Multicore Computing: Algorithms, Architectures, and Applications

451 Pages·2013·11.71 MB·English

by  Sanguthevar Rajasekaran

Computer Science/Computer Engineering/Computing
M Chapman & Hall/CRC
Chapman & Hall/CRC
Computer & Information Science Series
Computer & Information Science Series
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Multicore Computing: Algorithms, Architectures, and Applications
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focuses on the architectures, algorithms, and applications of multicore Multicore
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computing. It will help you understand the intricacies of these architectures
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and prepare you to design efficient multicore algorithms.
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Contributors at the forefront of the field cover the memory hierarchy for
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multicore and manycore processors, the caching strategy Flexible Set
Computing
Balancing, the main features of the latest SPARC architecture specifi-
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cation, the Cilk and Cilk++ programming languages, the numerical soft-
ware library Parallel Linear Algebra Software for Multicore Architectures
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(PLASMA), and the exact multipattern string matching algorithm of Aho-
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Corasick. They also describe the architecture and programming model of
Algorithms, Architectures,
the NVIDIA Tesla GPU, discuss scheduling directed acyclic graphs onto
multi/manycore processors, and evaluate design trade-offs among Intel p
and Applications
and AMD multicore processors, IBM Cell Broadband Engine, and NVIDIA
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GPUs. In addition, the book explains how to design algorithms for the Cell
Broadband Engine and how to use the backprojection algorithm for gen- t
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erating images from synthetic aperture radar data.
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Features
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• Equips you with the foundation to design efficient multicore
algorithms Edited by
• Addresses challenges in parallel computing
Sanguthevar Rajasekaran
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• Covers many techniques, tools, and algorithms for solving big data
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problems, including PLASMA, Cilk, the Aho-Corasick algorithm, h ja
m s Lance Fiondella
sorting algorithms, a modularized scheduling method, and the e
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backprojection algorithm d a
, r Mohamed Ahmed
• Describes various architectures, such as SPARC and the NVIDIA a a
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Tesla GPU d ,
F Reda A. Ammar
• Includes numerous applications and extensive experimental results A i
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K12518 a
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K12518_Cover.indd 1 11/13/13 9:21 AM

