Table Of ContentSPRINGER BRIEFS IN APPLIED SCIENCES AND
TECHNOLOGY COMPUTATIONAL INTELLIGENCE
Jameel Ahmed
Mohammed Yakoob Siyal
Shaheryar Najam
Zohaib Najam
Fuzzy Logic
Based Power-
Efficient Real-
Time Multi-Core
System
123
SpringerBriefs in Applied Sciences
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Computational Intelligence
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Jameel Ahmed Mohammed Yakoob Siyal
(cid:129)
Shaheryar Najam Zohaib Najam
(cid:129)
Fuzzy Logic Based
fi
Power-Ef cient Real-Time
Multi-Core System
123
Jameel Ahmed Shaheryar Najam
FacultyofEngineeringandAppliedScience FacultyofEngineeringandAppliedScience
RiphahInternational University RiphahInternational University
Islamabad Islamabad
Pakistan Pakistan
Mohammed Yakoob Siyal ZohaibNajam
Schoolof Electrical andElectronic FacultyofEngineeringandAppliedScience
Engineering RiphahInternational University
NanyangTechnological University Islamabad
Singapore Pakistan
Singapore
ISSN 2191-530X ISSN 2191-5318 (electronic)
SpringerBriefs inApplied SciencesandTechnology
ISBN978-981-10-3119-9 ISBN978-981-10-3120-5 (eBook)
DOI 10.1007/978-981-10-3120-5
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Preface
Reconfigurablemulti-corearchitecturehasbeenthecenterofinterestforlargebody
of researcher. This is because that the large amount of parallelism offered by
multi-core architecture often is underutilized and becomes liability instead of
advantage. An ideal system would be capable offinding optimal settings of recon-
figurable parameters to efficiently utilize resources and balance the performance to
power ratio. Increasing demand for processors with better performance has been
motivatingdesignerstoincreaseresourcesandparallelismofferedbyprocessors,but
duetotheincreaseinpowerconsumptionandheatdissipation,incurrentage,there
isa great need for efficient utilization of resources and parallelism aswell.
Various challenges are impelled on system architecture due to its
resource-constrained nature. On the other hand, different limitations of reconfigu-
rationsettingsanddynamicworkloadnatureofprocessorapplicationsmakeitmuch
more challenging to balance the performance to power ratio. Furthermore, due to
memory access and its latency, minimumconfiguration is not the optimal configu-
rationforefficientpowerconsumptionandutilizationofresources.Therefore,there
is a need of smart processors that is capable of efficiently utilizing parallelism and
resources,keeping a balancebetweenpower consumptionandperformance.
This book focuses on identifying the performance challenges of computer
architecture and optimal configuration settings and analyzing their impact on the
performance of multi-core architecture. For this purpose, a thorough literature
survey has been performed to identify the issues affecting the performance and
power consumption of computer architectures. Then, to validate the impact of
identifiedchallengesfromtheliterature,afuzzylogicbasedreconfigurationengine
targeting to optimize the multi-core architecture to achieve a balance between
power and performance is presented. A fuzzy logic based real-time multi-core
architecture is capable of optimizing reconfigurable system to such level that
optimumresourceswouldbeallocatedaccordingtoworkloadandallunderutilized
resources remain inactive for better power saving.
On the basis of achieved results and literature review, recommendations are
made for better selection of reconfiguration setting regarding application nature in
the presence of considered challenges. In addition, this book covers a proposed
v
vi Preface
fuzzy logic based power and throughput aware reconfiguration for multiprocessor
systemonchip(MPSoC)inbothsimulationandreal-timeenvironment.Therefore,
the manuscript is divided into two major parts: simulation based power and
throughput aware fuzzy logics reconfiguration for multi-core architecture.
A detailed analysis has been carried out against the factors affecting power con-
sumption and performance of MPSoC, and results of fuzzy logic based reconfig-
uration engine have been presented. The second part proposed real-time
implementations of fuzzy logic based power-efficient reconfigurable multi-core
architecture for Intel and Leone3 processors.
