《并行程序设计导》 第一章PPT.ppt

Professor P Copyright ? 2010, Elsevier Inc. All rights Reserved 15 questions 300 exams Professor P’s grading assistants Copyright ? 2010, Elsevier Inc. All rights Reserved TA#1 TA#2 TA#3 Division of work – data parallelism Copyright ? 2010, Elsevier Inc. All rights Reserved TA#1 TA#2 TA#3 100 exams 100 exams 100 exams Division of work – task parallelism Copyright ? 2010, Elsevier Inc. All rights Reserved TA#1 TA#2 TA#3 Questions 1 - 5 Questions 6 - 10 Questions 11 - 15 Division of work – data parallelism Copyright ? 2010, Elsevier Inc. All rights Reserved Division of work – task parallelism Copyright ? 2010, Elsevier Inc. All rights Reserved Tasks Receiving Addition Coordination Cores usually need to coordinate their work. Communication – one or more cores send their current partial sums to another core. Load balancing – share the work evenly among the cores so that one is not heavily loaded. Synchronization – because each core works at its own pace, make sure cores do not get too far ahead of the rest. Copyright ? 2010, Elsevier Inc. All rights Reserved What we’ll be doing Learning to write programs that are explicitly parallel. Using the C language. Using three different extensions to C. Message-Passing Interface (MPI) Posix Threads (Pthreads) OpenMP Copyright ? 2010, Elsevier Inc. All rights Reserved Type of parallel systems Shared-memory The cores can share access to the computer’s memory. Coordinate the cores by having them examine and update shared memory locations. Distributed-memory Each core has its own, private memory. The cores must communicate explicitly by sending messages across a network. Copyright ? 2010, Elsevier Inc. All rights Reserved Type of parallel systems Copyright ? 2010, Elsevier Inc. All rights Reserved Shared-memory Distributed-memory Terminology Concurrent computing – a program is one in which multiple tasks can be in progress at any instant. Parallel computing – a program is one in which multiple tasks cooperate closely to solve a