Search Results for "parallel"
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Showing 1344 open source projects for "parallel"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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parallel-ssh
Asynchronous parallel SSH client library.
parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways. -
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StreamEx
Enhancing Java Stream API
This library defines four classes, StreamEx, IntStreamEx, LongStreamEx, DoubleStreamEx which are fully compatible with Java 8 stream classes and provide many additional useful methods. Also EntryStream class is provided which represents the stream of map entries and provides additional functionality for this case. Finally, there are some new useful collectors defined in MoreCollectors class as well as primitive collectors concept. -
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The Futhark Programming Language
A data-parallel functional programming language
Futhark is a small programming language designed to be compiled into efficient parallel code. It is a statically typed, data-parallel, and purely functional array language in the ML family, and comes with a heavily optimizing ahead-of-time compiler that presently generates either GPU code via CUDA and OpenCL, or multi-threaded CPU code. Futhark is not designed for graphics programming, but can instead use the compute power of the GPU to accelerate data-parallel array computations. ... -
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PolarDB for PostgreSQL
A cloud-native database based on PostgreSQL developed by Alibaba Cloud
PolarDB for PostgreSQL is Alibaba Cloud's cloud-native, distributed version of PostgreSQL designed for high availability, scalability, and performance. It enhances standard PostgreSQL with features like shared storage, compute-storage separation, and parallel processing. PolarDB supports cloud-native workloads, offering enterprise-grade capabilities while maintaining PostgreSQL compatibility. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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101-0250-00
ETH course - Solving PDEs in parallel on GPUs
This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering. -
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Parallel WaveGAN
Unofficial Parallel WaveGAN
Parallel WaveGAN is an unofficial PyTorch implementation of several state-of-the-art non-autoregressive neural vocoders, centered on Parallel WaveGAN but also including MelGAN, Multiband-MelGAN, HiFi-GAN, and StyleMelGAN. Its main goal is to provide a real-time neural vocoder that can turn mel spectrograms into high-quality speech audio efficiently. -
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golangci-lint
Fast linters Runner for Go
golangci-lint is a fast Go linters runner. It runs linters in parallel, uses caching, supports yaml config, has integrations with all major IDE and has dozens of linters included. ⚡ Very fast: runs linters in parallel, reuses Go build cache and caches analysis results. Yaml-based configuration. Integrations with VS Code, Sublime Text, GoLand, GNU Emacs, Vim, Atom, GitHub Actions. A lot of linters included, no need to install them. -
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compress
Optimized Go Compression Packages
...Optimized deflate packages which can be used as a dropin replacement for gzip, zip and zlib. snappy is a drop-in replacement for github.com/golang/snappy offering better compression and concurrent streams. huff0 and FSE implementations for raw entropy encoding. gzhttp Provides client and server wrappers for handling gzipped requests efficiently. pgzip is a separate package that provides a very fast parallel gzip implementation. Stream decompression is now faster on asynchronous since the goroutine allocation much more effectively splits the workload. On typical streams, this will typically use 2 cores fully for decompression. When a stream has finished decoding no goroutines will be left over, so decoders can now safely be pooled and still be garbage collected. -
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Piscina
A fast, efficient Node.js Worker Thread Pool implementation
Piscina is a fast, efficient Node.js worker thread pool implementation, designed to perform heavy CPU-bound tasks in parallel, thereby improving application performance. -
Digital business card + lead capture + contact enrichmentShare digital business cards, capture leads, and enrich validated contact info - at events, in the field, and beyond. Powered by AI and our proprietary data engine, Popl drives growth for companies around the world, turning every handshake into an opportunity.
