LEADER 05630nam 2200733 a 450 001 9910817504703321 005 20230120011946.0 010 $a1-280-77921-7 010 $a9786613689603 010 $a0-12-391443-4 035 $a(CKB)2670000000212662 035 $a(EBL)947407 035 $a(OCoLC)798575627 035 $a(SSID)ssj0000693536 035 $a(PQKBManifestationID)12276844 035 $a(PQKBTitleCode)TC0000693536 035 $a(PQKBWorkID)10667185 035 $a(PQKB)10962368 035 $a(Au-PeEL)EBL947407 035 $a(CaPaEBR)ebr10574665 035 $a(CaONFJC)MIL368960 035 $a(CaSebORM)9780124159938 035 $a(MiAaPQ)EBC947407 035 $a(OCoLC)820028384 035 $a(OCoLC)ocn820028384 035 $a(EXLCZ)992670000000212662 100 $a20120711d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStructured parallel programming $epatterns for efficient computation /$fMichael McCool, Arch D. Robison, James Reinders 205 $a1st edition 210 $aAmsterdam ;$aBoston, Mass. $cElsevier/Morgan Kaufmann$d2012 215 $a1 online resource (433 p.) 300 $aDescription based upon print version of record. 311 $a0-12-415993-1 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Structured Parallel Programming: Patterns for Efficient Computation; Copyright; Table of Contents; Listings; Preface; Preliminaries; 1 Introduction; 1.1 Think Parallel; 1.2 Performance; 1.3 Motivation: Pervasive Parallelism; 1.3.1 Hardware Trends Encouraging Parallelism; 1.3.2 Observed Historical Trends in Parallelism; 1.3.3 Need for Explicit Parallel Programming; 1.4 Structured Pattern-Based Programming; 1.5 Parallel Programming Models; 1.5.1 Desired Properties; 1.5.2 Abstractions Instead of Mechanisms; 1.5.3 Expression of Regular Data Parallelism; 1.5.4 Composability 327 $a1.5.5 Portability of Functionality1.5.6 Performance Portability; 1.5.7 Safety, Determinism, and Maintainability; 1.5.8 Overview of Programming Models Used; Cilk Plus; Threading Building Blocks (TBB); OpenMP; Array Building Blocks (ArBB); OpenCL; 1.5.9 When to Use Which Model?; 1.6 Organization of this Book; 1.7 Summary; 2 Background; 2.1 Vocabulary and Notation; 2.2 Strategies; 2.3 Mechanisms; 2.4 Machine Models; 2.4.1 Machine Model; Instruction Parallelism; Memory Hierarchy; Virtual Memory; Multiprocessor Systems; Attached Devices; 2.4.2 Key Features for Performance; Data Locality 327 $aParallel Slack2.4.3 Flynn's Characterization; 2.4.4 Evolution; 2.5 Performance Theory; 2.5.1 Latency and Throughput; 2.5.2 Speedup, Efficiency, and Scalability; 2.5.3 Power; 2.5.4 Amdahl's Law; 2.5.5 Gustafson-Barsis' Law; 2.5.6 Work-Span Model; 2.5.7 Asymptotic Complexity; 2.5.8 Asymptotic Speedup and Efficiency; 2.5.9 Little's Formula; 2.6 Pitfalls; 2.6.1 Race Conditions; 2.6.2 Mutual Exclusion and Locks; 2.6.3 Deadlock; 2.6.4 Strangled Scaling; 2.6.5 Lack of Locality; 2.6.6 Load Imbalance; 2.6.7 Overhead; 2.7 Summary; I Patterns; 3 Patterns; 3.1 Nesting Pattern 327 $a3.2 Structured Serial Control Flow Patterns3.2.1 Sequence; 3.2.2 Selection; 3.2.3 Iteration; 3.2.4 Recursion; 3.3 Parallel Control Patterns; 3.3.1 Fork-Join; 3.3.2 Map; 3.3.3 Stencil; 3.3.4 Reduction; 3.3.5 Scan; 3.3.6 Recurrence; 3.4 Serial Data Management Patterns; 3.4.1 Random Read and Write; 3.4.2 Stack Allocation; 3.4.3 Heap Allocation; 3.4.4 Closures; 3.4.5 Objects; 3.5 Parallel Data Management Patterns; 3.5.1 Pack; 3.5.2 Pipeline; 3.5.3 Geometric Decomposition; 3.5.4 Gather; 3.5.5 Scatter; 3.6 Other Parallel Patterns; 3.6.1 Superscalar Sequences; 3.6.2 Futures 327 $a3.6.3 Speculative Selection3.6.4 Workpile; 3.6.5 Search; 3.6.6 Segmentation; 3.6.7 Expand; 3.6.8 Category Reduction; 3.6.9 Term Graph Rewriting; 3.7 Non-Deterministic Patterns; 3.7.1 Branch and Bound; 3.7.2 Transactions; 3.8 Programming Model Support for Patterns; 3.8.1 Cilk Plus; Nesting, Recursion, Fork-Join; Reduction; Map, Workpile; Scatter, Gather; 