UNIVERSITY OF CALIFORNIA, SAN DIEGO Accurate Temperature Sensing and Efficient Dynamic ...

134 Pages·2013·10.46 MB·English

UNIVERSITY OF CALIFORNIA, SAN DIEGO
Accurate Temperature Sensing and E�cient Dynamic Thermal
Management in MPSoCs
A dissertation submitted in partial satisfaction of the
requirements for the degree
Doctor of Philosophy
in
Computer Science (Computer Engineering)
by
Shervin Sharifi
Committee in charge:
Professor Tajana Simunic Rosing, Chair
Professor Chung-Kuan Cheng
Professor Tara Javidi
Professor Ryan Kastner
Professor Joseph Pasquale
2011
Copyright
Shervin Sharifi, 2011
All rights reserved.
The dissertation of Shervin Sharifi is approved, and it is
acceptable in quality and form for publication on micro-
film and electronically:
Chair
University of California, San Diego
2011
iii
DEDICATION
To those who have dedicated their lives to me, Mom and Dad.
And to my dearest Avisha.
iv
TABLE OF CONTENTS
Signature Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
Table of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x
Vita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
Abstract of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . xv
Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Thesis Contributions . . . . . . . . . . . . . . . . . . . . 8
Chapter 2 Direct temperature sensing . . . . . . . . . . . . . . . . . . . . 12
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3 Analytical Model for Upper Bound of On-Chip Temper-
ature Di↵erences . . . . . . . . . . . . . . . . . . . . . . 16
2.4 Thermal Sensor Placement . . . . . . . . . . . . . . . . . 21
2.5 Experimental Results . . . . . . . . . . . . . . . . . . . . 23
2.5.1 Maximum Temperature Di↵erence Model . . . . . 23
2.5.2 Sensor Placement . . . . . . . . . . . . . . . . . . 26
2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Chapter 3 Indirect Temperature Sensing . . . . . . . . . . . . . . . . . . 33
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . 34
3.3 Components of Indirect Temperature Sensing . . . . . . . 36
3.3.1 KF-based Temperature Estimation . . . . . . . . 37
3.3.2 Reducing Computational Complexity . . . . . . . 40
3.3.3 Detecting Sensor Failure and Degradation . . . . 42
3.4 Experimental results . . . . . . . . . . . . . . . . . . . . 45
3.4.1 Indirect temperature sensing . . . . . . . . . . . 46
3.4.2 Detecting sensor failure and degradation . . . . . 51
3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 53
v
Chapter 4 Tempo Temperature Prediction . . . . . . . . . . . . . . . . . 57
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.2 Related work . . . . . . . . . . . . . . . . . . . . . . . . 58
4.3 Temperature Prediction . . . . . . . . . . . . . . . . . . . 60
4.3.1 Theoretical Analysis of Tempo . . . . . . . . . . . 66
4.4 Experimental results . . . . . . . . . . . . . . . . . . . . 71
4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Chapter 5 PROMETHEUS Framework for Temperature-aware Schedul-
ing on Heterogeneous MPSoCs . . . . . . . . . . . . . . . . . 76
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.2 Related work . . . . . . . . . . . . . . . . . . . . . . . . 78
5.3 PROMETHEUS Scheduling Framework . . . . . . . . . . 80
5.3.1 Power state assignment in TempoMP . . . . . . . 82
5.3.2 Power state assignment in TemPrompt . . . . . 87
5.3.3 Runtime task assignment to the cores . . . . . . . 89
5.4 Experimental results . . . . . . . . . . . . . . . . . . . . 90
5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Chapter 6 Conclusion and Future Work . . . . . . . . . . . . . . . . . . . 97
6.1 Thesis Summary . . . . . . . . . . . . . . . . . . . . . . 98
6.1.1 Analytical Model for Upper Bound on On-chip
Spatial Thermal Gradients . . . . . . . . . . . . . 98
6.1.2 Accurate Direct Temperature Sensing . . . . . . . 99
6.1.3 Accurate Indirect Temperature Sensing . . . . . . 100
6.1.4 Tempo Temperature Prediction . . . . . . . . . . 100
6.1.5 PROMETHEUS FrameworkforTemperature-aware
Scheduling in Heterogeneous MPSoCs . . . . . . . 101
6.2 Future Research Directions . . . . . . . . . . . . . . . . . 102
6.2.1 Thermal Management in Heterogeneous MPSoCs
with Special Purpose Cores . . . . . . . . . . . . 102
6.2.2 Thermal Management in Many-core MPSoCs . . . 103
Appendix A Compact Thermal Modeling . . . . . . . . . . . . . . . . . . . 105
A.1 Electrical Representation of Heat Transfer . . . . . . . . 105
A.2 Extracting the Parameters of the Thermal Network . . . 107
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
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LIST OF FIGURES
Figure 1.1: Scaling of (a) Transistor integration capacity (2) Frequency,
Vdd and power [12] . . . . . . . . . . . . . . . . . . . . . . . . 2
Figure 1.2: Distibution of (a) power density vs. (b) temperature across a
chip [67] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Figure 2.1: Contour map of maximum temperature di↵erence to a point of
interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Figure 2.2: Algorithm for calculating the upper bounds . . . . . . . . . . . 20
