Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article

Challenges and opportunities for efficient computing with FAWN

Published: 18 February 2011 Publication History

Abstract

This paper presents the architecture and motivation for a clusterbased, many-core computing architecture for energy-efficient, dataintensive computing. FAWN, a Fast Array of Wimpy Nodes, consists of a large number of slower but efficient nodes coupled with low-power storage. We present the computing trends that motivate a FAWN-like approach, for CPU, memory, and storage. We follow with a set of microbenchmarks to explore under what workloads these FAWN nodes perform well (or perform poorly), and briefly examine scenarios in which both code and algorithms may need to be re-designed or optimized to perform well on an efficient platform. We conclude with an outline of the longer-term implications of FAWN that lead us to select a tightly integrated stacked chip and-memory architecture for future FAWN development.

References

[1]
Flexible I/O Tester. http://freshmeat.net/projects/fio/.
[2]
David G. Andersen, Jason Franklin, Michael Kaminsky, Amar Phanishayee, Lawrence Tan, and Vijay Vasudevan. FAWN: A fast array of wimpy nodes. In Proc. 22nd ACM Symposium on Operating Systems Principles (SOSP), Big Sky, MT, October 2009.
[3]
Eric Anderson and Joseph Tucek. Efficiency matters! In Proc. Hot-Storage, Big Sky, MT, October 2009.
[4]
Luiz André Barroso and Urs Hölzle. The case for energy-proportional computing. Computer, 40(12):33--37, 2007.
[5]
Andreas Beckmann, Ulrich Meyer, Peter Sanders, and Johannes Singler. Energy-efficient sorting using solid state disks. http://sortbenchmark.org/ecosort_2010_Jan_01.pdf, 2010.
[6]
W. Bowman, N. Cardwell, C. Kozyrakis, C. Romer, and H. Wang. Evaluation of existing architectures in IRAM systems. InWorkshop on Mixing Logic and DRAM, 24th International Symposium on Computer Architecture, June 1997.
[7]
Adrian M. Caulfield, Laura M. Grupp, and Steven Swanson. Gordon: Using flash memory to build fast, power-efficient clusters for data-intensive applications. In 14th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '09), March 2009.
[8]
Sang Kil Cha, Iulian Moraru, Jiyong Jang, John Truelove, David Brumley, and David G. Andersen. SplitScreen: Enabling efficient, distributed malware detection. In Proc. 7th USENIX NSDI, San Jose, CA, April 2010.
[9]
John D. Davis and Suzanne Rivoire. Building energy-efficient systems for sequential workloads. Technical Report MSR-TR-2010-30, Microsoft Research, March 2010.
[10]
Jeffrey Dean and Sanjay Ghemawat. MapReduce: Simplified data processing on large clusters. In Proc. 6th USENIX OSDI, San Francisco, CA, December 2004.
[11]
Dell fortuna. http://www1.euro.dell.com/content/topics/topic.aspx/emea/corporate/pressoffice/2009/uk/en/2009_05_20_brk_000, 2009.
[12]
Lakshmi Ganesh, Hakim Weatherspoon, Mahesh Balakrishnan, and Ken Birman. Optimizing power consumption in large scale storage systems. In Proc. HotOS XI, San Diego, CA, May 2007.
[13]
Kathy Gray. Port deal with Google to create jobs. The Dalles Chronicle, http://www.gorgebusiness.com/2005/google.htm, February 2005.
[14]
James Hamilton. Cooperative expendable micro-slice servers (CEMS): Low cost, low power servers for Internet scale services. http://mvdirona.com/jrh/TalksAndPapers/JamesHamilton_CEMS.pdf, 2009.
[15]
Penryn Press Release. http://www.intel.com/pressroom/archive/releases/20070328fact.htm.
[16]
Filesystem Benchmark. http://www.iozone.org.
[17]
Randy H. Katz. Tech titans building boom. IEEE Spectrum, February 2009.
[18]
Kevin Lim, Parthasarathy Ranganathan, Jichuan Chang, Chandrakant Patel, Trevor Mudge, and Steven Reinhardt. Understanding and designing new server architectures for emerging warehouse-computing environments. In International Symposium on Computer Architecture (ISCA), Beijing, China, June 2008.
[19]
Peering into future of cloud computing. http://research.microsoft.com/en-us/news/features/ccf-022409.aspx, 2009.
[20]
Iulian Moraru and David G. Andersen. Exact pattern matching with feed-forward bloom filters. In Proceedings of the Workshop on Algorithm Engineering and Experiments (ALENEX11), ALENEX 2011. Society for Industrial and Applied Mathematics, 2011.
[21]
Vijay Janapa Reddi, Benjamin Lee, Trishul Chilimbi, and Kushagra Vaid. Web search using small cores: Quantifying the price of efficiency. Technical Report MSR-TR-2009-105, Microsoft Research, August 2009.
[22]
Erik Riedel, Christos Faloutsos, Garth A. Gibson, and David Nagle. Active disks for large-scale data processing. IEEE Computer, 34(6):68--74, June 2001.
[23]
Suzanne Rivoire, Mehul A. Shah, Parthasarathy Ranganathan, and Christos Kozyrakis. JouleSort: A balanced energy-efficient benchmark. In Proc. ACM SIGMOD, Beijing, China, June 2007.
[24]
Steven W. Schlosser, John Linwood Griffin, David F. Nagle, and Gregory R. Ganger. Filling the memory access gap: A case for on-chip magnetic storage. Technical Report CMU-CS-99-174, Carnegie Mellon University, November 1999.
[25]
Seamicro. http://www.seamicro.com, 2010.
[26]
Mark W. Storer, Kevin M. Greenan, Ethan L. Miller, and Kaladhar Voruganti. Pergamum: Replacing tape with energy efficient, reliable, disk-based archival storage. In Proc. USENIX Conference on File and Storage Technologies (FAST 2008), San Jose, CA, February 2008.
[27]
Alex Szalay, Gordon Bell, Andreas Terzis, Alainna White, and Jan Vandenberg. Low power Amdahl blades for data intensive computing, 2009.
[28]
Niraj Tolia, Zhikui Wang, Manish Marwah, Cullen Bash, Parthasarathy Ranganathan, and Xiaoyun Zhu. Delivering energy proportionality with non energy-proportional systems -- optimizing the ensemble. In Proc. HotPower, San Diego, CA, December 2008.
[29]
.NET Power Meter. http://wattsupmeters.com.
[30]
MarkWeiser, BrentWelch, Alan Demers, and Scott Shenker. Scheduling for reduced CPU energy. In Proc. 1st USENIX OSDI, pages 13--23, Monterey, CA, November 1994.
[31]
Qingbo Zhu, Zhifeng Chen, Lin Tan, Yuanyuan Zhou, Kimberly Keeton, and Jon Wilkes. Hibernator: Helping disk arrays sleep through the winter. In Proc. 20th ACM Symposium on Operating Systems Principles (SOSP), Brighton, UK, October 2005.

