Parallel Programming
for Multicore and Cluster Systems
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Beschreibung
Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing.
Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures.
The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The presented material has been used for courses in parallel programming at different universities for many years.
This book offers broad coverage of all aspects of parallel programming. Many examples and exercises are provided to show how to apply the techniques. There is special emphasis on runtime efficiency and memory organization.
Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing.
Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures.
The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The presented material has been used for courses in parallel programming at different universities for many years.
Broad coverage of all aspects of parallel programming
Special emphasis on runtime efficiency and memory organization
Presented material has been used in courses for many years
Complemented by many examples and an additional website with teaching material
Autor*in
Thomas Rauber
Themen in »Parallel Programming«
Distributed Programming Grid Computing Multithreading Networking Parallel Programming Scientific Programming cluster multi-core parallel computing
Stimmen zu »Parallel Programming«
"[...] The end-ofchapter exercises are stimulating, there are adequate references for further study, and the index, though short, is quite helpful. [...] This book introduces the basics of parallel programming on multicore and cluster systems. Adequate sample programs illustrate the key concepts of parallel programming. [...]" ACM Computing Reviews, S. V. Nagaraj, February 2011
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