Microarchitecture sensitive empirical models for compiler optimizations

International Symposium on Code Generation and Optimization, CGO 2007

Volumn , Issue , 2007, Pages 131-143

  Vaswani, Kapil ^a   Thazhuthaveetil, Matthew J ^a   Srikant, Y N ^a   Joseph, P J ^b  

^a INDIAN INSTITUTE OF SCIENCE   (India)

^b Freescale ^*  (India)

Author keywords

[No Author keywords available]

Indexed keywords

EMPIRICAL MODELS; MEASURING PERFORMANCE; MICROARCHITECTURE;

COMPUTER ARCHITECTURE; COMPUTER SIMULATION; ERROR ANALYSIS; HEURISTIC ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; REGRESSION ANALYSIS; SENSITIVITY ANALYSIS;

PROGRAM COMPILERS;

EID: 34547681859     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CGO.2007.25     Document Type: Conference Paper

References (21)

1. F. Agakov, E. Bonilla, J. Cavazos, B. Franke, G. Fursin, M. F. P. Boyle, J. Thomson, M. Toussaint, and C. K. I. Williams. Using Machine Learning to Focus Iterative Optimization. In Proc. of CGO, 2006.
2. L. Almagor, K. Cooper, A. Grosul, T. Harvey, S. Reeves, D. Subramaniam, L. Torczon, and T. Waterman. Finding Effective Compilation Sequences. In Proc. of LCTES, 2004.
3. D. S. Broomhead and D. Love. Multivariate Function Interpolation and Adaptive Networks. Complex Systems, 1988.
4. J. Cavazos, C. Dubach, F. Agakov, E. Bonilla, M. F. P. O'Boyle, G. Fursin, and O. Temam. Automatic Performance Model Construction for the Fast Software Exploration of New Hardware Designs. In Proc. of CASES, 2006.
5. J. H. Friedman. Multivariate Adaptive Regression Splines. The Annals of Statistics, pages 1-141, 1991.
6. M. Haneda, P. M. W. Knijnenburg, and H. A. G. Wijshoff. Automatic Selection of Compiler Options using Nonparametric Inferential Statistics. In Proc. of PACT, 2005.
7. P. J. Joseph, K. Vaswani, and M. J. Thazhuthaveetil. A Predictive Model for Superscalar Processor Performance. In Proc. of MICRO, 2006.
8. P. J. Joseph, K. Vaswani, and M. J. Thazhuthaveetil. Construction and Use of Linear Regression Models for Processor Performance Analysis. In Proc. of HPCA, 2006.
9. T. Kisuki, P. M. W. KnijnenBurg, and M. F. P. O'Boyle. Combined Selection of Tile Size and Unroll Factors using Iterative Compilation. In Proc. of PACT, 2000.
10. P. Kulkarni, S. Hines, J. Hiser, D. Whalley, J. Davidson, and D. Jones. Fast Searches for Effective Optimization Phase Sequences. In Proc. of PLDI, 2004.
11. D. C. Montgomery. Design and Analysis of Experiments. Wiley, 5th edition, 2001.
12. M. Orr, J. Hallam, K. Takezawa, A. Murray, S. Ninomiya, M. Oide, and T. Leonard. Combining Regression Trees and Radial Basis Function Networks. International Journal of Neural Systems, 2000.
13. V. Sarkar and N. Megiddo. An Analytic Model for Loop Tiling and its Solution. In Proc. of ISPASS, 2000.
14. T. Sherwood, E. Perelman, G. Hamerly, and B. Calder. Automatically Characterizing Large Scale Program Behavior. In Proc. of ASPLOS, 2002.
15. M. Stephenson and S. Amarasinghe. Predicting Unroll Factors Using Supervised Classification. In Proc. of CGO, 2005.
16. M. Stephenson, S. Amarasinghe, M. Martin, and U.-M. O-Reily. Meta Optimization: Improving Compiler Heuristics using Machine Learning. In Proc. of PLDI, 2003.
17. S. Triantafyllis, M. Vachharajani, N. Vachharajani, and D. I. August. Compiler Optimization Space Exploration. In Proc. of CGO, 2003.
18. M. E. Wolf, D. E. Maydan, and D. Chen. Combining Loop Transformations Considering Caches and Scheduling. In Proc. of MICRO, 1996.
19. R. E. Wunderlich, B. F. T. F. Wenisch, and J. C. Hoe. SMARTS: Accelerating Microarchitecture Simulation via Rigorous Statistical Sampling. In Proc. of ISCA, 2003.
20. M. Zhao, B. R. Childers, and M. L. Soffa. Predicting the Impact of Optimizations for Embedded Systems. In Proc. of LCTES, 2003.
21. M. Zhao, B. R. Childers, and M. L. Soffa. A Model-based Framework: an Approach to Profit-driven Optimization. In Proc. of CGO, 2005.