Parallelism is a crucial concept in modern software development, allowing applications to perform multiple tasks simultaneously. In .NET Core, parallelism can be applied to both CPU-bound and I/O-bound operations using different techniques and tools. This article highlights the importance of understanding the differences between these two types of operations.

CPU-bound operations require significant processing power and benefit from parallel execution using tools like Parallel.For, Parallel.ForEach, and the Task Parallel Library (TPL). For example, applying a filter to a large collection of images is a CPU-bound task that can be accelerated using parallelism.

I/O-bound operations, on the other hand, are limited by external systems such as disk I/O, network I/O, or database queries. Asynchronous programming is more suitable for these tasks, allowing applications to continue executing other tasks while waiting for I/O operations to complete. For instance, downloading content from multiple web pages concurrently using Task.WhenAll and asynchronous programming.

In some cases, both CPU-bound and I/O-bound tasks need to be handled together. In such scenarios, combining parallel and asynchronous programming techniques can efficiently handle complex scenarios.

Source: https://dev.to/dotnetfullstackdev/parallelism-is-not-same-for-cpu-bound-and-io-bound-operations-in-net-core-157f