ACM Home Page
Please provide us with feedback. Feedback
Exploring and predicting the architecture/optimising compiler co-design space
Full text PdfPdf (478 KB)
Source
International Conference on Compilers, Architecture and Synthesis for Embedded Systems archive
Proceedings of the 2008 international conference on Compilers, architectures and synthesis for embedded systems table of contents
Atlanta, GA, USA
SESSION: Compiler hardware interaction table of contents
Pages 31-40  
Year of Publication: 2008
ISBN:978-1-60558-469-0
Authors
Christophe Dubach  University of Edinburgh, Edinburgh, United Kingdom
Timothy M. Jones  University of Edinburgh, Edinburgh, United Kingdom
Michael F.P. O'Boyle  University of Edinburgh, Edinburgh, United Kingdom
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
Bibliometrics
Downloads (6 Weeks): 13,   Downloads (12 Months): 111,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1450095.1450103
What is a DOI?

ABSTRACT

Embedded processor performance is dependent on both the underlying architecture and the compiler optimisations applied. However, designing both simultaneously is extremely difficult to achieve due to the time constraints designers must work under. Therefore, current methodology involves designing compiler and architecture in isolation, leading to sub-optimal performance of the final product.

This paper develops a novel approach to this co-design space problem. For any microarchitectural configuration we automatically predict the performance that an optimising compiler would achieve without actually building it. Once trained, a single run of -O1 on the new architecture is enough to make a prediction with just a 1.6% error rate. This allows the designer to accurately choose an architectural configuration with knowledge of how an optimising compiler will perform on it. We use this to find the best optimising compiler/architectural configuration in our co-design space and demonstrate that it achieves an average 13% performance improvement and energy savings of 23% compared to the baseline, leading to an energy-delay (ED) value of 0.67.


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
E. İpek, S. A. McKee, R. Caruana, B. R. de Supinski, and M. Schulz. Efficiently exploring architectural design spaces via predictive modeling. In ASPLOS, 2006.
 
2
P. J. Joseph, K. Vaswani, and M. J. Thazhuthaveetil. Construction and use of linear regression models for processor performance analysis. In HPCA, February 2006.
3
4
 
5
 
6
 
7
8
 
9
 
10
11
 
12
 
13
Intel Corporation. Intel XScale microarchitecture. http://www.intel.com/design/intelxscale/.
14
 
15
D. Tarjan, S. Thoziyoor, and N. P. Jouppi. Cacti 4.0. Technical Report HPL-2006-86, HP Laboratories Palo Alto, 2006.
 
16
17
18
19
 
20
 
21
E. İpek, B. R. de Supinski, M. Schulz, and S. A. McKee. An approach to performance prediction for parallel applications. In Euro-Par, 2005.
 
22
23
 
24
 
25
 
26
27
 
28
 
29
 
30
 
31
Milepost. http://www.milepost.eu.
 
32
The edinburgh compute and data facility (ECDF). http://www.ecdf.ed.ac.uk.
 
33
The eDIKT initiative. http://www.edikt.org.

Collaborative Colleagues:
Christophe Dubach: colleagues
Timothy M. Jones: colleagues
Michael F.P. O'Boyle: colleagues