Showing 1481 open source projects for "parallel"

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  • 1

    WFEF .NET Bindings

    .NET bindings for the WFEF project.

    Home Browse Open Source WFIO .NET Bindings WFIO .NET Bindings .NET bindings for WFIO Status: Pre-Alpha Brought to you by: thylordroot Add a Review Downloads: 0 This Week Last Update: 2023-01-25 Browse Code Get Updates Share This Windows Mac Linux BSD ChromeOS Summary Reviews Support Code This subproject contains a parallel implementation effort for the .NET Virtual Machine. It allows for you to use the WFEF interface in your .NET applications and will include a translation layer so that you can talk to the native WFEF libraries. This subproject exists partially to overcome the 8.3 file naming convention that WFEF itself is limited to.
    Downloads: 0 This Week
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  • 2
    Sqlite Index Blaster

    Sqlite Index Blaster

    Create huge Sqlite indexes at breakneck speeds

    SQLite Blaster is an advanced SQLite extension that enhances database performance by enabling multi-threading, data compression, and memory optimizations. It is designed for applications that require fast local storage with improved query efficiency.
    Downloads: 0 This Week
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  • 3
    GPT-NeoX

    GPT-NeoX

    Implementation of model parallel autoregressive transformers on GPUs

    This repository records EleutherAI's library for training large-scale language models on GPUs. Our current framework is based on NVIDIA's Megatron Language Model and has been augmented with techniques from DeepSpeed as well as some novel optimizations. We aim to make this repo a centralized and accessible place to gather techniques for training large-scale autoregressive language models, and accelerate research into large-scale training. For those looking for a TPU-centric codebase, we...
    Downloads: 2 This Week
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  • 4
    ElegantRL

    ElegantRL

    Massively Parallel Deep Reinforcement Learning

    ElegantRL is an efficient and flexible deep reinforcement learning framework designed for researchers and practitioners. It focuses on simplicity, high performance, and supporting advanced RL algorithms.
    Downloads: 3 This Week
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  • 5

    o'scopepy

    Oscilloscope using PC sound card and Python 3

    Version 6 uses a programming paradigm based on workcells which communicate with each other using text based signals. This creates a parallel programming environment with autonomous virtual machines communicating over a peer to peer network. The workcells are instantiated anonymously, therefore all methods and variables are completely private. Tkinter is used for both GUIs and for creating a second event loop used for synchronizing workcell to workcell communication.
    Downloads: 0 This Week
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  • 6
    Mars Framework

    Mars Framework

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

    ...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. Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. Mars is particularly useful for workloads that exceed the memory capacity of a single machine or require high levels of parallel processing.
    Downloads: 9 This Week
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  • 7
    Scrapyd

    Scrapyd

    A service daemon to run Scrapy spiders

    ...Scrapyd is an application (typically run as a daemon) that listens to requests for spiders to run and spawns a process for each one. Scrapyd also runs multiple processes in parallel, allocating them in a fixed number of slots given by the max_proc and max_proc_per_cpu options, starting as many processes as possible to handle the load.
    Downloads: 1 This Week
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  • 8
    FairScale

    FairScale

    PyTorch extensions for high performance and large scale training

    FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. ...
    Downloads: 10 This Week
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  • 9
    TextBox

    TextBox

    A text generation library with pre-trained language models github.com

    ...From a model perspective, we incorporate 47 pre-trained language models/modules covering the categories of general, translation, Chinese, dialogue, controllable, distilled, prompting, and lightweight models (modules). From a training perspective, we support 4 pre-training objectives and 4 efficient and robust training strategies, such as distributed data parallel and efficient generation. Compared with the previous version of TextBox, this extension mainly focuses on building a unified, flexible, and standardized framework for better supporting PLM-based text generation models.
    Downloads: 2 This Week
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  • 10
    OpenXR-Hpp project

    OpenXR-Hpp project

    Open-Source OpenXR C++ language projection

    ...If you just want to generate the headers, run ./generate-openxr-hpp.sh or ./generate-openxr-hpp.ps1. If your OpenXR-SDK-Source (or internal gitlab) repo isn't in a directory named that parallel to this one, you can set OPENXR_REPO environment variable before running. Requires clang-format, preferably 6.0. To build this project, you must have OpenXR-SDK-Source cloned in a peer directory of this one.
    Downloads: 0 This Week
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  • 11
    OK

    OK

    Welcome to the future of programming languages

    ...The language emphasises readability and pushing logic out into functions so cases remain simple. It includes concurrency via a map function that executes callbacks in parallel. The project is illustrative of Duffield’s vision: code should feel “magical to write” by removing what is unnecessary.
    Downloads: 0 This Week
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  • 12

    WFIO .NET Bindings

    .NET bindings for WFIO

    This subproject contains a parallel implementation effort for the .NET Virtual Machine. It allows for you to use the WFIO interface in your .NET applications and will include a translation layer so that you can talk to the native WFIO libraries. This subproject exists partially to overcome the 8.3 file naming convention that WFIO itself is limited to.
    Downloads: 0 This Week
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  • 13
    FLoops.jl

