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Methodology for multi-granularity embedded processor power model generation for an ESL design flow
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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: System level power modeling and optimization table of contents
Pages 255-260  
Year of Publication: 2008
ISBN:978-1-60558-470-6
Authors
Young-Hwan Park  University of California, Irvine, Irvine, CA, USA
Sudeep Pasricha  Colorado State University, Fort Collins, CO, USA
Fadi J. Kurdahi  University of California, Irvine, Irvine, CA, USA
Nikil Dutt  University of California, Irvine, Irvine, CA, USA
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
Publisher
ACM  New York, NY, USA
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ABSTRACT

With power becoming a major constraint for multi-processor embedded systems, it is becoming important for designers to characterize and model processor power dissipation. It is critical for these processor power models to be useable across various modeling abstractions in an electronic system level (ESL) design flow, to guide early design decisions. In this paper, we propose a unified processor power modeling methodology for the creation of power models at multiple granularity levels that can be quickly mapped to an ESL design flow. Our experimental results based on applying the proposed methodology on an OpenRISC processor demonstrate the usefulness of having multiple power models. The generated models range from very high-level two-state and architectural/ISS models that can be used in transaction level models (TLM), to extremely detailed cycle-accurate models that enable early exploration of power optimization techniques. These models offer a designer tremendous flexibility to trade off estimation accuracy with estimation/simulation effort.


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.

 
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3
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Cacti4", http://quid.hpl.hp.com:9081/cacti/.
 
6
 
7
Y. Park, et al, "System-level power estimation methodology with H.264 decoder prediction IP case study", Proc. ICCD 2007.
 
8
9
10
 
11
 
12
C. Chakrabarti et al, "Instruction level power model of microcontrollers", Proc. IEEE ISCAS, pp. 176--179, 1999.
13
 
14
N. Kavvadias, et al, "Measurements analysis of the software-related power consumption in microprocessors", Proc. IMTC, pp. 981--986, 2003.
 
15
A. Varma, et al, "Instruction-level power dissipation in the Intel XScale embedded microprocessor." Proc. SPIE's 17th Annual Symposium on Electronic Imaging Science & Technology, Jan. 2005.
 
16
M. Schneider, et al, "Power estimation on functional level for programmable processors", Advances in Radio Science, pp 215--219, 2005.
 
17
D. Burger, et al, "The simplescalar tool set, version 2.0", Technical report, Computer Sciences Dept., University of Wisconsin, June, 1997.
 
18
OpenRISC 1000 Family, http://www.opencores.org/projects/or1k/.
 
19
Y. Park, et al, "Methodology for Multi-Granularity Embedded Processor Power Model Generation", UCI Technical Report, 2008.
 
20
J. J. Faraway, "Linear Models with R", CRC Press, 2004.
 
21
Synopsys Design Compiler, PrimeTime PX, http://www.synopsys.com.
 
22
Cadence NC-Verilog, http://www.cadence.com.
 
23
SystemC initiative, http://www.systemc.org.
24

Collaborative Colleagues:
Young-Hwan Park: colleagues
Sudeep Pasricha: colleagues
Fadi J. Kurdahi: colleagues
Nikil Dutt: colleagues