000906817 000__ 03092cam\a2200409\a\4500 000906817 001__ 906817 000906817 005__ 20210515182103.0 000906817 006__ m\\\\\o\\d\\\\\\\\ 000906817 007__ cr\cn\nnnunnun 000906817 008__ 111201s2012\\\\fluaf\\\ob\\\\000\0\eng\d 000906817 010__ $$z 2011044663 000906817 020__ $$z9781439827352 000906817 020__ $$z9781439827369 $$q(electronic book) 000906817 035__ $$a(MiAaPQ)EBC870689 000906817 035__ $$a(Au-PeEL)EBL870689 000906817 035__ $$a(CaPaEBR)ebr10535465 000906817 035__ $$a(CaONFJC)MIL390926 000906817 035__ $$a(OCoLC)785784652 000906817 040__ $$aMiAaPQ$$cMiAaPQ$$dMiAaPQ 000906817 050_4 $$aQA76.6$$b.C6275 2012 000906817 08204 $$a511/.6$$223 000906817 24500 $$aCombinatorial scientific computing$$h[electronic resource] /$$cedited by Uwe Naumann, Olaf Schenk. 000906817 260__ $$aBoca Raton :$$bCRC Press,$$c2012. 000906817 300__ $$axxiii, 549 p., [8] p. of plates :$$bill. 000906817 4901_ $$aChapman & Hall/CRC computational science series 000906817 504__ $$aIncludes bibliographical references. 000906817 506__ $$aAccess limited to authorized users. 000906817 520__ $$a"Foreword the ongoing era of high-performance computing is filled with enormous potential for scientific simulation, but also with daunting challenges. Architectures for high-performance computing may have thousands of processors and complex memory hierarchies paired with a relatively poor interconnecting network performance. Due to the advances being made in computational science and engineering, the applications that run on these machines involve complex multiscale or multiphase physics, adaptive meshes and/or sophisticated numerical methods. A key challenge for scientific computing is obtaining high performance for these advanced applications on such complicated computers and, thus, to enable scientific simulations on a scale heretofore impossible. A typical model in computational science is expressed using the language of continuous mathematics, such as partial differential equations and linear algebra, but techniques from discrete or combinatorial mathematics also play an important role in solving these models efficiently. Several discrete combinatorial problems and data structures, such as graph and hypergraph partitioning, supernodes and elimination trees, vertex and edge reordering, vertex and edge coloring, and bipartite graph matching, arise in these contexts. As an example, parallel partitioning tools can be used to ease the task of distributing the computational workload across the processors. The computation of such problems can be represented as a composition of graphs and multilevel graph problems that have to be mapped to different microprocessors"--$$cProvided by publisher. 000906817 650_0 $$aComputer programming. 000906817 650_0 $$aScience$$xData processing. 000906817 650_0 $$aCombinatorial analysis. 000906817 7001_ $$aNaumann, Uwe,$$d1969- 000906817 7001_ $$aSchenk, Olaf,$$d1967- 000906817 830_0 $$aChapman & Hall/CRC computational science series. 000906817 852__ $$bebk 000906817 85640 $$3ProQuest Ebook Central Academic Complete$$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=870689$$zOnline Access 000906817 909CO $$ooai:library.usi.edu:906817$$pGLOBAL_SET 000906817 980__ $$aEBOOK 000906817 980__ $$aBIB 000906817 982__ $$aEbook 000906817 983__ $$aOnline