"计算机组成与结构：lecture 17 并行处理.pdf"

Lecture 17: Parallel Processing.pdf discusses the concept of parallel processing in computer organization. Parallel processing is the use of multiple processing units or cores to perform multiple tasks simultaneously. This allows for increased processing speed and efficiency in computing systems. The lecture explores the benefits of parallel processing, such as improved performance, increased reliability, and scalability. Parallel processing can significantly reduce the time it takes to complete complex computational tasks by dividing them into smaller tasks that can be executed in parallel. The lecture also covers various types of parallel processing architectures, including shared memory, distributed memory, and hybrid architectures. Shared memory systems allow multiple processing units to access a common memory space, while distributed memory systems have separate memory spaces for each processing unit. Hybrid architectures combine elements of both shared and distributed memory architectures. Additionally, the lecture discusses parallel processing programming models, such as task parallelism and data parallelism. Task parallelism involves dividing a computational task into smaller tasks that can be executed concurrently, while data parallelism involves dividing data into smaller chunks that can be processed in parallel. Overall, parallel processing is an essential concept in computer organization that is crucial for improving processing speed and efficiency in modern computing systems. By utilizing multiple processing units to perform tasks simultaneously, parallel processing has the potential to revolutionize the way we approach computational tasks and drive innovation in the field of computer science.