research-article

Impact of GC design on power and performance for Android

Authors:

Antony Hosking,

Christopher A. VickAuthors Info & Claims

SYSTOR '15: Proceedings of the 8th ACM International Systems and Storage Conference

Article No.: 13, Pages 1 - 12

https://doi.org/10.1145/2757667.2757674

Published: 26 May 2015 Publication History

Abstract

Small mobile devices have evolved to versatile computing systems. Android devices run a complete software stack, including a full Linux kernel, user land with several software daemons and a virtual machine to run applications. On these mobile systems energy is a scarce resource and needs to be handled carefully. Current systems rely on governors that adjust the frequency of individual cores depending on the system load.

We measure energy consumption of different components of this complex software stack, including garbage collection (GC) of the Android virtual machine. Here we propose several extensions to the default GC configuration of Android, including a generational collector, across established dimensions of heap memory size and concurrency.

Our evaluation shows that Android's asynchronous GC thread consumes a significant amount of energy. Therefore, varying the GC strategy can reduce total on-chip energy (by 20--30%) whilst slightly impacting application throughput (by 10--40%) and increasing worst-case pause times (by 20--30%). Our work quantifies the direct impact of GC on mobile system, enumerates the main factors and layers of this relationship, and offers a guide for analysis of memory behavior in understanding and tuning system performance.

References

[1]

M. Arnold, S. Fink, D. Grove, M. Hind, and P. F. Sweeney. Adaptive optimization in the jalapeño JVM. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 47--65, Minneapolis, Minnesota, Oct. 2000.

Digital Library

[2]

ART and Dalvik. URL https://source.android.com/devices/tech/dalvik/art.html.

[3]

S. M. Blackburn, R. Garner, C. Hoffman, A. M. Khan, K. S. McKinley, R. Bentzur, A. Diwan, D. Feinberg, D. Frampton, S. Z. Guyer, M. Hirzel, A. L. Hosking, M. Jump, H. Lee, J. E. B. Moss, A. Phansalkar, D. Stefanović, T. VanDrunen, D. von Dincklage, and B. Wiedermann. The DaCapo benchmarks: Java benchmarking development and analysis. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 169--190, Portland, Oregon, Oct. 2006.

Digital Library

[4]

S. M. Blackburn, R. Garner, C. Hoffman, A. Khan, K. S. McKinley, R. Bentzur, A. Diwan, D. Feinberg, S. Z. Guyer, A. Hosking, M. Jump, J. E. B. Moss, D. Stefanovic, T. VanDrunen, D. von Dincklage, and B. Widerman. Wake up and smell the coffee: Evaluation methodology for the 21st century. Commun. ACM, 51 (8): 83--89, Aug. 2008.

Digital Library

[5]

T. Brecht, E. Arjomandi, C. Li, and H. Pham. Controlling garbage collection and heap growth to reduce the execution time of Java applications. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 353--366, Tampa, Florida, Nov. 2001.

Digital Library

[6]

D. Brodowski. CPU frequency and voltage scaling code in the Linux kernel. URL https://www.kernel.org/doc/Documentation/cpu-freq/governors.txt.

[7]

T. Cao, S. M. Blackburn, T. Gao, and K. S. McKinley. The yin and yang of power and performance for asymmetric hardware and managed software. In International Symposium on Computer Architecture, pages 225--236, Portland, Oregon, June 2012.

Digital Library

[8]

A. Carroll and G. Heiser. An analysis of power consumption in a smartphone. In USENIX Annual Technical Conference, pages 271--284, Boston, Massachusetts, June 2010. URL https://www.usenix.org/legacy/event/atc10/tech/full_papers/Carroll.pdf.

Digital Library

[9]

A. Carroll and G. Heiser. Unifying DVFS and offlining in mobile multicores. In IEEE Real-Time and Embedded Technology and Applications Symposium, pages 287--296, Berlin, Germany, Apr. 2014.

