Concurrent Extensions Library (CEL) provides functionality and implementations commonly useful in concurrent programming.
http://threading.codeplex.com/Tags | asynchronous atomic concurrency concurrent extensions |
Implementation | DotNet |
License | Ms-PL |
Platform | Windows |
Threading, concurrency, etc
asynchronous concurrency concurrent thread thread-pool threading threadpoolZIO is a zero-dependency Scala library for asynchronous and concurrent programming. It is powered by highly-scalable, non-blocking fibers that never waste or leak resources, ZIO lets you build scalable, resilient, and reactive applications that meet the needs of your business.
concurrency asynchronicity functional-programming queues streams promises stm asynchronous concurrent concurrent-programming asynchronous-programming concurrent-data-structureRxJava is a Java VM implementation of Reactive Extensions: a library for composing asynchronous and event-based programs by using observable sequences. It extends the observer pattern to support sequences of data/events and adds operators that allow you to compose sequences together declaratively while abstracting away concerns about things like low-level threading, synchronization, thread-safety and concurrent data structures.
reactive reactive-programming asynchronous events asyncCrossbeam supports concurrent programming, especially focusing on memory management, synchronization, and non-blocking data structures. atomic for enhancing std::sync API. AtomicConsume provides C/C++11-style "consume" atomic operations (re-exported from crossbeam-utils). ArcCell provides atomic storage and retrieval of Arc.
synchronization concurrency parallelism🎏 simple show cases of java concurrency problems
concurrency demo showcase concurrent-programming concurrency-problem concurrency-issue concurrency-gotchas thread-safety multi-threading parallelismAsynchronous function queue with adjustable concurrency. This module exports a class Queue that implements most of the Array API. Pass async functions (ones that accept a callback or return a promise) to an instance's additive array methods. Processing begins when you call q.start().
queue async asynchronous synchronous job task concurrency concurrentReactive Programming is a hot topic as of late, especially with such things as the Reactive Manifesto. Applications' needs have changed over time, from simple polling for data to a full reactive system where data is pushed at you. Each time, we're adding more complexity, data, and asynchronous behavior to our applications. How do we manage it all? How do we scale it? By moving towards "Reactive Architectures" which are event-driven, resilient, and responsive. With the Reactive Extensions, you have all the tools you need to help build these systems.The Reactive Extensions for Ruby (RxRuby) is a set of libraries for composing asynchronous and event-based programs using observable sequences and fluent query operators that many of you already know in Ruby. Using RxRuby, developers represent asynchronous data streams with Observables, query asynchronous data streams using our many operators, and parameterize the concurrency in the asynchronous data streams using Schedulers. Simply put, RxRuby = Observables + Operators + Schedulers.
The Joins project provides asynchronous concurrency semantics based on join calculus and modeled after the Microsoft Research C? (C Omega) project.
asynchronous concurrency threadingLibdill is a C library that makes writing structured concurrent programs easy. There is no interaction between threads. Each thread is treated as a separate process. Channels are always unbuffered. Coroutines can be canceled. Generally speaking, though, libdill's concurrency primitives are only a bit slower than basic C flow control statements. A context switch has been seen to execute in as little as 6 ns, with coroutine creation taking 26 ns. Passing a message through a channel takes about 40 ns.
concurrency threads multi-threading socketsReactive Extensions for Python (RxPY) is a set of libraries for composing asynchronous and event-based programs using observable sequences and LINQ-style query operators in Python. Using Rx, developers represent asynchronous data streams with Observables, query asynchronous data streams using operators, and parameterize concurrency in data/event streams using Schedulers.Using Rx, you can represent multiple asynchronous data streams (that come from diverse sources, e.g., stock quote, Tweets, computer events, web service requests, etc.), and subscribe to the event stream using the Observer object. The Observable notifies the subscribed Observer instance whenever an event occurs.You can put various transformations in-between the source Observable and the consuming Observer as well.
reactive reactivex reactive-extensions rxpyYew is a modern Rust framework inspired by Elm and ReactJS for creating multi-threaded frontend apps with WebAssembly. NEW! The framework supports multi-threading & concurrency out of the box. It uses Web Workers API to spawn actors (agents) in separate threads and uses a local scheduler attached to a thread for concurrent tasks.
web gui jsx elm web-framework wasm asmjs emscripten concurrency multithreading webworkersEight two-week units of courseware (slides, lecture notes, samples, tools) for teaching how to program parallel/concurrent applications at a high-level using Microsoft’s Parallel Extensions to the .NET Framework.
parallel-programming concurrency concurrent performanceAkka is the platform for the next generation event-driven, scalable and fault-tolerant architectures on the JVM. It helps to write simpler correct concurrent applications using Actors, STM & Transactors. It could scale out on multi-core or multiple nodes using asynchronous message passing. For fault-tolerance it adopts the Let it crash or Embrace failure model to build applications that self-heals, systems that never stop.
concurrency scalable fault-tolerance event-driven parallelism messaging high-availabilityOur apps constantly do work. The faster you react to user input and produce an output, the more likely is that the user will continue to use your application. As our applications grow in complexity, the more and more work needs to be done. You need to start thinking about how to categorize and optimize work, how to make that work more efficient, more optimized and finally, faster. In most cases that doesn’t end very well because you need to know a lot about concurrency, multithreading etc. - it’s a very complex field. You need to know all API specifics before you are able to write something. Overdrive was created as a result of that struggle. It is a framework that exposes several simple concepts which are made on top of complex system frameworks that enable multithreading, concurrency and most importantly, more speed.
concurrency multi-threading thread-safetyOur apps constantly do work. The faster you react to user input and produce an output, the more likely is that the user will continue to use your application. As our applications grow in complexity, the more and more work needs to be done. You need to start thinking about how to categorize and optimize work, how to make that work more efficient, more optimized and finally, faster. In most cases that doesn’t end very well because you need to know a lot about concurrency, multithreading etc. - it’s a very complex field. You need to know all API specifics before you are able to write something. Overdrive was created as a result of that struggle. It is a framework that exposes several simple concepts which are made on top of complex system frameworks that enable multithreading, concurrency and most importantly, more speed.
concurrency multi-threading thread-safetyJava Concurrency Tools for the JVM. This project aims to offer some concurrent data structures currently missing from the JDK.
concurrency data-structures queues lock-free wait-free awesome collections java-collection data-structureTunneling software created using the Reactive Extensions framework! Rx is not just for events!!!
concurrency http link message reactive-extensio threadingAs explained here and here, the map type in Go doesn't support concurrent reads and writes. concurrent-map provides a high-performance solution to this by sharding the map with minimal time spent waiting for locks. The package is now imported under the "cmap" namespace.
concurrency map concurrent-programming thread-safetyThis is not an ORM. People that are wrapping ORM’s around Redis are missing the point. This gem originally arose out of a need for high-concurrency atomic operations; for a fun rant on the topic, see An Atomic Rant, or scroll down to Atomic Counters and Locks in this README.
Evaluate asynchronous tasks with configurable concurrency.
d3 d3-module asynchronous async queue
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