首页describe the difference between parallelism and concurrency in embedded system

describe the difference between parallelism and concurrency in embedded system

时间: 2024-05-31 17:14:21 浏览: 112

Concurrency in C# Cookbook 原版（pdf+mobi）

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I had one major goal in writing this book: to cover modern approaches to concurrency. There are a hundred books out there that describe threads and all the various synchronization primitives in excruciating detail; this is not one of those. This book focuses specifically on how code should be written, not how code could be written. This book does contain an introduction to concurrency (multithreading, asynchronous programming, etc). However, it is not an introduction to C# or .NET. I do expect my readers to understand delegates, lambda expressions, LINQ, OOP, etc. If you need help in these areas, there are other great books that cover these topics far better than I could do. By focusing only on modern coding practices, and by avoiding "fluff", I've kept the book short. It's 200 pages, a portable size. The vast majority of these pages are recipes written with an extremely practical mindset, so they can be used as a ready reference for the modern developer.

Parallelism and concurrency are concepts that are commonly used in embedded systems programming. Although they are related, they are not the same thing. Parallelism refers to the simultaneous execution of multiple tasks or processes. This can be achieved through the use of multiple processing units or cores. In embedded systems, parallelism is often used to improve performance and reduce response times. For example, a microcontroller with multiple cores can execute multiple tasks simultaneously, which can improve the overall performance of the system. Concurrency, on the other hand, refers to the ability of multiple tasks or processes to make progress at the same time. Concurrency can be achieved through the use of multitasking or multithreading. In embedded systems, concurrency is often used to improve responsiveness and allow multiple tasks to run simultaneously. For example, a system that needs to read data from multiple sensors can use concurrency to read the data from each sensor simultaneously, which can reduce the overall response time of the system. In summary, parallelism refers to the simultaneous execution of multiple tasks, while concurrency refers to the ability of multiple tasks to make progress at the same time. Both concepts are important in embedded systems programming and can be used to improve performance, responsiveness, and efficiency.

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