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Books > Computing & IT > Computer communications & networking
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Parallel Programming for Modern High Performance Computing Systems (Paperback)
Loot Price: R1,359
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Parallel Programming for Modern High Performance Computing Systems (Paperback)
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In view of the growing presence and popularity of multicore and
manycore processors, accelerators, and coprocessors, as well as
clusters using such computing devices, the development of efficient
parallel applications has become a key challenge to be able to
exploit the performance of such systems. This book covers the scope
of parallel programming for modern high performance computing
systems. It first discusses selected and popular state-of-the-art
computing devices and systems available today, These include
multicore CPUs, manycore (co)processors, such as Intel Xeon Phi,
accelerators, such as GPUs, and clusters, as well as programming
models supported on these platforms. It next introduces
parallelization through important programming paradigms, such as
master-slave, geometric Single Program Multiple Data (SPMD) and
divide-and-conquer. The practical and useful elements of the most
popular and important APIs for programming parallel HPC systems are
discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and
OpenACC. It also demonstrates, through selected code listings, how
selected APIs can be used to implement important programming
paradigms. Furthermore, it shows how the codes can be compiled and
executed in a Linux environment. The book also presents hybrid
codes that integrate selected APIs for potentially multi-level
parallelization and utilization of heterogeneous resources, and it
shows how to use modern elements of these APIs. Selected
optimization techniques are also included, such as overlapping
communication and computations implemented using various APIs.
Features: Discusses the popular and currently available computing
devices and cluster systems Includes typical paradigms used in
parallel programs Explores popular APIs for programming parallel
applications Provides code templates that can be used for
implementation of paradigms Provides hybrid code examples allowing
multi-level parallelization Covers the optimization of parallel
programs
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