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle large-scale data. It’s become widely-used for ranking, classification and many other machine learning tasks. -
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Dagger.jl
A framework for out-of-core and parallel execution
Dagger.jl is a framework for out-of-core and parallel computing in Julia that allows users to construct and execute dynamic task graphs. It is designed for large-scale, distributed, and memory-efficient computations. Dagger supports lazy evaluation and scheduling across multiple threads or machines, enabling high-performance workflows for data processing, scientific computing, and machine learning. -
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mprocs
Run multiple commands in parallel
mprocs runs multiple commands in parallel and shows output of each command separately. When you work on a project you very often need the same list of commands to be running. For example: webpack serve, just --watch, node src/server.js. With mprocs you can list these commands in mprocs.yaml and run all of them by running mprocs. Then you can switch between the outputs of running commands and interact with them. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Apache Beam
Unified programming model for Batch and Streaming
Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers. -
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Async PHP
Easily run code asynchronously
Spatie Async is a PHP library that allows developers to run parallel processes using asynchronous tasks. It helps optimize performance by executing long-running or resource-intensive tasks concurrently, instead of sequentially. The library is easy to use and integrates well with existing PHP applications, making it suitable for batch processing, data scraping, or any scenario where concurrency can boost efficiency. -
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future
R package: future: Unified Parallel and Distributed Processing in R
The future package in R provides a unified abstraction for asynchronous and/or parallel computation. It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. -
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Parallel executor
paexec distributes tasks over network or CPUs.
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Colly
Elegant Scraper and Crawler Framework for Golang
...With Colly you can easily extract structured data from websites, which can be used for a wide range of applications, like data mining, data processing or archiving. Clean API. Fast (>1k request/sec on a single core) Manages request delays and maximum concurrency per domain. Automatic cookie and session handling. Sync/async/parallel scraping. Distributed scraping. Caching, automatic encoding of non-unicode responses. Robots.txt support. Google App Engine support. -
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HDF5
Official HDF5® Library Repository
HDF5 (Hierarchical Data Format v5) is a widely-used data management library and file format for storing large and complex scientific data sets efficiently. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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HYPRE
Parallel solvers for sparse linear systems featuring multigrid methods
Livermore’s HYPRE library of linear solvers makes possible larger, more detailed simulations by solving problems faster than traditional methods at large scales. It offers a comprehensive suite of scalable solvers for large-scale scientific simulation, featuring parallel multigrid methods for both structured and unstructured grid problems. The HYPRE library is highly portable and supports a number of languages. Work on HYPRE began in the late 1990s. It has since been used by research institutions and private companies to simulate groundwater flow, magnetic fusion energy plasmas in tokamaks and stellarators, blood flow through the heart, fluid flow in steam generators for nuclear power plants, and pumping activity in oil reservoirs, to name just a few areas. ... -
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pgBadger
A fast PostgreSQL Log Analyzer
...It parses PostgreSQL logs and generates detailed, visually appealing HTML reports, helping DBAs and developers understand query performance, connection issues, and system bottlenecks. With support for incremental analysis, gzip-compressed logs, and parallel processing, pgBadger is ideal for monitoring and optimizing PostgreSQL database activity in production environments. -
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TFT_eSPI
Arduino and PlatformIO IDE compatible TFT library
...The library can be loaded using the Arduino IDE's Library Manager. Direct Memory Access (DMA) can be used with the ESP32, RP2040, and STM32 processors to improve rendering performance. "Four wire" SPI and 8 bit parallel interfaces are supported. Due to the lack of GPIO pins, the 8-bit parallel interface is NOT supported on the ESP8266. 8 bit parallel interface TFTs (e.g. UNO format mcufriend shields) can use with the STM32 Nucleo 64/144 range or the UNO format ESP32. ILI9341 and ST7796 SPI-based displays are recommended as starting points for experimenting with this library. ... -
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pgsync
Postgres to Elasticsearch/OpenSearch sync
pgsync is a lightweight tool for syncing Postgres databases across environments, such as from production to staging. It allows selective table syncing, data masking, and parallel copying for fast and safe data migration. pgsync is ideal for developers who need realistic test data without exposing sensitive information. -
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Bend
A massively parallel, high-level programming language
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic...
