Search Results for "parallel"
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Showing 18 open source projects for "parallel"
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Cloud tools for web scraping and data extractionAutomate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient. An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous... -
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Apache brpc
Industrial-grade RPC framework used throughout Baidu
Apache brpc is an industrial-grade RPC framework for building reliable and high-performance services. Apache brpc (incubating) is an effort undergoing Incubation at The Apache Software Foundation (ASF), sponsored by the Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not... -
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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OpenHCPP
A Directive-Based Heterogeneous Parallel Programming Framework
OpenHCPP is a high-level directive-based parallel programming framework. -
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ProgramNet Designer
C++ cross plattform functional block programming
With the help of the ProgramNet the user can develop plug-ins(called units) which can be connected with other units forming a net. The net has a form of a flow diagram. The resulted net can be executed in the ProgramNet for testing purposes or independently in the target platform as a final release. In order to execute a net the ProgramNet uses the kernel. The kernel executes automatically each unit in a separate thread and manages the data exchange between the units. -
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The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
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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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MapReduce++ is a project for implementation of parallel algorithms. It has currently two C++ implementations of the MapReduce abstraction: the MapMP library (multiprocessors) and the MaPI framework (multicomputers).
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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. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons.
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Ash C++ Template Library (AshTL)
Hashing and spatial concurrency library.
AshTL aims to provide a complete framework for dealing with spatial data in an efficient, parallel manner. As such, we primarily provide container classes and data types relating to 2D and 3D coordinate grids. AshTL is currently in alpha development (some features may not work correctly, and interfaces are likely to change). While in alpha and beta development, AshTL is licensed under AGPL v3+. Stable releases will include an exception so that AshTL itself will always be AGPL, but will not force code that uses it to be. -
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Project provides a set of concurrent building blocks (Java & C/C++) that can be used to develop parallel/multi-threaded applications. Components are grouped into 4 categories: 1.Data Structures 2. Parallel Patterns 3.Parallel functions 4.Atomics and STM
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A framework for creating automatically-assembling trees of objects. Intended to parallel another interface as strictly a data I/O structure (e.g. file load/save in parallel with a GUI displaying it.) Adaptable to any hierachical data format.
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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
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QuickMP (Quick Multi-Processing) is a simple cross-platform C++ API for generating parallel for loops in shared-memory programs, similar to OpenMP. It provides automatic scalable performance based on the number of available processors.
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Dynamic Probe Class Library (DPCL) is an object based C++ class library that provides the necessary infrastructure to allow tool developers and sophisticated tool users to build parallel and serial tools through technology called dynamic instrumentation.
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FastPara is a C++ programming framework for writing data-parallel applications in cluster environments. It builds the code framework for the data-parallel applications based on their data distribution declaration.
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laetus-framework
C++ Parallel Framework
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