Search Results for "parallel"
Sort By:
Showing 351 open source projects for "parallel"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Dun and Bradstreet Risk Analytics - Supplier IntelligenceRisk, procurement, and compliance teams across the globe are under pressure to deal with geopolitical and business risks. Third-party risk exposure is impacted by rapidly scaling complexity in domestic and cross-border businesses, along with complicated and diverse regulations. It is extremely important for companies to proactively manage their third-party relationships. An AI-powered solution to mitigate and monitor counterparty risks on a continuous basis, this cutting-edge platform is powered by D&B’s Data Cloud with 520M+ Global Business Records and 2B+ yearly updates for third-party risk insights. With high-risk procurement alerts and multibillion match points, D&B Risk Analytics leverages best-in-class risk data to help drive informed decisions. Perform quick and comprehensive screening, using intelligent workflows. Receive ongoing alerts of key business indicators and disruptions.
-
1
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. -
2
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. -
3
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. -
4
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. -
The Original Buy Center Software.VAN sources private-party vehicles from over 20 platforms and provides all necessary tools to communicate with sellers and manage opportunities. Franchise and Independent dealers can boost their buy center strategies with our advanced tools and an experienced Acquisition Coaching™ team dedicated to your success.
-
5
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. -
6
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. -
7
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. ... -
8
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. ... -
9
Hermione
Browser test runner based on mocha and wdio
...If you are familiar with WebdriverIO and Mocha, you can start writing and running tests in 5 minutes! You need to install Hermione via npm and add a tiny config to your project. When tests are run one by one, it takes a lot of time. Hermione can run tests in parallel sessions in different browsers out of the box. Running of too many tests in parallel can lead to the overloading of the main process CPU usage which causes degradation in test passing time, so Hermione runs all tests in subprocesses in order to solve this problem. -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
-
10
PlatEMO
Evolutionary multi-objective optimization platform
...Users can select various figures to be displayed, including the Pareto front of the result, the Pareto set of the result, the true Pareto front, and the evolutionary trajectories of any performance indicator values. PlatEMO provides a powerful and friendly GUI, where users can configure all the settings and perform experiments in parallel via the GUI without writing any code. -
11
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... -
12
Bifrost
Middleware for production-oriented MySQL
...Multiple data sources, multiple target library support. Both incremental and full data synchronization are supported. One Binlog parsing thread, multiple target libraries are synchronized in parallel. Automatically restore configuration after restarting after downtime, accurate control of location. Support monitoring and alarm functions such as Email and WeChat enterprise account. Provide third-party monitoring platform access interface (Http Basic authentication) HTTP API. MySQL, ClickHouse plugin supports DDL synchronization. -
13
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. -
14
bild
Image processing algorithms in pure Go
...Package histogram provides basic histogram types and functions to analyze RGBA images. Package paint provides functions to edit a group of pixels on an image. Package parallel provides helper functions for the dispatching of parallel jobs. -
15
Starlark in Go
Starlark in Go: the Starlark configuration language, implemented in Go
...The Go-based interpreter allows developers to run or embed Starlark programs directly within Go applications, extending them with user-defined scripts and configurable logic. Unlike Python, Starlark supports parallel execution across multiple threads and maintains deterministic behavior, making it suitable for scalable and reproducible workloads. It offers familiar syntax features such as dictionaries, lists, and first-class functions with lexical scoping. -
16
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. -
17
nbmake
Pytest plugin for testing notebooks
Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks. -
18
Soufflé
Datalog variant for tool designers crafting analyses in Horn clauses
Rapid prototyping for your analysis problems with logic; enabling deep design-space explorations; designed for large-scale static analysis; e.g., points-to analysis for Java, taint-analysis, and security checks. Futamura projections/partial evaluation for effective translation to parallel C++; optimized staged compilation; specialized data-structures for logical relations. Efficient translation to parallel C++ of Datalog programs (CAV'16, CC'16) Efficient interpretation using de-specialization techniques (PLDI'21) Specialized data structure for relations (PACT'19, PPoPP'19, PMAM'19) with optimal index selection (VLDB'18) Extended semantics of Datalog, e.g., permitting unbounded recursions with numbers and terms. ... -
19
Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
20
PRDownloader
A file downloader library for Android with pause and resume support
...PRDownloader gives callbacks for everything like onProgress, onCancel, onStart, onError and etc while downloading a file. Supports proper request canceling. Many requests can be made in parallel. All types of customization are possible. -
21
ComputeSharp
.NET library to run C# code in parallel on the GPU through DX12
ComputeSharp is a .NET library to run C# code in parallel on the GPU through DX12 and dynamically generated HLSL compute shaders. The available APIs let you access GPU devices, allocate GPU buffers and textures, move data between them and the RAM, write compute shaders entirely in C# and have them run on the GPU. The goal of this project is to make GPU computing easy to use for all .NET developers! -
22
Binaryen
Compiler infrastructure and toolchain library for WebAssembly
...It accepts input in WebAssembly-like form but also accepts a general control flow graph for compilers that prefer that. Binaryen's internal IR uses compact data structures and is designed for completely parallel codegen and optimization, using all available CPU cores. Binaryen's IR also compiles down to WebAssembly extremely easily and quickly because it is essentially a subset of WebAssembly. Binaryen's optimizer has many passes (see an overview later down) that can improve code size and speed. These optimizations aim to make Binaryen powerful enough to be used as a compiler backend by itself. -
23
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. -
24
JavaCV
Java interface to OpenCV, FFmpeg, and more
JavaCV uses wrappers from the JavaCPP Presets of commonly used libraries by researchers in the field of computer vision (OpenCV, FFmpeg, libdc1394, FlyCapture, Spinnaker, OpenKinect, librealsense, CL PS3 Eye Driver, videoInput, ARToolKitPlus, flandmark, Leptonica, and Tesseract) and provides utility classes to make their functionality easier to use on the Java platform, including Android. JavaCV also comes with hardware accelerated full-screen image display (CanvasFrame and GLCanvasFrame), easy-to-use methods to execute code in parallel on multiple cores (Parallel), user-friendly geometric and color calibration of cameras and projectors (GeometricCalibrator, ProCamGeometricCalibrator, ProCamColorCalibrator), detection and matching of feature points (ObjectFinder), a set of classes that implement direct image alignment of projector-camera systems (mainly GNImageAligner, ProjectiveTransformer, ProjectiveColorTransformer, ProCamTransformer, and ReflectanceInitializer), and more. -
25
TensorStore
Library for reading and writing large multi-dimensional arrays
...It separates the logical view (shape, dtype, chunking) from the physical layout so the same code can target Zarr, N5, TIFF pyramids, or custom backends. Rich indexing, slicing, and broadcasting operations make it feel like a familiar array API, while asynchronous I/O pipelines stream chunks efficiently in parallel. Transactional semantics allow atomic updates and consistent snapshots, which is essential for large, shared datasets used by ML and scientific workflows. The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core.