[10]

G. Chen, M. T. Kandemir, N. Vijaykrishnan, M. J. Irwin, and M. Wolczko. Adaptive garbage collection for battery-operated environments. In USENIX Java Virtual Machine Research and Technology Symposium, pages 1--12, San Francisco, California, Aug. 2002a. URL https://www.usenix.org/legacy/event/jvm02/chen_g.html.

Digital Library

[11]

G. Chen, R. Shetty, M. Kandemir, N. Vijaykrishnan, M. J. Irwin, and M. Wolczko. Tuning garbage collection for reducing memory system energy in an embedded Java environment. ACM Transactions on Embedded Computing Systems, 1(1): 27--55, Nov. 2002b.

Digital Library

[12]

X. Chen, A. Jindal, and Y. C. Hu. How much energy can we save from prefetching ads?: Energy drain analysis of top 100 apps. In ACM Workshop on Power-Aware Computing and Systems, HotPower, pages 3:1--3:5, Farmington, Pennsylvania, 2013.

Digital Library

[13]

P. Cheng and G. E. Blelloch. A parallel, real-time garbage collector. In ACM SIGPLAN International Conference on Programming Language Design and Implementation, pages 125--136, Snowbird, Utah, June 2001.

Digital Library

[14]

F. M. David, J. C. Carlyle, and R. H. Campbell. Context switch overheads for Linux on ARM platforms. In Workshop on Experimental Computer Science, San Diego, California, 2007. ACM.

Digital Library

[15]

S. Dieckmann and U. Hölzle. A study of the allocation behavior of the SPECjvm98 Java benchmarks. In European Conference on Object-Oriented Programming, Lecture Notes in Computer Science, pages 92--115, Lisbon, Portugal, July 1999.

Digital Library

[16]

E. W. Dijkstra, L. Lamport, A. J. Martin, C. S. Scholten, and E. F. M. Steffens. On-the-fly garbage collection: An exercise in cooperation. Commun. ACM, 21(11): 966--975, Nov. 1978.

Digital Library

[17]

T. Domani, E. K. Kolodner, E. Lewis, E. E. Salant, K. Barabash, I. Lahan, Y. Levanoni, E. Petrank, and I. Yanorer. Implementing an on-the-fly garbage collector for Java. In ACM SIGPLAN International Symposium on Memory Management, pages 155--166, Minneapolis, Minnesota, Oct. 2000.

Digital Library

[18]

B. Dufour, K. Driesen, L. Hendren, and C. Verbrugge. Dynamic metrics for Java. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 149--168, Anaheim, California, Oct. 2003.

Digital Library

[19]

R. Efron. Conservation of temporal information by perceptual systems. Perception & Psychophysics, 14(3): 518--530, Oct. 1973.

[20]

D. Ehringer. The Dalvik Virtual Machine Architecture, Mar. 2010. URL http://davidehringer.com/software/android/The_Dalvik_Virtual_Machine.pdf.

[21]

H. Esmaeilzadeh, T. Cao, Y. Xi, S. M. Blackburn, and K. S. McKinley. Looking back on the language and hardware revolutions: Measured power, performance, and scaling. In ACM Conference on Architectural Support for Programming Languages and Operating Systems, pages 319--332, Newport Beach, California, Mar. 2011.

Digital Library

[22]

Market Share: Ultramobiles by Region, OS and Form Factor, 4Q13 and 2013. Gartner, Feb. 2014. URL https://www.gartner.com/doc/2672716/market-share-ultramobiles-region-os.

[23]

A. Gautham, K. Korgaonkar, P. Slpsk, S. Balachandran, and K. Veezhinathan. The implications of shared data synchronization techniques on multi-core energy efficiency. In USENIX Conference on Power-Aware Computing and Systems, HotPower, Hollywood, California, Oct. 2012. URL https://www.usenix.org/system/files/conference/hotpower12/hotpower12-final40.pdf.

Digital Library

[24]

A. Georges, D. Buytaert, and L. Eeckhout. Statistically rigorous Java performance evaluation. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 57--76, Montréal, Canada, Oct. 2007.