Cited By

View all
  • (2017)Survey on energy-efficient hard drive disks2017 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICCNC.2017.7876257(929-931)Online publication date: Jan-2017
  • (2015)An Energy-Efficient and Reliable Storage Mechanism for Data-Intensive Academic Archive SystemsACM Transactions on Storage10.1145/272002111:2(1-21)Online publication date: 20-Mar-2015
  • (2015)A study of suitable fault tolerance frameworks for an energy-efficient storage system2015 International Conference on Collaboration Technologies and Systems (CTS)10.1109/CTS.2015.7210424(220-225)Online publication date: Jun-2015
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM SIGOPS Operating Systems Review
ACM SIGOPS Operating Systems Review  Volume 45, Issue 1
January 2011
160 pages
ISSN:0163-5980
DOI:10.1145/1945023
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 February 2011
Published in SIGOPS Volume 45, Issue 1

Check for updates

Author Tags

  1. cluster computing
  2. design
  3. energy efficiency
  4. flash
  5. measurement
  6. performance

Qualifiers

  • Research-article

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)1
Reflects downloads up to 09 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2017)Survey on energy-efficient hard drive disks2017 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICCNC.2017.7876257(929-931)Online publication date: Jan-2017
  • (2015)An Energy-Efficient and Reliable Storage Mechanism for Data-Intensive Academic Archive SystemsACM Transactions on Storage10.1145/272002111:2(1-21)Online publication date: 20-Mar-2015
  • (2015)A study of suitable fault tolerance frameworks for an energy-efficient storage system2015 International Conference on Collaboration Technologies and Systems (CTS)10.1109/CTS.2015.7210424(220-225)Online publication date: Jun-2015
  • (2012)CacheRAIDProceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing10.1109/UCC.2012.26(117-124)Online publication date: 5-Nov-2012

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media