Paper Info
Title
Multi-Objective Auto-Tuning with Insieme: Optimization and Trade-Off Analysis for Time, Energy and Resource Usage.
Abstract
The increasing complexity of modern multi-and many-core hardware design makes performance tuning of parallel applications a difficult task. In the past, auto-tuners have been successfully applied to minimize execution time. However, besides execution time, additional optimization goals have recently arisen, such as energy consumption or computing costs. Therefore, more sophisticated methods capable of exploiting and identifying the trade-offs among these goals are required. In this work we present and discuss results of applying a multi-objective search-based auto-tuner to optimize for three conflicting criteria: execution time, energy consumption, and resource usage. We examine a method, called RS-GDE3, to tune HPC codes using the Insieme parallelizing and optimizing compiler. Our results demonstrate that RS-GDE3 offers solutions of superior quality than those provided by a hierarchical and a random search at a fraction of the required time (5%) or energy (8%). A comparison to a state-of-the-art multi-objective optimizer (NSGA-II) shows that RS-GDE3 computes solutions of higher quality. Finally, based on the trade-off solutions found by RS-GDE3, we provide a detailed analysis and several hints on how to improve the design of multi-objective auto-tuners and code optimization.
Year
DOI
Venue
2014
10.1007/978-3-319-09873-9_8
Lecture Notes in Computer Science
Field
DocType
Volume
Program optimization,Random search,Computer science,Optimizing compiler,Execution time,Energy consumption,Auto tuning,Performance tuning,Distributed computing
Conference
8632
ISSN
Citations 
PageRank 
0302-9743
12
0.52
References 
Authors
15
3
Name
Order
Citations
PageRank
Philipp Gschwandtner1587.15
Juan José Durillo227214.31
Thomas Fahringer32847254.09