Digital Library

[25]

P. Griffin, W. Srisa-an, and J. M. Chang. An energy efficient garbage collector for Java embedded devices. In ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems, pages 230--238, Chicago, Illinois, June 2005.

Digital Library

[26]

S. Hao, D. Li, W. G. J. Halfond, and R. Govindan. Estimating mobile application energy consumption using program analysis. In International Conference on Software Engineering, pages 92--101, San Francisco, California, May 2013. IEEE Press.

Digital Library

[27]

Intrinsync. DragonBoard development board based on the Qualcomm Snapdragon 800 processor (APQ8074). URL http://mydragonboard.org/db8074.

[28]

A. Iyer and D. Marculescu. Power efficiency of voltage scaling in multiple clock, multiple voltage cores. In IEEE/ACM International Conference on Computer-Aided Design, pages 379--386, San Jose, California, Nov. 2002.

Digital Library

[29]

A. Jindal, A. Pathak, Y. C. Hu, and S. Midkiff. Hypnos: Understanding and treating sleep conflicts in smartphones. In ACM European Conference on Computer Systems, EuroSys, pages 253--266, Prague, Czech Republic, 2013. ISBN 978-1-4503-1994-2.

Digital Library

[30]

R. Jones, A. Hosking, and E. Moss. The Garbage Collection Handbook: The Art of Automatic Memory Management. Chapman & Hall/CRC Press, 2011.

[31]

T. Kalibera and R. Jones. Rigorous benchmarking in reasonable time. In The International Symposium on Memory Management, pages 63--74, Seattle, Washington, June 2013.

Digital Library

[32]

T. Kalibera, M. Mole, R. Jones, and J. Vitek. A black-box approach to understanding concurrency in DaCapo. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 335--354, Tucson, Arizona, Oct. 2012.

Digital Library

[33]

M. Kambadur and M. A. Kim. An experimental survey of energy management across the stack. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 329--344, Portland, Oregon, Oct. 2014.

Digital Library

[34]

H. Lieberman and C. E. Hewitt. A real-time garbage collector based on the lifetimes of objects. Commun. ACM, 26(6): 419--429, June 1983.

Digital Library

[35]

A. Miyoshi, C. Lefurgy, E. Van Hensbergen, R. Rajamony, and R. Rajkumar. Critical power slope: Understanding the runtime effects of frequency scaling. In International Conference on Supercomputing, pages 35--44, New York, New York, June 2002. ACM.

Digital Library

[36]

monkeyrunner. URL http://developer.android.com/tools/help/monkeyrunner_concepts.html.

[37]

National Instruments. NI USB-6008/6009 user guide and specifications: Bus-powered multifunction DAQ USB device, Feb. 2012. URL http://www.ni.com/pdf/manuals/371303m.pdf.

[38]

S. Park, W. Jiang, Y. Zhou, and S. Adve. Managing energy-performance tradeoffs for multithreaded applications on multiprocessor architectures. In ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, pages 169--180, San Diego, California, June 2007.

Digital Library

[39]

A. Pathak, Y. C. Hu, M. Zhang, P. Bahl, and Y.-M. Wang. Fine-grained power modeling for smartphones using system call tracing. In ACM European Conference on Computer Systems, pages 153--168, Salzburg, Austria, Apr. 2011.

Digital Library

[40]

A. Pathak, Y. C. Hu, and M. Zhang. Where is the energy spent inside my app?: Fine grained energy accounting on smartphones with eprof. In ACM European Conference on Computer Systems, pages 29--42, Bern, Switzerland, Apr. 2012.

Digital Library

[41]

G. Pinto, F. Castor, and Y. D. Liu. Understanding energy behaviors of thread management constructs. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 345--360, Portland, Oregon, Oct. 2014.

Digital Library

[42]

T. Printezis. On measuring garbage collection responsiveness. Science of Computer Programming, 62(2): 164--183, Oct. 2006.

