SSH. Test processes are defined in a simple config file for execution on remote hosts, enabling a tester to run tests in serially or in parallel. Processes are as non-blocking and un-buffered as possible. The harness redirects process output to an individual log for each process and logs process metadata. It captures the return code of each remote process and interprets 0 as pass and everything else as fail, enabling it to run tests written in any language. The harness depends on a standard testbed descriptor to facilitate portability across testbeds. ...
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  • 8

    CUSHAW2: Parallel Gapped Read Alignment

    One of the leading short-/long-read aligner to large genomes

    ...Furthermore, our aligner shows good parallel scalability with respect to the number of CPU threads.
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  • 9
    Intermediate Language Distributed Just-In-Time (ILDJIT) is a unified compilation framework for CIL bytecode. It is a parallel and easily extensible framework thanks to its internal structure composed by plugins.
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  • 10
    Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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  • 11
    Scenario

    Scenario

    Simple, neat and powerful tool for loading and managing JS scripts

    ...Load and manage scripts stored in arrays (code management). 3. Optimize coding flow by dynamically switching among best solution per case. 4. Run scenarios either distinctly or in parallel. 5. Keep easier track of bugs and errors when deploying. So, Scenario executes multiple views of your code or multiple scenarios of your code life-time on-demand.
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  • 12

    ParaBWT - parallel BWT construction

    a parallel and space-efficient Burrows-Wheeler transfrom constructor

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  • 13
    giServer

    giServer

    giServer the easy to use and extensible batch and integration server

    The giServer is an easy-to-use integration server for process automation and event-driven or scheduled execution of batch jobs. Instead of using complex XML configuration files an elaborate GUI for batch job management is included. Some possible usage scenarios are: - Automatic processing of incoming data files - Big Data applications - Process automation - Data Mining/Aggregation applications - Automatic Reporting - Processing and analysis of database records
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  • 14

    noSisyphos

    Embedded Rapid Application Development

    ...This system should be modular, which means, it's possible to add own components. The IDE (aka Tantalus) of the project must be able to handle also the self implemented components, without a recompile. It's possible to work parallel for the gui, the information are stored in XML, but for usage the data are transformed into a binary format, which decrease the code size and increase the speed of execution.
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  • 15
    PARUS

    PARUS

    Dataflow parallel programming language for clusters

    PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it.
    Downloads: 1 This Week
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  • 16

    C++11 ThreadPool

    An easy-to-use thread pool for C++11.

    An easy-to-use thread pool for C++11. With ThreadPool class for queueing free functions, and with parallel versions of std::for_each() and std::transform(). Configurable for header-only use or with a library. With many usage examples.
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  • 17
    Sisal is a unique parallel language that supports a clean, fully implicit parallelization model. The optimizing sisal compiler (sisalc) works on top of pthreads to give high performance on commodity SMP architectures.
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  • 18

    Distributed Multithread Apriori (DMTA)

    A parallel implementation using MPI and OpenMP to Apriori algorithm

    DMTA (Distributed Multithreaded Apriori) is a parallel implementation of Apriori algorithm, which exploits the parallelism at the level of threads and processes, seeking to perform load balancing among the cores. Was implemented in C++ language, using the parallelization libraries OpenMP and MPI. The algorithm was generated as a result of a project developed by André Camilo Bolina, under the guidance of teachers Marluce Rodrigues Pereira, Ahmed Ali Abdalla Esmin and Denilson Alves Pereira, in Department of Computer Science at Federal University of Lavras. ...
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  • 19
    LaunchMON is a software infrastructure that enables HPC run-time tools to co-locate tool daemons with a parallel job. Its API allows a tool to identify all the remote processes of a job and to scalably launch daemons into the relevant nodes.
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  • 20

    genericmock

    generic bits of useful code

    ...Everything is provided under BSD license so you don't need to worry about incorporating this into your commercial application. Bits of code: - redirecting standard streams (stdin, stdout, stderr) - getting access to a program's streams - run parallel tasks .... Visit the wiki for details: https://sourceforge.net/p/genericmock/wiki/Home/
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  • 21

    Drid

    Multi-Purpose Automation Grid

    Console-based tool that will allow for multiple types of automation testing to run in parallel. Written in Python
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  • 22
    A parallel system simulator kernel that support ultra-large scale computer system simulation.
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  • 23
    Route11

    Route11

    C++ flow-based metaprogramming library

    Route11 is a powerful C++ flow-based metaprogramming library that allows you to create and route complex dataflow systems at compile-time. Route11 uses Template Metaprogramming to construct complex "process systems" defined by static relationships between "process primitives". A process primitive is a generic host class that inherits a "process policy". The process policy defines the specific behavior of a process primitive. The general term: "process" can refer to either one of these...
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  • 24

    Fast Matrix for Java

    General purpose matrix utilities for Java in Parallel Computing

    Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors.
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  • 25

    PPSeq: Parallel NGS Analysis

    Parallel Processing for Next-Generation Sequencing (NGS) Analysis

    ...However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive parallel processing (MPP) systems.
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