| Dynamic tuning of configurable architectures: the AWW online algorithm |
| Full text |
Pdf
(294 KB)
|
Source
|
International Conference on Hardware Software Codesign
archive
Proceedings of the 6th IEEE/ACM/IFIP international conference on Hardware/Software codesign and system synthesis
table of contents
Atlanta, GA, USA
SESSION: Exploration, profiling and tuning of embedded systems
table of contents
Pages 97-102
Year of Publication: 2008
ISBN:978-1-60558-470-6
|
|
Authors
|
|
Chen Huang
|
University of California, Riverside, Riverside, CA, USA
|
|
David Sheldon
|
University of California, Riverside, Riverside, CA, USA
|
|
Frank Vahid
|
University of California, Riverside, Riverside, CA, USA
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 10, Downloads (12 Months): 67, Citation Count: 0
|
|
|
ABSTRACT
Architectures with software-writable parameters, or configurable architectures, enable runtime reconfiguration of computing platforms to the applications they execute. Such dynamic tuning can improve application performance, as well as energy. However, reconfiguring incurs a temporary performance cost. Thus, online algorithms are needed that decide when to reconfigure and which configuration to choose such that overall performance is optimized. We introduce the adaptive weighted window (AWW) algorithm, and compare with several other algorithms, including algorithms previously developed by the online algorithm community. We describe experiments showing that AWW results are within 4% of the offline optimal on average. AWW outperforms the other algorithms, and is robust across three datasets and across three categories of application sequences too. AWW improves a non-dynamic approach on average by 6%, and by up to 30% in low-reconfiguration-time situations.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
D.H. Albonesi. Selective Cache Ways: On-Demand Cache Resource Allocation. Journal of Instruction Level. Parallelism, May 2000.
|
 |
2
|
Rajeev Balasubramonian , David Albonesi , Alper Buyuktosunoglu , Sandhya Dwarkadas, Memory hierarchy reconfiguration for energy and performance in general-purpose processor architectures, Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture, p.245-257, December 2000, Monterey, California, United States
[doi> 10.1145/360128.360153]
|
 |
3
|
Yair Bartal , Avrim Blum , Carl Burch , Andrew Tomkins, A polylog(n)-competitive algorithm for metrical task systems, Proceedings of the twenty-ninth annual ACM symposium on Theory of computing, p.711-719, May 04-06, 1997, El Paso, Texas, United States
[doi> 10.1145/258533.258667]
|
| |
4
|
|
 |
5
|
|
| |
6
|
W.R. Burley and S. Irani. On algorithm design for metrical task system. Algorithmica, 1997, Vol. 18, pp. 461--485.
|
| |
7
|
|
 |
8
|
|
| |
9
|
|
 |
10
|
Kanishka Lahiri , Anand Raghunathan , Ganesh Lakshminarayana , Sujit Dey, Communication architecture tuners: a methodology for the design of high-performance communication architectures for systems-on-chips, Proceedings of the 37th conference on Design automation, p.513-518, June 05-09, 2000, Los Angeles, California, United States
[doi> 10.1145/337292.337561]
|
 |
11
|
|
 |
12
|
David Sheldon , Rakesh Kumar , Roman Lysecky , Frank Vahid , Dean Tullsen, Application-specific customization of parameterized FPGA soft-core processors, Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design, November 05-09, 2006, San Jose, California
[doi> 10.1145/1233501.1233553]
|
| |
13
|
|
 |
14
|
Pablo Viana , Ann Gordon-Ross , Eamonn Keogh , Edna Barros , Frank Vahid, Configurable cache subsetting for fast cache tuning, Proceedings of the 43rd annual conference on Design automation, July 24-28, 2006, San Francisco, CA, USA
[doi> 10.1145/1146909.1147085]
|
 |
15
|
|
|