Digital Library

[43]

J. B. Sartor and L. Eeckhout. Exploring multi-threaded Java application performance on multicore hardware. In ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications, pages 281--296, Tucson, Arizona, Oct. 2012.

Digital Library

[44]

Standard Performance Evaluation Corporation. SPECjvm98 Benchmarks, release 1.03 edition, Mar. 1999. URL http://www.spec.org/jvm98.

[45]

D. M. Ungar. Generation scavenging: A non-disruptive high performance storage reclamation algorithm. In ACM SIGSOFT/SIGPLAN Software Engineering Symposium on Practical Software Development Environments, pages 157--167, Pittsburgh, Pennsylvania, Apr. 1984.

Digital Library

[46]

N. Vijaykrishnan, M. Kandemir, S. Kim, S. Tomar, A. Sivasubramaniam, and M. J. Irwin. Energy behavior of Java applications from the memory perspective. In USENIX Java Virtual Machine Research and Technology Symposium, Monterey, California, Apr. 2001. URL https://www.usenix.org/legacy/events/jvm01/full_papers/vijaykrishnan/vijaykrishnan.pdf.

Digital Library

[47]

V. M. Weaver, D. Terpstra, and S. Moore. Non-determinism and overcount on modern hardware performance counter implementations. IEEE International Symposium on Performance Analysis of Systems and Software, pages 215--224, Apr. 2013.

[48]

R. Wilhelm, J. Engblom, A. Ermedahl, N. Holsti, S. Thesing, D. Whalley, G. Bernat, C. Ferdinand, R. Heckmann, T. Mitra, F. Mueller, I. Puaut, P. Puschner, J. Staschulat, and P. Stenström. The worst-case execution-time problem --- overview of methods and survey of tools. ACM Transactions on Embedded Computing Systems, 7(3): 36:1--36:53, May 2008.

Digital Library

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Sareen KBlackburn SHamouda SGidra LBond MLee JPayer H(2024)Memory Management on Mobile DevicesProceedings of the 2024 ACM SIGPLAN International Symposium on Memory Management10.1145/3652024.3665510(15-29)Online publication date: 20-Jun-2024
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Index Terms

Impact of GC design on power and performance for Android

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Reviews

Reviewer: David E. Goldfarb

Android's garbage collection (GC) strategy is investigated in this paper in impressive detail. The authors do a good job of explaining how GC works in Dalvik, have ported a significant number of benchmarks, and have collected statistics that appear to be detailed and accurate. Unfortunately, the paper is rapidly becoming dated. Newer Android devices run Android Runtime (ART) rather than Dalvik. ART's GC already includes many of the optimizations suggested by this paper (most notably a generational GC). Parts of this paper do remain relevant, such as the authors' suggestions of system changes to allow for better and more repeatable benchmarking access. However, most of this paper is specific to Dalvik, and therefore of limited current interest to most readers. The authors are, of course, aware of this problem and, in a final paragraph, propose a follow-up study of the ART GC. I look forward to reading that future paper. Online Computing Reviews Service

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cover image ACM Conferences

SYSTOR '15: Proceedings of the 8th ACM International Systems and Storage Conference

May 2015

183 pages

ISBN:9781450336079

DOI:10.1145/2757667

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 May 2015

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SYSTOR 2015: International Conference on Systems and Storage

May 26 - 28, 2015

Haifa, Israel

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Overall Acceptance Rate 108 of 323 submissions, 33%

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Sareen KBlackburn SHamouda SGidra LBond MLee JPayer H(2024)Memory Management on Mobile DevicesProceedings of the 2024 ACM SIGPLAN International Symposium on Memory Management10.1145/3652024.3665510(15-29)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3652024.3665510
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https://doi.org/10.1016/j.scico.2023.102962
Hort MKechagia MSarro FHarman M(2022)A Survey of Performance Optimization for Mobile ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2021.307119348:8(2879-2904)Online publication date: 1-Aug-2022
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