This book consists of five chapters. Chapter 1 introduces the type of micro-
processors with examples, and working and polices of cache memory. Chapter 2
explainstheenergy-delayproduct,animportantevaluatingparameterforbalancing
power to performance ratio, along with energy of multilevel cache, multiple cores
andthroughputofmultiplecores.Chapter3highlightstheissuesandchallengesin
moderncomputerarchitecturealongwiththeavailablesolutions.Chapter4presents
the real-time power and performance aware system for INTEL and LEON3
architecture, detailed fuzzy logic controller designed for balancing power to per-
formance ratio and results of fuzzy logic based power and performance aware
system against someoftheavailable techniques. Chapter5enunciatesindetailthe
fuzzy logic and its fuzzifier, inference, and deffuzzifier modules.
Islamabad, Pakistan Jameel Ahmed
Singapore, Singapore Mohammed Yakoob Siyal
Islamabad, Pakistan Shaheryar Najam
Islamabad, Pakistan Zohaib Najam
Contents
1 Multiprocessors and Cache Memory. .... .... .... .... ..... .... 1
1.1 Overview . .... .... ..... .... .... .... .... .... ..... .... 1
1.1.1 Single Processor to Multiprocessors ... .... ..... .... 2
1.1.2 General-Purpose Processors.. .... .... .... ..... .... 2
1.1.3 Microcontroller ... .... .... .... .... .... ..... .... 3
1.1.4 Application-Specific Processors... .... .... ..... .... 3
1.1.5 Digital Signal Processors.... .... .... .... ..... .... 3
1.1.6 Application-Specific Instruction Processor... ..... .... 3
1.1.7 Graphic Processing Units ... .... .... .... ..... .... 3
1.1.8 Application-Specific Integrated Circuit . .... ..... .... 4
1.2 Embedded Multi-core Processor. .... .... .... .... ..... .... 4
1.2.1 Tilera Tile 64 .... .... .... .... .... .... ..... .... 5
1.2.2 Element CXI ECA-64.. .... .... .... .... ..... .... 6
1.2.3 Silicon Hive Hiveflex CSP2X00 Series. .... ..... .... 6
1.2.4 TI OMAP 4430-Mobile SOC .... .... .... ..... .... 7
1.2.5 NVIDIA G200.... .... .... .... .... .... ..... .... 7
1.2.6 Intel Core i7 ..... .... .... .... .... .... ..... .... 8
1.3 Cache Memory. .... ..... .... .... .... .... .... ..... .... 8
1.3.1 Principal of Locality ... .... .... .... .... ..... .... 9
1.3.2 Cache Block ..... .... .... .... .... .... ..... .... 9
1.3.3 Hit Rate.... ..... .... .... .... .... .... ..... .... 10
1.3.4 Miss Rate .. ..... .... .... .... .... .... ..... .... 10
1.3.5 Hit Time ... ..... .... .... .... .... .... ..... .... 10
1.3.6 Miss Penalty ..... .... .... .... .... .... ..... .... 10
1.3.7 Cache Organization.... .... .... .... .... ..... .... 11
1.3.8 Cache Memory Controller and Its Interaction
Policies .... ..... .... .... .... .... .... ..... .... 12
1.3.9 Cache’s Block Replacement Algorithm. .... ..... .... 14
References.. .... .... .... ..... .... .... .... .... .... ..... .... 15
vii
viii Contents
2 Energy-Delay Product and Throughput .. .... .... .... ..... .... 17
2.1 Overview . .... .... ..... .... .... .... .... .... ..... .... 17
2.2 Energy-Delay Product..... .... .... .... .... .... ..... .... 17
2.2.1 Energy of Caches . .... .... .... .... .... ..... .... 19
2.2.2 Energy of Cores .. .... .... .... .... .... ..... .... 20
2.2.3 Throughput of Cores... .... .... .... .... ..... .... 21
References.. .... .... .... ..... .... .... .... .... .... ..... .... 21
3 Challenges and Issues in Modern Computer Architectures .... .... 23
3.1 Overview . .... .... ..... .... .... .... .... .... ..... .... 23
3.1.1 Inefficient Utilization of Available Resources
and Parallelism ... .... .... .... .... .... ..... .... 23
