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Concurrent, Parallel, and Distributed Computing offers an excellent overview of the various areas of the computing field. There is a lot of overlap between the words "concurrent computing," "parallel computing," and "distributed computing," and there is no obvious differentiation between them. The same system can be described as "parallel" and "distributed"; in a typical distributed system, the processors run concurrently in parallel. The content in the book is presented in such a way that even a reader with no prior knowledge of computers may understand it and become acquainted with the fundamental concepts of computing. It offers numerous small examples, demonstration materials, and sample exercises that teachers can use to teach parallel programming principles to students who have just recently been introduced to basic programming concepts. It focuses on Python multiprocessing features like fork/join threading, message passing, sharing resources between threads, and using locks. Parallelism's utility can be seen in applications like searching, sorting, and simulations. Students and researchers can get an accessible and comprehensive explanation of the concepts, guidelines, and, in particular, the complex instrumentation techniques used in computing.
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Concurrent, Parallel, and Distributed Computing offers an excellent overview of the various areas of the computing field. There is a lot of overlap between the words "concurrent computing," "parallel computing," and "distributed computing," and there is no obvious differentiation between them. The same system can be described as "parallel" and "distributed"; in a typical distributed system, the processors run concurrently in parallel. The content in the book is presented in such a way that even a reader with no prior knowledge of computers may understand it and become acquainted with the fundamental concepts of computing. It offers numerous small examples, demonstration materials, and sample exercises that teachers can use to teach parallel programming principles to students who have just recently been introduced to basic programming concepts. It focuses on Python multiprocessing features like fork/join threading, message passing, sharing resources between threads, and using locks. Parallelism's utility can be seen in applications like searching, sorting, and simulations. Students and researchers can get an accessible and comprehensive explanation of the concepts, guidelines, and, in particular, the complex instrumentation techniques used in computing.