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Hopefully it is also useful to give some help for parallelising programs for other applications.Īdobe Acrobat 7 Tips and Tricks: The 150 Best This tutorial mainly aims at writing parallel programs for solving linear equation systems. * how to write parallel programs for or distributed memory computers using MPI and ScaLA-PACK. * how to write parallel programs for shared memory computers using OpenMP, * how to analyse software and find the points where parallelisation might be helpful, * the software needed for parallel programming, and how to install and configure it, * the various existing architectures of parallel computers, The goal of this tutorial is to give an introduction into all aspects of parallel programming that are necessary to write ones own parallel programs. Parallel programming methods that work on dual-core PCs also work on larger shared memory systems, and a program designed for a cluster or other type of distributed memory system will also perform well on your dual-core (or multi-core) PC. This cheap extra computing power has to be used efficiently, which equires parallel programming. Since 2005, x86-compatible CPUs designed for desktop computers are available with two "cores", which essentially makes them dualprocessor systems. Multiprocessor computers used to be quite expensive, and not everybody had access to them. This computing time can be reduced by distributing a problem over several processors. Many scientific computations require a considerable amount of computing time. And that you will have a whole lot of fun creating content pages on topics you have a passion for. The strategies in the book can help you maximize your revenue from Google AdSense. The Google AdSense Handbook: Making money by adding Google AdSense ads to your websites
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