3.1.2 Demand for High Performance Versus Power
and Heat Dissipation... .... .... .... .... ..... .... 24
3.1.3 Cache Coherency in Multi-core Architecture. ..... .... 25
3.1.4 Software Optimization.. .... .... .... .... ..... .... 25
3.1.5 Process Scheduling .... .... .... .... .... ..... .... 25
3.1.6 The Memory Wall. .... .... .... .... .... ..... .... 26
3.1.7 Contemporary Work ... .... .... .... .... ..... .... 26
References.. .... .... .... ..... .... .... .... .... .... ..... .... 28
4 Real-Time Power and Performance-Aware System.. .... ..... .... 31
4.1 Performance and Power Aware System ... .... .... ..... .... 31
4.2 Fuzzy Logic Based Power Efficient INTEL Architecture ... .... 32
4.2.1 INTEL Architecture.... .... .... .... .... ..... .... 32
4.2.2 Input Parameters .. .... .... .... .... .... ..... .... 32
4.2.3 Fuzzy Logic Controller. .... .... .... .... ..... .... 33
4.2.4 Reconfigurable Output Parameter . .... .... ..... .... 34
4.2.5 Results. .... ..... .... .... .... .... .... ..... .... 37
4.3 Fuzzy Logic Based Power and Energy Aware Leon3
Architecture ... .... ..... .... .... .... .... .... ..... .... 39
4.3.1 Leon3 Architecture .... .... .... .... .... ..... .... 39
4.3.2 Fuzzy Logic Controller for Leon3 .... .... ..... .... 39
4.3.3 Input Variables for Fuzzy Logic Controller.. ..... .... 40
4.3.4 Power Optimizing Techniques for Leon3 ... ..... .... 42
4.3.5 Results. .... ..... .... .... .... .... .... ..... .... 43
References.. .... .... .... ..... .... .... .... .... .... ..... .... 44
5 Fuzzy Logic Theory . .... ..... .... .... .... .... .... ..... .... 47
5.1 Introduction to Fuzzy Systems .. .... .... .... .... ..... .... 47
5.2 Fuzzy Sets .... .... ..... .... .... .... .... .... ..... .... 48
5.2.1 Basic Concepts in Fuzzy Set. .... .... .... ..... .... 49
5.2.2 Basic Operators in Fuzzy Set .... .... .... ..... .... 50
5.3 Fuzzy Relations .... ..... .... .... .... .... .... ..... .... 51
5.4 Fuzzy Composition Operation .. .... .... .... .... ..... .... 51
5.5 Projection of Fuzzy Relation ... .... .... .... .... ..... .... 51
Contents ix
5.6 Cylindrical Extension of Fuzzy Relation... .... .... ..... .... 52
5.7 Linguist Terms in Fuzzy System .... .... .... .... ..... .... 52
5.7.1 Linguistic Hedges . .... .... .... .... .... ..... .... 52
5.8 Fuzzy IF-THEN Rules .... .... .... .... .... .... ..... .... 52
5.8.1 Implication of Fuzzy IF-THEN Rules.. .... ..... .... 53
5.8.2 Generalized Modus Ponens in Fuzzy Systems..... .... 55
5.8.3 Fuzzy Rule Base Structure .. .... .... .... ..... .... 55
5.9 Fuzzy Inference Engine ... .... .... .... .... .... ..... .... 55
5.9.1 Composition-Based Inference .... .... .... ..... .... 56
5.9.2 Individual-Rule Based Inference .. .... .... ..... .... 56
5.9.3 Types of Inference Engines Used . .... .... ..... .... 56
5.10 Fuzzifiers . .... .... ..... .... .... .... .... .... ..... .... 57
5.11 Defuzzifier .... .... ..... .... .... .... .... .... ..... .... 57
5.11.1 Center of Gravity Defuzzifier .... .... .... ..... .... 58
5.11.2 Center Average Defuzzifier.. .... .... .... ..... .... 58
5.12 Membership Functions.... .... .... .... .... .... ..... .... 58
5.12.1 Triangular Membership Function.. .... .... ..... .... 59
5.12.2 Trapezoidal Membership Function. .... .... ..... .... 59
5.12.3 Gaussian Membership Function... .... .... ..... .... 60
5.12.4 Generalized Bell Membership Function. .... ..... .... 60
5.12.5 Sigmoid Membership Function ... .... .... ..... .... 61
References.. .... .... .... ..... .... .... .... .... .... ..... .... 62
