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Produktbild: Energy-Efficient Distributed Computing Systems

Energy-Efficient Distributed Computing Systems

Aus der Reihe Wiley Series on Parallel and Distributed Computing

179,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

21.08.2012

Herausgeber

Albert Y. Zomaya + weitere

Verlag

John Wiley & Sons Inc

Seitenzahl

856

Maße (L/B/H)

23,6/16,3/5,1 cm

Gewicht

1279 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-90875-4

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

21.08.2012

Herausgeber

Verlag

John Wiley & Sons Inc

Seitenzahl

856

Maße (L/B/H)

23,6/16,3/5,1 cm

Gewicht

1279 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-90875-4

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Energy-Efficient Distributed Computing Systems
  • PREFACE xxix
     
    ACKNOWLEDGMENTS xxxi
     
    CONTRIBUTORS xxxiii
     
    1 POWER ALLOCATION AND TASK SCHEDULING ON MULTIPROCESSOR COMPUTERS WITH ENERGY AND TIME CONSTRAINTS 1
    Keqin Li
     
    1.1 Introduction 1
     
    1.2 Preliminaries 5
     
    1.3 Problem Analysis 10
     
    1.4 Pre-Power-Determination Algorithms 16
     
    1.5 Post-Power-Determination Algorithms 28
     
    1.6 Summary and Further Research 33
     
    References 34
     
    2 POWER-AWARE HIGH PERFORMANCE COMPUTING 39
    Rong Ge and Kirk W. Cameron
     
    2.1 Introduction 39
     
    2.2 Background 41
     
    2.3 Related Work 45

    2.4 PowerPack: Fine-Grain Energy Profiling of HPC Applications 48
     
    2.5 Power-Aware Speedup Model 59
     
    2.6 Model Usages 69
     
    2.7 Conclusion 73
     
    References 75
     
    3 ENERGY EFFICIENCY IN HPC SYSTEMS 81
    Ivan Rodero and Manish Parashar
     
    3.1 Introduction 81
     
    3.2 Background and Related Work 83
     
    3.3 Proactive, Component-Based Power Management 88
     
    3.4 Quantifying Energy Saving Possibilities 91
     
    3.5 Evaluation of the Proposed Strategies 95
     
    3.6 Results 97
     
    3.7 Concluding Remarks 102
     
    3.8 Summary 103
     
    References 104
     
    4 A STOCHASTIC FRAMEWORK FOR HIERARCHICAL SYSTEM-LEVEL POWER MANAGEMENT 109
    Peng Rong and Massoud Pedram
     
    4.1 Introduction 109
     
    4.2 Related Work 111
     
    4.3 A Hierarchical DPM Architecture 113
     
    4.4 Modeling 114
     
    4.5 Policy Optimization 122
     
    4.6 Experimental Results 125
     
    4.7 Conclusion 130
     
    References 130
     
    5 ENERGY-EFFICIENT RESERVATION INFRASTRUCTURE FOR GRIDS, CLOUDS, AND NETWORKS 133
    Anne-Ce´ cile Orgerie and Laurent Lefe` vre
     
    5.1 Introduction 133
     
    5.2 Related Works 134
     
    5.3 ERIDIS: Energy-Efficient Reservation Infrastructure for Large-Scale Distributed Systems 138
     
    5.4 EARI: Energy-Aware Reservation Infrastructure for Data Centers and Grids 147
     
    5.5 GOC: Green Open Cloud 149
     
    5.6 HERMES: High Level Energy-Aware Model for Bandwidth Reservation in End-To-End Networks 152
     
    5.7 Summary 158
     
    References 158
     
    6 ENERGY-EFFICIENT JOB PLACEMENT ON CLUSTERS, GRIDS, AND CLOUDS 163
    Damien Borgetto, Henri Casanova, Georges Da Costa, and Jean-Marc Pierson

    6.1 Problem and Motivation 163
     
    6.2 Energy-Aware Infrastructures 164
     
    6.3 Current Resource Management Practices 167
     
    6.4 Scientific and Technical Challenges 170
     
    6.5 Energy-Aware Job Placement Algorithms 172
     
    6.6 Discussion 180
     
    6.7 Conclusion 183
     
    References 184
     
    7 COMPARISON AND ANALYSIS OF GREEDY ENERGY-EFFICIENT SCHEDULING ALGORITHMS FOR COMPUTATIONAL GRIDS 189
    Peder Lindberg, James Leingang, Daniel Lysaker, Kashif Bilal, Samee Ullah Khan, Pascal Bouvry, Nasir Ghani, Nasro Min-Allah, and Juan Li
     
    7.1 Introduction 189
     
    7.2 Problem Formulation 191
     
    7.3 Proposed Algorithms 193
     
    7.4 Simulations, Results, and Discussion 203
     
    7.5 Related Works 211
     
    7.6 Conclusion 211
     
    References 212
     
    8 TOWARD ENERGY-AWARE SCHEDULING USING MACHINE LEARNING 215
    Josep LL. Berral, In~ igo Goiri, Ramon Nou, Ferran Julia` , Josep O. Fito´ , Jordi Guitart, Ricard Gavalda´ , and Jordi Torres
     
    8.1 Introduction 215
     
    8.2 Intelligent Self-Management 218
     
    8.3 Introducing Power-Aware Approaches 225

    8.4 Experiences of Applying ML on Power-Aware Self-Management 230
     
    8.5 Conclusions on Intelligent Power-Aware Self-Management 238
     
    References 240