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010   $a981-13-9802-X
024 7 $a10.1007/978-981-13-9802-5
035   $a(CKB)4100000009757397
035   $a(MiAaPQ)EBC5915717
035   $a(DE-He213)978-981-13-9802-5
035   $a(PPN)260302813
035   $a(EXLCZ)994100000009757397
100   $a20191001d2019      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 14$aThe Art of High Performance Computing for Computational Science, Vol. 2 $eAdvanced Techniques and Examples for Materials Science /$fedited by Masaaki Geshi
205   $a1st ed. 2019.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2019.
215   $a1 online resource (IX, 206 p. 99 illus., 7 illus. in color.)
311   $a981-13-9801-1 
327   $aChapter 1: Supercomputers and application performance -- Chapter 2: Performance optimization of applications -- Chapter 3: Case studies of performance optimization of applications -- Chapter 4: O(N) methods -- Chapter 5: Acceleration of Classical Molecular Dynamics Simulations -- Chapter 6: Large scale quantum chemical calculation.
330   $aThis book presents advanced and practical techniques for performance optimization for highly parallel processing. Featuring various parallelization techniques in material science, it is a valuable resource for anyone developing software codes for computational sciences such as physics, chemistry, biology, earth sciences, space science, weather, disaster prevention and manufacturing, as well as for anyone using those software codes. Chapter 1 outlines supercomputers and includes a brief explanation of the history of hardware. Chapter 2 presents procedures for performance evaluation, while Chapter 3 describes the set of tuned applications in materials science, nanoscience and nanotechnology, earth science and engineering on the K computer. Introducing the order-N method, based on density functional theory (DFT) calculation, Chapter 4 explains how to extend the applicability of DFT to large-scale systems by reducing the computational complexity. Chapter 5 discusses acceleration and parallelization in classical molecular dynamics simulations, and lastly, Chapter 6 explains techniques for large-scale quantum chemical calculations, including the order-N method. This is the second of the two volumes that grew out of a series of lectures in the K computer project in Japan. The first volume addresses more basic techniques, and this second volume focuses on advanced and concrete techniques.
606   $aComputer programming
606   $aCheminformatics
606   $aComputer simulation
606   $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010
606   $aComputer Applications in Chemistry$3https://scigraph.springernature.com/ontologies/product-market-codes/C13009
606   $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000
615  0$aComputer programming.
615  0$aCheminformatics.
615  0$aComputer simulation.
615 14$aProgramming Techniques.
615 24$aComputer Applications in Chemistry.
615 24$aSimulation and Modeling.
676   $a005.11
702   $aGeshi$b Masaaki$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910350221003321
996   $aThe Art of High Performance Computing for Computational Science, Vol. 2$92547196
997   $aUNINA