Figure 2.3: Layout of SoC2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Figure 2.4: Temperature di↵erence between points a and b . . . . . . . . . 25
Figure 2.5: Generating the maximum temperature di↵erence by construct-
ing the proper power trace . . . . . . . . . . . . . . . . . . . . . 26
Figure 2.6: Temperature di↵erence in the example of figure 2.5 . . . . . . . 27
Figure 2.7: Using observability area vs. circular range . . . . . . . . . . . 28
Figure 3.1: Proposedtechnique. (a)O✏inesetup(b)Runtimetemperature
estimation by KF . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Figure 3.2: Comparison of sensor, actual and estimated temperatures . . . 52
Figure 3.3: Run time of the technique on (a) XScale R (b) SPARCR . . . 54
� �
Figure 3.4: SPRT technique to detect sensor degradation . . . . . . . . . . 55
Figure 4.1: (a) Temperature of the core (b) Breakdown of temperature into
components of equation (4.7) (c) Temperature of corresponding
nodesinthermalinterfacematerial,heatspreaderandheatsink,
all relative to ambient . . . . . . . . . . . . . . . . . . . . . . . 62
Figure 4.2: Gershgorin discs of matrix �t in complex plane for (a) a high
s
end package and (b) an embedded-type package . . . . . . . . 68
Figure 4.3: Characteristics of the MPSoC . . . . . . . . . . . . . . . . . . 72
Figure 4.4: Comparison of Tempo and BLP predictor [10] . . . . . . . . . 73
Figure 5.1: Scheduling system in PROMETHEUS . . . . . . . . . . . . . . 80
Figure 5.2: O✏ine stage of TempoMP . . . . . . . . . . . . . . . . . . . . . 82
Figure 5.3: A very simple example describing use of multi-parametric pro-
gramming in power state assignment . . . . . . . . . . . . . . . 84
Figure 5.4: Comparison of Maximum Temperature . . . . . . . . . . . . . 91
Figure 5.5: Average lateness (seconds) . . . . . . . . . . . . . . . . . . . . . 92
Figure 5.6: Throughput (million instructions executed per second) . . . . . 93
Figure 5.7: Average power consumption . . . . . . . . . . . . . . . . . . . . 93
Figure 5.8: Average energy per billion instructions executed . . . . . . . . . 95
Figure 5.9: Average Energy Lateness Product (ELP) . . . . . . . . . . . . . 95
vii
Figure A.1: An example of a chip and package, together with their corre-
sponding thermal RC network . . . . . . . . . . . . . . . . . . 108
viii
LIST OF TABLES
Table 1.1: Examples of di↵erent classes of thermal management techniques 3
Table 2.1: Errors in temperature di↵erence simulations (oC) . . . . . . . . 28
Table 2.2: Number of sensors needed by our technique and range-based
methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Table 2.3: Error statistics for limited number of sensors . . . . . . . . . . . 30
Table 2.4: Error statistics for di↵erent time steps . . . . . . . . . . . . . . . 31
Table 3.1: E↵ectofnumberofmatchedmomentsontemperatureestimation
Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Table 3.2: E↵ects of sensor degradation and failure . . . . . . . . . . . . . 49
Table A.1: Duality between Thermal and Electrical Quantities . . . . . . . 107
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ACKNOWLEDGMENTS
The work presented in this thesis would not have been possible without the
help and support of wonderful people that I have had the privilege of interacting
with during my years at UC San Diego.
First and foremost, I would like to thank my advisor, Professor Tajana
SimunicRosingforherguidance, supportandthemanylessonsIhavelearnedfrom
her. I especially thank her for her understanding, support and patience during the
di�cult times I had. Without her help, I would not have been able to overcome
many technical and non-technical challenges. In addition, I really appreciate the
supportive and friendly environment she has created in our research group.
I really appreciate the e↵ort and the time my thesis committee members,
Professor Chung-Kuan Cheng, Professor Tara Javidi, Professor Ryan Kastner and
Professor Joseph Pasquale have taken to review my manuscript and conduct my
defense.
I have also been very lucky to have wonderful colleagues and friends in our
department and in our research group. I wish to thank them all for providing a
friendly and joyful environment and for their valuable comments and discussions.
Special thanks to Raid Ayoub, Yen-Kuan Wu, Ayse Coskun, Gaurav Dhiman,
EdoardoRegini, PritiAghera, NimaNikzad, BryanKim, YasharAsgarieh, Richard
Strong, Aruna Ravinagarajan, Jamie Bradley Steck and Giacomo Marchetti. I had
the privilege to collaborate with Raid Ayoub, Ayse Coskun, Dilip Krishnaswamy
and Chun-Chen Liu.
I have been very fortunate to have a wonderful group of friends in San
Diego. I sincerely thank them for their friendship, support and being my family
when I was far from my own family. I would like to especially thank Kambiz
Samadi, Amirali Shayan, Ahsan Samiee, Kiarash Kiantaj, Hamed Movahedpour,
Ehsan Ardestanizadeh, Haleh Azartash, Behrokh Farzad and Setareh Setayesh
among the others. We have shared many memorable moments which I will never
forget.
My utmost and deepest gratitude, a↵ection and love belong to my family,
especially my parents for their unconditional and endless love and support. I am
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