3.8.2 Threading Building Blocks; Nesting, Recursion, Fork-Join; Map; Workpile; Reduction; Scan; Pipeline; Speculative Selection, Branch and Bound; 3.8.3 OpenMP; Map, Workpile; Reduction; Fork-Join 327 $aStencil, Geometric Decomposition, Gather, Scatter 330 $aProgramming is now parallel programming. Much as structured programming revolutionized traditional serial programming decades ago, a new kind of structured programming, based on patterns, is relevant to parallel programming today. Parallel computing experts and industry insiders Michael McCool, Arch Robison, and James Reinders describe how to design and implement maintainable and efficient parallel algorithms using a pattern-based approach. They present both theory and practice, and give detailed concrete examples using multiple programming models. Examples are primarily given using two of 517 3 $aPatterns for efficient computation 606 $aParallel programming (Computer science) 606 $aStructured programming 615 0$aParallel programming (Computer science) 615 0$aStructured programming. 676 $a005.1 676 $a005.275 676 $a005.275 700 $aMcCool$b Michael$01694467 701 $aRobison$b Arch D$01694468 701 $aReinders$b James$0851755 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910817504703321 996 $aStructured parallel programming$94073073 997 $aUNINA LEADER 02835nam 2200589Ia 450 001 9910437983903321 005 20200520144314.0 010 $a4-431-54318-X 024 7 $a10.1007/978-4-431-54318-3 035 $a(CKB)2670000000535969 035 $a(EBL)1206381 035 $a(OCoLC)837552284 035 $a(SSID)ssj0000878522 035 $a(PQKBManifestationID)11532603 035 $a(PQKBTitleCode)TC0000878522 035 $a(PQKBWorkID)10814098 035 $a(PQKB)10777538 035 $a(DE-He213)978-4-431-54318-3 035 $a(MiAaPQ)EBC1206381 035 $a(PPN)169141276 035 $a(EXLCZ)992670000000535969 100 $a20130410d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA Bayesian analysis of QCD sum rules /$fPhilipp Gubler 205 $a1st ed. 2013. 210 $aTokyo ;$aNew York $cSpringer$dc2013 215 $a1 online resource (190 p.) 225 1 $aSpringer theses 300 $aDescription based upon print version of record. 311 $a4-431-54317-1 311 $a4-431-54696-0 320 $aIncludes bibliographical references. 327 $aIntroduction and Review -- Introduction -- Basic Properties of QCD -- Basics of QCD Sum Rules -- The Maximum Entropy Method -- Applications -- MEM Analysis of the ? Meson Sum Rule -- MEM Analysis of the Nucleon Sum Rule -- Quarkonium Spectra at finite Temperature from QCD Sum Rules and MEM.-  Concluding Remarks -- Summary, Conclusion and Outlook -- Appendix. 330 $aThe author develops a novel analysis method for QCD sum rules (QCDSR) by applying the maximum entropy method (MEM) to arrive at an analysis with less artificial assumptions than previously held. This is a first-time accomplishment in the field. In this thesis, a reformed MEM for QCDSR is formalized and is applied to the sum rules of several channels: the light-quark meson in the vector channel, the light-quark baryon channel with spin and isospin 1/2, and several quarkonium channels at both zero and finite temperatures. This novel technique of combining QCDSR with MEM is applied to the study of quarkonium in hot matter, which is an important probe of the quark-gluon plasma currently being created in heavy-ion collision experiments at RHIC and LHC. 410 0$aSpringer theses. 606 $aQuantum chromodynamics$xMathematics 606 $aBayesian statistical decision theory 615 0$aQuantum chromodynamics$xMathematics. 615 0$aBayesian statistical decision theory. 676 $a539.7548 700 $aGubler$b Philipp$0916028 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437983903321 996 $aA Bayesian Analysis of QCD Sum Rules$92053519 997 $aUNINA