Multicore
Computing
Algorithms, Architectures,
and Applications
CHAPMAN & HALL/CRC
COMPUTER and INFORMATION SCIENCE SERIES
Series Editor: Sartaj Sahni
PUBLISHED TITLES HANDBOOK OF PARALLEL COMPUTING: MODELS, ALGORITHMS
AND APPLICATIONS
ADVERSARIAL REASONING: COMPUTATIONAL
Sanguthevar Rajasekaran and John Reif
APPROACHES TO READING THE OPPONENT’S MIND
HANDBOOK OF REAL-TIME AND EMBEDDED SYSTEMS
Alexander Kott and William M. McEneaney
Insup Lee, Joseph Y-T. Leung, and Sang H. Son
DELAUNAY MESH GENERATION
HANDBOOK OF SCHEDULING: ALGORITHMS, MODELS, AND
Siu-Wing Cheng, Tamal Krishna Dey, and
PERFORMANCE ANALYSIS
Jonathan Richard Shewchuk
Joseph Y.-T. Leung
DISTRIBUTED SENSOR NETWORKS, SECOND EDITION
HIGH PERFORMANCE COMPUTING IN REMOTE SENSING
S. Sitharama Iyengar and Richard R. Brooks
Antonio J. Plaza and Chein-I Chang
DISTRIBUTED SYSTEMS: AN ALGORITHMIC APPROACH
HUMAN ACTIVITY RECOGNITION: USING WEARABLE SENSORS
Sukumar Ghosh
AND SMARTPHONES
ENERGY-AWARE MEMORY MANAGEMENT FOR EMBEDDED
Miguel A. Labrador and Oscar D. Lara Yejas
MULTIMEDIA SYSTEMS: A COMPUTER-AIDED DESIGN APPROACH
INTRODUCTION TO NETWORK SECURITY
Florin Balasa and Dhiraj K. Pradhan
Douglas Jacobson
ENERGY EFFICIENT HARDWARE-SOFTWARE
LOCATION-BASED INFORMATION SYSTEMS:
CO-SYNTHESIS USING RECONFIGURABLE HARDWARE
DEVELOPING REAL-TIME TRACKING APPLICATIONS
Jingzhao Ou and Viktor K. Prasanna
Miguel A. Labrador, Alfredo J. Pérez, and Pedro M. Wightman
FUNDAMENTALS OF NATURAL COMPUTING: BASIC CONCEPTS,
METHODS IN ALGORITHMIC ANALYSIS
ALGORITHMS, AND APPLICATIONS
Vladimir A. Dobrushkin
Leandro Nunes de Castro
MULTICORE COMPUTING: ALGORITHMS, ARCHITECTURES,
HANDBOOK OF ALGORITHMS FOR WIRELESS NETWORKING AND
AND APPLICATIONS
MOBILE COMPUTING
Sanguthevar Rajasekaran, Lance Fiondella, Mohamed Ahmed,
Azzedine Boukerche
and Reda A. Ammar
HANDBOOK OF APPROXIMATION ALGORITHMS
PERFORMANCE ANALYSIS OF QUEUING AND COMPUTER
AND METAHEURISTICS
NETWORKS
Teofilo F. Gonzalez
G. R. Dattatreya
HANDBOOK OF BIOINSPIRED ALGORITHMS
THE PRACTICAL HANDBOOK OF INTERNET COMPUTING
AND APPLICATIONS
Munindar P. Singh
Stephan Olariu and Albert Y. Zomaya
SCALABLE AND SECURE INTERNET SERVICES AND ARCHITECTURE
HANDBOOK OF COMPUTATIONAL MOLECULAR BIOLOGY
Cheng-Zhong Xu
Srinivas Aluru
SOFTWARE APPLICATION DEVELOPMENT: A VISUAL C++®, MFC,
HANDBOOK OF DATA STRUCTURES AND APPLICATIONS
AND STL TUTORIAL
Dinesh P. Mehta and Sartaj Sahni
Bud Fox, Zhang Wenzu, and Tan May Ling
HANDBOOK OF DYNAMIC SYSTEM MODELING
SPECULATIVE EXECUTION IN HIGH PERFORMANCE COMPUTER
Paul A. Fishwick
ARCHITECTURES
HANDBOOK OF ENERGY-AWARE AND GREEN COMPUTING
David Kaeli and Pen-Chung Yew
Ishfaq Ahmad and Sanjay Ranka
VEHICULAR NETWORKS: FROM THEORY TO PRACTICE
Stephan Olariu and Michele C. Weigle
Multicore
Computing
Algorithms, Architectures,
and Applications
Edited by
Sanguthevar Rajasekaran
Lance Fiondella
Mohamed Ahmed
Reda A. Ammar
CRC Press
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© 2014 by Taylor & Francis Group, LLC
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Version Date: 20130808
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Dedication
To my teachers,
Esakki Rajan, P.S. Srinivasn, V. Krishnan, and John H. Reif
—Sanguthevar Rajasekaran
To my son,
Advika
—Lance Fiondella
To my wife,
Noha Nabawi
my parents, and my advisors
Professors Sanguthevar Rajasekaran and Reda Ammar
—Mohamed F. Ahmed
To my family,
Tahany Fergany, Rabab Ammar, Doaa Ammar and Mohamed
Ammar
—Reda A. Ammar
( ; - : )

An indestructible and impeccable treasure to one is learning;
all the other things are not wealth.

