Table Of ContentE-AMOM: AN ENERGY-AWARE MODELING AND
OPTIMIZATION METHODOLOGY FOR SCIENTIFIC
APPLICATIONS ON MULTICORE SYSTEMS
A Dissertation
by
CHARLES WESLEY LIVELY III
Submitted to the Office of Graduate Studies of
Texas A&M University
in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
May 2012
Major Subject: Computer Engineering
E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific
Applications on Multicore Systems
Copyright 2012 Charles Wesley Lively III
E-AMOM: AN ENERGY-AWARE MODELING AND
OPTIMIZATION METHODOLOGY FOR SCIENTIFIC
APPLICATIONS ON MULTICORE SYSTEMS
A Dissertation
by
CHARLES WESLEY LIVELY III
Submitted to the Office of Graduate Studies of
Texas A&M University
in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
Approved by:
Chair of Committee, Valerie Elaine Taylor
Committee Members, Karen Butler-Purry
Eun Jung Kim
Tiffani Williams
Head of Department, Duncan Walker
May 2012
Major Subject: Computer Engineering
iii
ABSTRACT
E-AMOM: An Energy-Aware Modeling and Optimization Methodology for Scientific
Applications on Multicore Systems. (May 2012)
Charles Wesley Lively III,
B.S.E., Mercer University;
M.S., Texas A&M University
Chair of Advisory Committee: Dr. Valerie Elaine Taylor
Power consumption is an important constraint in achieving efficient execution on
High Performance Computing Multicore Systems. As the number of cores available on
a chip continues to increase, the importance of power consumption will continue to
grow. In order to achieve improved performance on multicore systems scientific
applications must make use of efficient methods for reducing power consumption and
must further be refined to achieve reduced execution time.
In this dissertation, we introduce a performance modeling framework, E-AMOM,
to enable improved execution of scientific applications on parallel multicore systems
with regards to a limited power budget. We develop models for each application based
upon performance hardware counters. Our models utilize different performance
counters for each application and for each performance component (runtime, system
power consumption, CPU power consumption, and memory power consumption) that
are selected via our performance-tuned principal component analysis method. Models
developed through E-AMOM provide insight into the performance characteristics of
iv
each application that affect performance for each component on a parallel multicore
system. Our models are more than 92% accurate across both Hybrid (MPI/OpenMP)
and MPI implementations for six scientific applications.
E-AMOM includes an optimization component that utilizes our models to
employ run-time Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic
Concurrency Throttling to reduce power consumption of the scientific applications.
Further, we optimize our applications based upon insights provided by the performance
models to reduce runtime of the applications. Our methods and techniques are able to
save up to 18% in energy consumption for Hybrid (MPI/OpenMP) and MPI scientific
applications and reduce the runtime of the applications up to 11% on parallel multicore
systems.
v
DEDICATION
This dissertation is dedicated to my loving and supportive parents, Charles W.
Lively Jr. and Irene S. Lively.
vi
ACKNOWLEDGEMENTS
Graduate school has been an enriching journey that has helped to shape my life
and thought process. For this, I would first like to give thanks to my Lord and Savior
Jesus Christ for guiding me through out this journey and in life. My mother, Irene, has
been an endless source of encouragement and support since birth and I could never repay
her for always encouraging my intellectual interests. My family and friends have been a
great support system over the years and so I would like to thank them for always
offering kind words of encouragement and support (Charles Lively Jr., Vidal Lively,
Charles Beverley Jr., Courtney Carey, Jesse Dukes, Jacqueline Hodge, Carla Marsh, and
Antoinette Davis)
I have to thank my academic family for support throughout this time. My
advisor and mentor, Dr. Valerie Taylor, has taught me what it truly takes to be an
excellent researcher through constant encouragement, hard work, and “refinement”. I
would also like to give thanks to my second advisor, Dr. Xingfu Wu, for always
providing encouraging feedback and support. Special thanks are also in order for my
past research group members Dr. Ayodeji Coker and Dr. Sameh Sharkawi.
vii
NOMENCLATURE
MPI Message Passing Interface
HPC High Performance Computing
DVFC Dynamic Voltage and Frequency Scaling
DCT Dynamic Concurrency Throttling
viii
TABLE OF CONTENTS
Page
ABSTRACT .............................................................................................................. iii
DEDICATION .......................................................................................................... v
ACKNOWLEDGEMENTS ...................................................................................... vi
NOMENCLATURE ................................................................................................. vii
TABLE OF CONTENTS .......................................................................................... viii
LIST OF FIGURES .................................................................................................. x
LIST OF TABLES .................................................................................................... xv
1. INTRODUCTION .............................................................................................. 1
1.1 Research Challenges on Multicore Systems ........................................ 8
1.2 Modeling Infrastructure ....................................................................... 11
1.3 Related Work ....................................................................................... 16
2. PROPOSED PERFORMANCE MODELING SCHEME .................................. 27
2.1 Energy-Aware Modeling and Optimization Methodology (E-AMOM) 27
2.2 Performance-Tuned Principal Component Analysis Method .............. 30
2.3 Application Optimization Methods ...................................................... 34
2.4 Modeling Approaches Leveraged ........................................................ 37
3. PERFORMANCE-POWER TRADE-OFFS OF MPI AND HYBRID
APPLICATIONS ................................................................................................ 50
3.1 Parallel Multicore Systems .................................................................. 50
3.2 Experimental Environment .................................................................. 52
3.3 Experimental Results ........................................................................... 53
3.4 Summary .............................................................................................. 68
ix
Page
4. POWER-AWARE PERFORMANCE MODELS OF SCIENTIFIC
APPLICATIONS………………………………………………......…………….. 70
4.1 Performance-Tuned Principal Component Analysis Methodology ..... 70
4.2 HPC Applications ................................................................................ 81
4.3 Experimental Results ........................................................................... 85
4.4 Summary .............................................................................................. 149
5. OPTIMIZATION OF HYBRID AND MPI SCIENTIFIC APPLICATIONS .... 152
5.1 Software-Based Power Reduction Methods ........................................ 152
5.2 Optimization Methodology for Application Kernels ........................... 153
5.3 Loop Optimizations ............................................................................. 160
5.4 Experimental Results ........................................................................... 161
5.5 Summary .............................................................................................. 184
6. SUMMARY AND FUTURE WORK ................................................................ 185
6.1 Summary .............................................................................................. 185
6.2 Future Work ......................................................................................... 186
REFERENCES ......................................................................................................... 189
VITA ......................................................................................................................... 199
