00894nam0 2200289 450 00002429320090312101000.088-453-0705-020090312d1994----km-y0itay50------baitaITy-------001yyLetture di macroeconomiaa cura di Franco Spinelli e Guido TabelliniMilanoEtaslibri1994X, 325 p.24 cmEconomiaAnalisi e teoria economica2001EconomiaLetture di macroeconomia59899Macroeconomia33920Macroeconomia e argomenti connessiTabellini,GuidoSpinelli,Franco<1949- >ITUNIPARTHENOPE20090312RICAUNIMARC000024293023/2617526NAVA22009Letture di macroeconomia59899UNIPARTHENOPE05544nam 2200709 a 450 991101936100332120200520144314.09786610901098978128090109612809010989780470121177047012117397804701211600470121165(CKB)1000000000355070(EBL)297311(OCoLC)476071527(SSID)ssj0000255638(PQKBManifestationID)11195823(PQKBTitleCode)TC0000255638(PQKBWorkID)10217254(PQKB)11514517(MiAaPQ)EBC297311(Perlego)2776941(EXLCZ)99100000000035507020061103d2007 uy 0engur|n|---|||||txtccrTask scheduling for parallel systems /Oliver SinnenHoboken, N.J. Wiley-Intersciencec20071 online resource (314 p.)Wiley series on parallel and distributed computingDescription based upon print version of record.9780471735762 0471735760 Includes bibliographical references (p. 269-280) and indexes.TASK SCHEDULING FOR PARALLEL SYSTEMS; CONTENTS; Preface; Acknowledgments; 1. Introduction; 1.1 Overview; 1.2 Organization; 2. Parallel Systems and Programming; 2.1 Parallel Architectures; 2.1.1 Flynn's Taxonomy; 2.1.2 Memory Architectures; 2.1.3 Programming Paradigms and Models; 2.2 Communication Networks; 2.2.1 Static Networks; 2.2.2 Dynamic Networks; 2.3 Parallelization; 2.4 Subtask Decomposition; 2.4.1 Concurrency and Granularity; 2.4.2 Decomposition Techniques; 2.4.3 Computation Type and Program Formulation; 2.4.4 Parallelization Techniques; 2.4.5 Target Parallel System2.5 Dependence Analysis2.5.1 Data Dependence; 2.5.2 Data Dependence in Loops; 2.5.3 Control Dependence; 2.6 Concluding Remarks; 2.7 Exercises; 3. Graph Representations; 3.1 Basic Graph Concepts; 3.1.1 Computer Representation of Graphs; 3.1.2 Elementary Graph Algorithms; 3.2 Graph as a Program Model; 3.2.1 Computation and Communication Costs; 3.2.2 Comparison Criteria; 3.3 Dependence Graph (DG); 3.3.1 Iteration Dependence Graph; 3.3.2 Summary; 3.4 Flow Graph (FG); 3.4.1 Data-Driven Execution Model; 3.4.2 Summary; 3.5 Task Graph (DAG); 3.5.1 Graph Transformations and Conversions3.5.2 Motivations and Limitations3.5.3 Summary; 3.6 Concluding Remarks; 3.7 Exercises; 4. Task Scheduling; 4.1 Fundamentals; 4.2 With Communication Costs; 4.2.1 Schedule Example; 4.2.2 Scheduling Complexity; 4.3 Without Communication Costs; 4.3.1 Schedule Example; 4.3.2 Scheduling Complexity; 4.4 Task Graph Properties; 4.4.1 Critical Path; 4.4.2 Node Levels; 4.4.3 Granularity; 4.5 Concluding Remarks; 4.6 Exercises; 5. Fundamental Heuristics; 5.1 List Scheduling; 5.1.1 Start Time Minimization; 5.1.2 With Dynamic Priorities; 5.1.3 Node Priorities; 5.2 Scheduling with Given Processor Allocation5.2.1 Phase Two5.3 Clustering; 5.3.1 Clustering Algorithms; 5.3.2 Linear Clustering; 5.3.3 Single Edge Clustering; 5.3.4 List Scheduling as Clustering; 5.3.5 Other Algorithms; 5.4 From Clustering to Scheduling; 5.4.1 Assigning Clusters to Processors; 5.4.2 Scheduling on Processors; 5.5 Concluding Remarks; 5.6 Exercises; 6. Advanced Task Scheduling; 6.1 Insertion Technique; 6.1.1 List Scheduling with Node Insertion; 6.2 Node Duplication; 6.2.1 Node Duplication Heuristics; 6.3 Heterogeneous Processors; 6.3.1 Scheduling; 6.4 Complexity Results; 6.4.1 α|β|γ Classification6.4.2 Without Communication Costs6.4.3 With Communication Costs; 6.4.4 With Node Duplication; 6.4.5 Heterogeneous Processors; 6.5 Genetic Algorithms; 6.5.1 Basics; 6.5.2 Chromosomes; 6.5.3 Reproduction; 6.5.4 Selection, Complexity, and Flexibility; 6.6 Concluding Remarks; 6.7 Exercises; 7. Communication Contention in Scheduling; 7.1 Contention Awareness; 7.1.1 End-Point Contention; 7.1.2 Network Contention; 7.1.3 Integrating End-Point and Network Contention; 7.2 Network Model; 7.2.1 Topology Graph; 7.2.2 Routing; 7.2.3 Scheduling Network Model; 7.3 Edge Scheduling7.3.1 Scheduling Edge on RouteA new model for task scheduling that dramatically improves the efficiency of parallel systems Task scheduling for parallel systems can become a quagmire of heuristics, models, and methods that have been developed over the past decades. The author of this innovative text cuts through the confusion and complexity by presenting a consistent and comprehensive theoretical framework along with realistic parallel system models. These new models, based on an investigation of the concepts and principles underlying task scheduling, take into account heterogeneity, contention for communication rWiley series on parallel and distributed computing.Parallel processing (Electronic computers)Computer multitaskingComputer schedulingParallel processing (Electronic computers)Computer multitasking.Computer scheduling.004/.35Sinnen Oliver1971-1839421MiAaPQMiAaPQMiAaPQBOOK9911019361003321Task scheduling for parallel systems4418638UNINA