TY  - BOOK
AU  - Trobec,Roman
AU  - Bulić,Patricio
AU  - Robič,Borut
AU  - Slivnik,Boštjan
TI  - Introduction to Parallel Computing: From Algorithms to Programming on State-of-the-Art Platforms 
T2  - Undergraduate Topics in Computer Science,
SN  - 9783319988337
U1  - 005.11 23
PY  - 2018///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Computer programming
KW  - Microprocessors
KW  - Microprogramming
KW  - Numerical analysis
KW  - Programming Techniques
KW  - Control Structures and Microprogramming
KW  - Numeric Computing
KW  - Processor Architectures
N1  - Part I: Foundations -- Why Do We Need Parallel Programming -- Overview of Parallel Systems -- Part II: Programming -- Programming Multi-Core and Shared Memory Multiprocessors Using OpenMP -- MPI Processes and Messaging -- OpenCL for Massively Parallel Graphic Processors -- Part III: Engineering -- Engineering: Parallel Computation of the Number pi -- Engineering: Parallel Solution of 1-D Heat Equation -- Engineering: Parallel Implementation of Seam Carving -- Final Remarks and Perspectives -- Appendix A: Hints for Making Your Computer a Parallel Machine
N2  - Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs' run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition
UR  - https://hdl.loc.gov/loc.gdc/stacks.2019736344
ER  -