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» Meta optimization: improving compiler heuristics with machin...
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PLDI
2004
ACM
13 years 10 months ago
Inducing heuristics to decide whether to schedule
Instruction scheduling is a compiler optimization that can improve program speed, sometimes by 10% or more—but it can also be expensive. Furthermore, time spent optimizing is mo...
John Cavazos, J. Eliot B. Moss
CC
2006
Springer
124views System Software» more  CC 2006»
13 years 8 months ago
Hybrid Optimizations: Which Optimization Algorithm to Use?
We introduce a new class of compiler heuristics: hybrid optimizations. Hybrid optimizations choose dynamically at compile time which optimization algorithm to apply from a set of d...
John Cavazos, J. Eliot B. Moss, Michael F. P. O'Bo...
ML
2008
ACM
135views Machine Learning» more  ML 2008»
13 years 4 months ago
Compiling pattern matching to good decision trees
We address the issue of compiling ML pattern matching to compact and efficient decisions trees. Traditionally, compilation to decision trees is optimized by (1) implementing decis...
Luc Maranget
ICPR
2006
IEEE
14 years 6 months ago
Machine Learning for Video Compression: Macroblock Mode Decision
Video Compression currently is dominated by engineering and fine-tuned heuristic methods. In this paper, we propose to instead apply the well-developed machinery of machine learni...
Christoph H. Lampert
CGO
2007
IEEE
13 years 11 months ago
Microarchitecture Sensitive Empirical Models for Compiler Optimizations
This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program perform...
Kapil Vaswani, Matthew J. Thazhuthaveetil, Y. N. S...