Showing 128 open source projects for "parallel-sudoku-solver"

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  • 1
    RecNN

    RecNN

    Reinforced Recommendation toolkit built around pytorch 1.7

    This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like.
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  • 2
    Kotlin Coroutines for Retrofit

    Kotlin Coroutines for Retrofit

    Kotlin Coroutines await() extension for Retrofit Call

    This is a small library that provides the Kotlin Coroutines suspending extension Call.await() for Retrofit 2. Based on kotlinx.coroutines implementation. Kotlin 1.2 and experimental coroutines are not supported anymore, but you can use version 0.13.0 for old projects.
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  • 3
    ComplexEventExtraction

    ComplexEventExtraction

    Expression pattern collection of Chinese compound event extraction

    ComplexEventExtraction is a Chinese NLP project for identifying relationships between events expressed in compound sentences. It defines patterns for causal, conditional, sequential, contrastive, and parallel event structures. The system uses explicit connective words and phrase combinations to split text into linked event pairs. Extracted results can support event graphs that represent how situations develop, conflict, or depend on one another. The repository catalogs hundreds of linguistic patterns and demonstrates them on a large Chinese news corpus. ...
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  • 4
    Sudoku Game Solver Generator

    Sudoku Game Solver Generator

    Standalone Complete Sudoku puzzle Game Solver Generator for Windows

    ...The Sudoku generation algorithm used by this app is my ultimate proud. Primarily it was based on a Deep Neural Network. But I analyzed more than 100 scientific publications on Sudoku generation problem and have reduced the Deep Neural Network to a relatively simple and very elegant deterministic algorithm that works pretty fast. As a result, the app can generate Sudoku fields in 7 difficulty levels from 'Yellow Belt' to 'Sudoku Game Jedi Master'.
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  • 5
    Quasar

    Quasar

    Fibers, channels and actors for the JVM

    Quasar is a library that provides high-performance lightweight threads, Go-like channels, Erlang-like actors, and other asynchronous programming tools for Java and Kotlin. Quasar is developed by Parallel Universe and released as free software, dual-licensed under the Eclipse Public License and the GNU Lesser General Public License. Quasar fibers rely on bytecode instrumentation. This can be done at classloading time via a Java Agent, or at compilation time with an Ant task. Quasar’s lightweight thread implementation relies on bytecode instrumentation. ...
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  • 6
    FastFlow: programming multi-core

    FastFlow: programming multi-core

    Pattern-based multi/many-core parallel programming framework

    FastFlow is a C/C++ programming framework supporting the development of pattern-based parallel programs on multi/many-core, GPUs and distributed platforms. FastFlow run-time is built upon non-blocking threads and lock-free queues. Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on commodity multi-core. ...
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  • 7
    Phaser 3 Webpack Loader

    Phaser 3 Webpack Loader

    Asset loader for Phaser + Webpack.

    Phaser Webpack Loader is a plugin that streamlines the process of loading game assets in Phaser projects using Webpack. It facilitates parallel asset loading and integrates with Webpack's module system for efficient game development.
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  • 8
    Tiramisu

    Tiramisu

    Polyhedral compiler for expressing fast and portable data algorithms

    Tiramisu is a compiler for expressing fast and portable data parallel computations. It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. ...
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  • 9
    Incanter

    Incanter

    Clojure-based, R-like statistical computing and graphics environment

    Incanter is a Clojure-based, R-like statistical computing and visualization library running on the JVM. It integrates core numerical libraries like Parallel Colt and JFreeChart to deliver data manipulation, modeling, statistical tests, and charting in a REPL-friendly environment. Start by visiting the Incanter website for an overview, check out the documentation page for a listing of HOW-TOs and examples, and then download either an Incanter executable or a pre-built version of the latest build of Incanter, which includes all the necessary dependencies, and unpack the file (if you would like to build it from source, read Building Incanter). ...
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  • 10
    RxJavaSamples

    RxJavaSamples

    Examples of some of the most common usages of RxJava 2 and Retrofit

    Examples of some of the most common uses of RxJava 2 with Retrofit. For the interface that needs to request the token first, then use flatMap() to connect the token request and the actual data request coherently, without having to write a nested Callback structure. For non-disposable tokens (tokens that can be reused), after obtaining the token, save it for repeated use, and use retryWhen() to automatically re-acquire the token when it expires, making the process of token acquisition...
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  • 11
    Grenade

    Grenade

    Deep Learning in Haskell

    Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only...
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  • 12
    Swift AI

    Swift AI

    The Swift machine learning library

    ...Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the usage of Swift AI. Each resides in their own repository and can be built with little or no configuration. Each module now contains its own documentation. We recommend that you read the docs carefully for detailed instructions on using the various components of Swift AI. ...
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  • 13

    JavaMutex

    Provides 100% pure Java mutual exclusion.

    Freely redistributable open source 100% pure Java for mutual exclusion. Read-write and read-only reentrant lock, condition variable, atomic wraps for Boolean, Integer, Long, and Reference. Cell pool with optional locking, object exchanger, Intersect.
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  • 14
    PyCNN

    PyCNN

    Image Processing with Cellular Neural Networks in Python

    Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. CNN processors were designed to perform image processing; specifically, the original application of CNN processors was to perform real-time ultra-high frame-rate (>10,000 frame/s) processing unachievable by digital processors.
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  • 15

    ViennaCL

    Linear algebra and solver library using CUDA, OpenCL, and OpenMP

    ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects.
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    Downloads: 24 This Week
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  • 16
    Robot Framework FTP Library

    Robot Framework FTP Library

    FTP client for Robot Framework

    SOURCE CODE MOVED TO https://github.com/kowalpy/Robot-Framework-FTP-Library . NEW RELEASES WILL APPEAR ONLY AT GITHUB AND PYPI. This Python library makes it possible to test or use FTP server using Robot Framework keywords. Together with the library, there are also available project example and keywords documentation created by libdoc. This sourceforge webpage is linked from http://robotframework.org/#test-libraries as external library so it can be considered as the official Robot...
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  • 17

    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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  • 18
    PUB-Web is a peer-to-peer based volunteer computing environment for parallel applications written in Java.
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  • 19
    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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  • 20

    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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  • 21

    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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  • 22
    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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  • 23

    sudoku

    This a sudoku game using java like the on found in newspaper

    This a sudoku game using java like the on found in newspaper
    Downloads: 0 This Week
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  • 24

    FFmpeg for Android

    Configure and build FFmpeg library with Android NDK

    FFmpeg for Android is a set of Android makefiles which enable configuration and building FFmpeg library under Android source code tree with Android NDK.
    Downloads: 6 This Week
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  • 25

    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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