Parallel processing is a crucial aspect of modern computing, enabling us to handle complex tasks more efficiently. In this section, we provide a benchmark to evaluate the performance of different parallel processing methods.
Single-threaded Execution: This method executes tasks sequentially on a single processor. It is the simplest form of processing but can be slow for complex tasks.
Multi-threaded Execution: This method divides a task into smaller sub-tasks and executes them simultaneously on multiple threads within a single processor. It can significantly improve performance for CPU-bound tasks.
Multi-core Execution: This method utilizes multiple cores within a single processor to execute tasks simultaneously. It is more efficient than multi-threading for tasks that require a lot of computational resources.
Distributed Computing: This method distributes tasks across multiple machines connected over a network. It is ideal for large-scale tasks that cannot be executed on a single machine.
For more information about parallel processing, you can read our detailed guide on Parallel Processing.
If you're interested in learning more about the benefits and challenges of parallel processing, check out our Parallel Processing Series.