00720nam0-22002531i-450-990002660290403321000266029FED01000266029(Aleph)000266029FED0100026602920000920d--------km-y0itay50------baENGMarketing Management and Administrative actionby Britt and BoydNew YorkMcGraw-HillBritt,Stewart Henderson370165Boyd,Harper W.ITUNINARICAUNIMARCBK9900026602904033214-0-41-TI806ECAECAMarketing Management and Administrative action430975UNINAING0102955nam 2200529 450 991081982180332120200520144314.03-11-055569-710.1515/9783110556674(CKB)4100000001502380(DE-B1597)483611(OCoLC)1020031101(DE-B1597)9783110556674(Au-PeEL)EBL5156684(CaPaEBR)ebr11497563(CaSebORM)9783110555691(MiAaPQ)EBC5156684(EXLCZ)99410000000150238020180206h20182018 uy 0engurcnu||||||||rdacontentrdamediardacarrierContext-aware computing /Ling FengBerlin, [Germany] ;Boston, [Massachusetts] :De Gruyter,2018.©20181 online resource (482 pages)Advances in Computer Science ;Volume 3Includes index.3-11-055568-9 3-11-055667-7 Frontmatter -- Preface / Feng, Ling -- Contents -- Acknowledgments -- Part I: Fundamental -- 1. Context-Aware Data Management Toward Ambient Intelligence -- Part II: Context -- 2. Modeling Context -- 3. Addressing Context Uncertainty -- 4. Acquiring Context -- 5. Protecting Context Privacy -- Part III: Context Awareness -- 6. Querying Context -- 7. Detecting Context Events -- 8. Energy Management in Context Querying -- 9. Context Query Efficiency Versus Expense -- Part IV: Context-Aware Data Management -- 10. Context-Aware Preference Querying -- 11. Analyzing Sensitivity of Answer Ordering Change -- 12. Explaining and Scrubbing Context-Aware Query Results -- 13. Context-Based Information Refinding -- Part V: Context-Aware Applications -- 14. A Context-Aware Ad-Hoc Meeting Planner Program -- 15. Context-Aware Learning -- 16. Context-Aware Management of Bilingual Aviation MRO Task Cards -- 17. FireVGuide: A Context-Aware Fire Victims Guide -- IndexThe book addresses the impact of ambient intelligence, particularly its user-centric context-awareness requirement on data management strategies and solutions. Techniques of conceptualizing, capturing, protecting, modelling, and querying context information, as well as context-aware data management application are discussed, making the book is an essential reference for computer scientists, information scientists and industrial engineers.Advances in computer science ;Volume 3.Context-aware computingContext-aware computing.004Feng Ling1605274Tsinghua University Press1605275MiAaPQMiAaPQMiAaPQBOOK9910819821803321Context-aware computing3930426UNINA05630nam 2200733 a 450 991081750470332120230120011946.01-280-77921-797866136896030-12-391443-4(CKB)2670000000212662(EBL)947407(OCoLC)798575627(SSID)ssj0000693536(PQKBManifestationID)12276844(PQKBTitleCode)TC0000693536(PQKBWorkID)10667185(PQKB)10962368(Au-PeEL)EBL947407(CaPaEBR)ebr10574665(CaONFJC)MIL368960(CaSebORM)9780124159938(MiAaPQ)EBC947407(OCoLC)820028384(OCoLC)ocn820028384 (EXLCZ)99267000000021266220120711d2012 uy 0engur|n|---|||||txtccrStructured parallel programming patterns for efficient computation /Michael McCool, Arch D. Robison, James Reinders1st editionAmsterdam ;Boston, Mass. Elsevier/Morgan Kaufmann20121 online resource (433 p.)Description based upon print version of record.0-12-415993-1 Includes bibliographical references and index.Front 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 Composability1.5.5 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 LocalityParallel 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 Pattern3.2 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 Futures3.6.3 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-JoinStencil, Geometric Decomposition, Gather, ScatterProgramming 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 ofPatterns for efficient computationParallel programming (Computer science)Structured programmingParallel programming (Computer science)Structured programming.005.1005.275005.275McCool Michael1694467Robison Arch D1694468Reinders James851755MiAaPQMiAaPQMiAaPQBOOK9910817504703321Structured parallel programming4073073UNINA