Practical parallel programming
著者
書誌事項
Practical parallel programming
（Scientific and engineering computation）
MIT Press, c1995
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Practical Parallel Programming provides scientists and engineers with a detailed, informative, and often critical introduction to parallel programming techniques.
Parallel computers have become widely available in recent years. Many scientists are now using them to investigate the grand challenges of science, such as modeling global climate change, determining the masses of elementary particles from first principles, or sequencing the human genome. However, software for parallel computers has developed far more slowly than the hardware. Many incompatible programming systems exist, and many useful programming techniques are not widely known.Practical Parallel Programming provides scientists and engineers with a detailed, informative, and often critical introduction to parallel programming techniques. Following a review of the fundamentals of parallel computer theory and architecture, it describes four of the most popular parallel programming models in use today-data parallelism, shared variables, message passing, and Linda-and shows how each can be used to solve various scientific and numerical problems. Examples, coded in various dialects of Fortran, are drawn from such domains as the solution of partial differential equations, solution of linear equations, the simulation of cellular automata, studies of rock fracturing, and image processing. Practical Parallel Programming will be particularly helpful for scientists and engineers who use high-performance computers to solve numerical problems and do physical simulations but who have little experience of networking or concurrency. The book can also be used by advanced undergraduate and graduate students in computer science in conjunction with material covering parallel architectures and algorithms in more detail. Computer science students will gain a critical appraisal of the current state of the art in parallel programming. Scientific and Engineering Computation series
目次
- Part 1 Fundamentals: basic architectural ideas
- classifying architectures
- some example applications
- decomposition techniques
- terms and measures. Part 3 Data parallelism: basic operations
- an inside-out syntax
- other data-parallel operations
- automatic parallelization
- controlling and exploiting data placement
- discussion. Part 3 Shared variables: creating and coordinating processes
- practical synchronization mechanisms
- futures
- caching
- scheduling and mapping parallel programmes
- parallel I/O systems
- discussion. Part 4 Message passing: channels
- the crystalline model
- procedural message-passing systems
- watching programmes run
- discussion. Part 5 Generative communication: the generative model
- managing data structures in Tuple space
- active data structures
- message passing through Tuple space
- implementing generative communication
- enhancing generative communication
- some other high-level alternatives
- discussion. Appendices: the Fortran-K programming language
- a short history lesson
- recommended reading.
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