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LCTRTS
2010
Springer
13 years 5 months ago
Improving both the performance benefits and speed of optimization phase sequence searches
The issues of compiler optimization phase ordering and selection present important challenges to compiler developers in several domains, and in particular to the speed, code size,...
Prasad A. Kulkarni, Michael R. Jantz, David B. Wha...
BMCBI
2007
161views more  BMCBI 2007»
13 years 7 months ago
Efficient classification of complete parameter regions based on semidefinite programming
Background: Current approaches to parameter estimation are often inappropriate or inconvenient for the modelling of complex biological systems. For systems described by nonlinear ...
Lars Kuepfer, Uwe Sauer, Pablo A. Parrilo
PLDI
2004
ACM
14 years 24 days ago
Fast searches for effective optimization phase sequences
It has long been known that a fixed ordering of optimization phases will not produce the best code for every application. One approach for addressing this phase ordering problem ...
Prasad Kulkarni, Stephen Hines, Jason Hiser, David...
CGO
2009
IEEE
14 years 2 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 27 days ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...