Thiruvalluvar (circa 100 B.C.)
(Thirukkural; Section - Wealth; Chapter 40 - Education)
Contents
Preface xvii
Acknowledgements xxi
List of Contributing Editors xxiii
List of Contributing Authors xxv
1 MemoryHierarchyforMulticoreandMany-CoreProcessors 1
Mohamed Zahran and Bushra Ahsan
1.1 Design Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.1.1 Latency and Bandwidth . . . . . . . . . . . . . . . . . 5
1.1.2 Power Consumption . . . . . . . . . . . . . . . . . . . 6
1.2 Physical Memory . . . . . . . . . . . . . . . . . . . . . . . . 7
1.3 Cache Hierarchy Organization . . . . . . . . . . . . . . . . . 8
1.3.1 Caches versus Cores . . . . . . . . . . . . . . . . . . . 9
1.3.1.1 Technological and usage factors . . . . . . . 9
1.3.1.2 Application-related factors . . . . . . . . . . 9
1.3.2 Private, Shared, and Cooperative Caching . . . . . . . 11
1.3.3 Nonuniform Cache Architecture (NUCA) . . . . . . . 13
1.4 Cache Hierarchy Sharing . . . . . . . . . . . . . . . . . . . . 16
1.4.1 At What Level to Share Caches? . . . . . . . . . . . . 17
1.4.2 Cache-Sharing Management . . . . . . . . . . . . . . . 18
1.4.2.1 Fairness . . . . . . . . . . . . . . . . . . . . . 18
1.4.2.2 Quality of Service (QoS) . . . . . . . . . . . 20
1.4.3 Configurable Caches . . . . . . . . . . . . . . . . . . . 21
1.5 Cache Hierarchy Optimization . . . . . . . . . . . . . . . . . 23
1.5.1 Multilevel Inclusion . . . . . . . . . . . . . . . . . . . 23
1.5.2 Global Placement. . . . . . . . . . . . . . . . . . . . . 25
1.6 Cache Coherence . . . . . . . . . . . . . . . . . . . . . . . . . 28
1.6.1 Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
1.6.2 Protocols for Traditional Multiprocessors . . . . . . . 31
1.6.3 Protocols for Multicore Systems . . . . . . . . . . . . 32
1.7 Support for Memory Consistency Models . . . . . . . . . . . 36
1.8 Cache Hierarchy in Light of New Technologies . . . . . . . . 37
1.9 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . 37
vii
viii
2 FSB: A Flexible Set-Balancing Strategy for Last-Level
Caches 45
Mohammad Hammoud, Sangyeun Cho, and Rami Melhem
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
2.2 Motivation and Background . . . . . . . . . . . . . . . . . . 48
2.2.1 Baseline Architecture . . . . . . . . . . . . . . . . . . 48
2.2.2 A Caching Problem . . . . . . . . . . . . . . . . . . . 49
2.2.3 Dynamic Set-Balancing Cache and Inherent Shortcom-
ings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.2.4 Our Solution . . . . . . . . . . . . . . . . . . . . . . . 52
2.3 Flexible Set Balancing . . . . . . . . . . . . . . . . . . . . . . 54
2.3.1 Retention Limits . . . . . . . . . . . . . . . . . . . . . 54
2.3.2 Retention Policy . . . . . . . . . . . . . . . . . . . . . 55
2.3.3 Lookup Policy . . . . . . . . . . . . . . . . . . . . . . 57
2.3.4 FSB Cost . . . . . . . . . . . . . . . . . . . . . . . . . 57
2.4 Quantitative Evaluation . . . . . . . . . . . . . . . . . . . . . 58
2.4.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . 58
2.4.2 Comparing FSB against Shared Baseline . . . . . . . . 59
2.4.3 Sensitivity to Different Pressure Functions . . . . . . . 62
2.4.4 Sensitivity to LPL and HPL. . . . . . . . . . . . . . . 63
2.4.5 Impact of Increasing Cache Size and Associativity . . 64
2.4.6 FSB versus Victim Caching . . . . . . . . . . . . . . . 66
2.4.7 FSB versus DSBC and V-WAY . . . . . . . . . . . . . 66
2.5 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 67
2.6 Conclusions and Future Work . . . . . . . . . . . . . . . . . 69
3 The SPARC Processor Architecture 73
Simone Secchi, Antonino Tumeo, and Oreste Villa
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.2 The SPARC Instruction-Set Architecture . . . . . . . . . . . 75
3.2.1 Registers and Register Windowing . . . . . . . . . . . 76
3.3 Memory Access . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.3.1 MMU Requirements . . . . . . . . . . . . . . . . . . . 79
3.3.2 Memory Models . . . . . . . . . . . . . . . . . . . . . 79
3.3.3 The MEMBAR instruction . . . . . . . . . . . . . . . 81
3.4 Synchronization . . . . . . . . . . . . . . . . . . . . . . . . . 81
3.5 The NIAGARA Processor Architecture . . . . . . . . . . . . 82
3.6 Core Microarchitecture . . . . . . . . . . . . . . . . . . . . . 84
3.7 Core Interconnection . . . . . . . . . . . . . . . . . . . . . . 86
3.8 Memory Subsystem . . . . . . . . . . . . . . . . . . . . . . . 86
3.8.1 Cache-Coherence Protocol . . . . . . . . . . . . . . . . 87
3.8.1.1 Example 1 . . . . . . . . . . . . . . . . . . . 87
3.8.1.2 Example 2 . . . . . . . . . . . . . . . . . . . 88
3.9 Niagara Evolutions . . . . . . . . . . . . . . . . . . . . . . . 88