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High-level power analysis for multi-core chips
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Source International Conference on Compilers, Architecture and Synthesis for Embedded Systems archive
Proceedings of the 2006 international conference on Compilers, architecture and synthesis for embedded systems table of contents
Seoul, Korea
SESSION: Low power table of contents
Pages: 389 - 400  
Year of Publication: 2006
ISBN:1-59593-543-6
Authors
Noel Eisley  Princeton University, Princeton, NJ
Vassos Soteriou  Princeton University, Princeton, NJ
Li-Shiuan Peh  Princeton University, Princeton, NJ
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
SIGBED: ACM Special Interest Group on Embedded Systems
SIGMICRO: ACM Special Interest Group on Microarchitectural Research and Processing
Publisher
ACM  New York, NY, USA
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ABSTRACT

Technology trends have led to the advent of multi-core chips in the form of both general-purpose chip multiprocessors (CMPs)and embedded multi-processor systems-on-a-chip (MPSoCs), with on-chip networks increasingly becoming the defacto communication fabric between cores as the demand for on-chip bandwidth scales up. These multi-core chips are composed of two key subcomponents: processor cores and a network fabric. Rapid, early-stage power estimation of these multi-core chips is crucial in assisting compilers in determining the most efficient thread partitioning and place-ment. While prior work in high-level power analysis exists, the focus has been on uniprocessor cores and ignores the interactions between cores via the on-chip network, as well as the power contribution of the on-chip fabric itself. In this paper we propose a ?rst high-level power analysis framework that synergistically considers both computation and communication in a complete CMP system. Processor cores and the communication fabric are both abstracted as network nodes and links, so data dependencies, structural dependencies and communication dependencies are all modeled as resource contention, with resource utilization as a proxy for relative power. Our tool has been validated against the cycle-accurate BTL simulator of the MITRawCMP, showing an average speed up of 7X while achieving relative accuracy of 9.1%. We see this as a ?rst step towards enabling the implementation of parallelizing compilers that explore various power-performance tradeoffs for future multi-core chips.


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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ARM Integrated Multiprocessor Core, 2006. Available{online}:http://www.arm.com.
 
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L. Benini and G. DeMicheli. Powering Networks on Chip. In Proc. of the International Symposium on System Synthesis, pp. 33--38, Oct. 2001.
3
 
4
5
6
 
7
8
 
9
L. Eeckhout et al. Statistical Simulation:Adding Efficiency to the Computer Designer's Toolbox. IEEE Micro, Vol. 23, No. 5, pp. 26--38, Sept.-Oct. 2003.
10
 
11
Gigascale Systems Research Center (GSRC), 2006. Available {online} http://www.gigascale.org/roadmap/.
12
 
13
C. Isci and M. Martonosi. Phase Characterization for Power: Evaluating Control-Flow-Based and Event-Counter-Based Techniques. In Proc. of the International Symposium on High Performance Computer Architecture, pp. 121--132, Feb. 2006.
14
 
15
 
16
E. Macii et al. High-Level Power Modeling, Estimation, and Optimization. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 17, No. 11, Nov. 1998.
17
 
18
 
19
MIT Raw Team, personal communication, 2006.
20
 
21
22
 
23
D. Penry et al. Exploiting Parallelism and Structure to Accelerate the Simulation of Chip Multi-Processors. In Proc. of International Symposium on High Performance Computer Architecture, pp. 29--40, Feb. 2006.
 
24
D. Pham et al. The Design and Implementation of a First-Generation Cell Processor. In Proc. of the International Solid-State Circuits Conference, pp. 184--185, March 2005.
 
25
PoPNet Simulator, 2006. Available {online} http://www.princeton.edu/~lshang/popnet.html.
26
27
28
 
29
 
30
T. Sherwoood et al. Automatically Characterizing Large Scale Program Behavior. ACM SIGPLAN Notices, Vol. 37, No. 10, pp. 45--57, Oct. 2002.
 
31
Simics, 2006. Available {online}:www.simics.net.
 
32
Simple Scalar LLC, 2006. Available {online}: http://www.simplescalar.com.
33
34
 
35
 
36
The Standard Performance Evaluation Corporation, 2006. Available {online}: http://www.spec.org.
 
37
 
38
 
39
 
40
41
 
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Collaborative Colleagues:
Noel Eisley: colleagues
Vassos Soteriou: colleagues
Li-Shiuan Peh: colleagues