    FLoops.jl

    Fast sequential, threaded, and distributed for-loops for Julia

    Fast sequential, threaded, and distributed for-loops for Julia, fold for humans.FLoops.jl provides a macro @floop. It can be used to generate a fast generic sequential and parallel iteration over complex collections. Furthermore, the loop written in @floop can be executed with any compatible executors. See FoldsThreads.jl for various thread-based executors that are optimized for different kinds of loops. FoldsCUDA.jl provides an executor for GPU. FLoops.jl also provides a simple distributed executor.
    Downloads: 10 This Week
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  • 14

    webotron

    Using industrial automation techniques for creating web scraping tools

    Industry uses machines that can easily maim or kill their operators and is also used in very adverse environments. In spite of this, production quality must be close to perfect without reliance on operator skill or attentiveness. Control programs must be robust, yet simple enough to be understood and maintained by non programmer skilled trades like electricians . The main programming model is the PLC which implements double buffering and an event loop. The most advanced production model...
    Downloads: 1 This Week
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  • 15

    ImageJ2x

    Java Image Processing Program

    ...The program supports simultaneous that number of windows (images), limited only by available memory. It is multithreaded, so that time-consuming operations such as reading lists in parallel with other operations are performed. It can calculate area and pixel value statistics of user-defined selection. It can measure distances and angles. It can record density histograms and line profiles. It supports standard image processing functions such as contrast manipulation, sharpening, smoothing, edge detection and filtering it through all kinds of geometric transformations such as Zoom in / out and rotation. ...
    Downloads: 3 This Week
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  • 16
    ThreadsX.jl

    ThreadsX.jl

    Parallelized Base functions

    ...The public API functions of ThreadsX expect that the data structure and function(s) passed as argument are "thread-friendly" in the sense that operating on distinct elements in the given container from multiple tasks in parallel is safe. For example, ThreadsX.sum(f, array) assumes that executing f(::eltype(array)) and accessing elements as in array[i] from multiple threads is safe.
    Downloads: 10 This Week
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  • 17
    OpenProject Community Ed Virtual Machine

    OpenProject Community Ed Virtual Machine

    Free & Open Source - Project / Task / Time & Team Management Software

    Please click the Files Tab above to get all the related files of this system. ( Right Click Each File, to Open Them in New Tab, one by one, to download them all ) This is a Complete Virtual Machine, with Web Based OpenProject Software, for all sorts of Project Management / Task Management / Time Management & Team Management Activities. This Web Based Software can be operated by all Teams, in parallel, on your local and trusted work network. Have a look at the Video below for details. Refer Wiki for more instructions.
    Downloads: 3 This Week
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  • 18

    SkePi

    Data parallel and stream parallel skeletons implemented in erlang.

    Downloads: 0 This Week
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  • 19
    Vue Query

    Vue Query

    Hooks for fetching, caching and updating asynchronous data in Vue

    ...Transport/protocol/backend agnostic data fetching (REST, GraphQL, promises, whatever!) Auto Caching + Refetching (stale-while-revalidate, Window Refocus, Polling/Realtime) Parallel + Dependent Queries. Mutations + Reactive Query Refetching. Multi-layer Cache + Automatic Garbage Collection. Paginated + Cursor-based Queries. Load-More + Infinite Scroll Queries w/ Scroll Recovery. Request Cancellation. (experimental) Suspense + Fetch-As-You-Render Query Prefetching (experimental) SSR support. If you need to update options on your query dynamically, make sure to pass them as reactive variables.
    Downloads: 0 This Week
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  • 20

    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: 14 This Week
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  • 21
    Elephas

    Elephas

    Distributed Deep learning with Keras & Spark

    ...Elephas intends to keep the simplicity and high usability of Keras, thereby allowing for fast prototyping of distributed models, which can be run on massive data sets. Elephas implements a class of data-parallel algorithms on top of Keras, using Spark's RDDs and data frames. Keras Models are initialized on the driver, then serialized and shipped to workers, alongside with data and broadcasted model parameters. Spark workers deserialize the model, train their chunk of data and send their gradients back to the driver. The "master" model on the driver is updated by an optimizer, which takes gradients either synchronously or asynchronously. ...
    Downloads: 0 This Week
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  • 22
    eCScope

    eCScope

    Oscilloscope like software for measure data with INA260 chips

    Freeware software for Raspberry PI 4B+ using GPIO and I2C connections with a hardware board with a 30 cm I2C cable (seed or qwicc) or 2m (proprietary eComet). Hardware will be available soon at http://electromaker.io. main features: max 150s measurement time, load measurement data to CSV file, measurement calibration, parallel measurement of 4 values, scale zoom in out, and move at X and Y axes For news and updates see twitter page.
    Downloads: 0 This Week
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  • 23
    Buck

    Buck

    Build system that encourages the creation of small, reusable modules

    ...It encourages the creation of small, reusable modules consisting of code and resources, and supports a variety of languages on many platforms. Buck builds independent artifacts in parallel to take advantage of multiple cores on your machine. Further, it reduces incremental build times by keeping track of unchanged modules so that the minimal set of modules is rebuilt. Buck only uses the declared inputs, which means everybody gets the same results. Buck looks at the contents of your inputs, not their timestamps to figure out what needs to be built. ...
    Downloads: 2 This Week
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  • 24
    rayshade-mathematica

    rayshade-mathematica

    rayshade and POV for Mathematica Export + view

    Beautifully Render* your Graphic3D and Shown or Manipulate right in the Front End (without Export to, ie 3DStudio Art Renderer, et al). For use with Mathematica 4.0 - 13.1. Makes file.ray or .pov that will look much like image in notebook except rendered. Works easily/automatically with many Graphics3D (and some Graphic) as well. However graphics in 13.1 is too big to comment on: many will work many not. Has many options to fix renders that aren't so auto. Now very portable...
    Downloads: 2 This Week
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  • 25
    Fairseq

    Fairseq

    Facebook AI Research Sequence-to-Sequence Toolkit written in Python

    Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. ...
    Downloads: 1 This Week
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