Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
An approach for exploring code improving transformations
ACM Transactions on Programming Languages and Systems (TOPLAS)
Advanced compiler design and implementation
Advanced compiler design and implementation
Optimizing for reduced code space using genetic algorithms
Proceedings of the ACM SIGPLAN 1999 workshop on Languages, compilers, and tools for embedded systems
VISTA: a system for interactive code improvement
Proceedings of the joint conference on Languages, compilers and tools for embedded systems: software and compilers for embedded systems
Compiler Construction
Theory and Practice of Compiler Writing
Theory and Practice of Compiler Writing
A Machine Learning Approach to Automatic Production of Compiler Heuristics
AIMSA '02 Proceedings of the 10th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Compiler optimization-space exploration
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Predicting the impact of optimizations for embedded systems
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
Meta optimization: improving compiler heuristics with machine learning
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Combined Selection of Tile Sizes and Unroll Factors Using Iterative Compilation
PACT '00 Proceedings of the 2000 International Conference on Parallel Architectures and Compilation Techniques
Adaptive java optimisation using instance-based learning
Proceedings of the 18th annual international conference on Supercomputing
Cole: compiler optimization level exploration
Proceedings of the 6th annual IEEE/ACM international symposium on Code generation and optimization
Callgraph properties of executables
AI Communications - Network Analysis in Natural Sciences and Engineering
OptiScope: Performance Accountability for Optimizing Compilers
Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
On the determination of inlining vectors for program optimization
CC'13 Proceedings of the 22nd international conference on Compiler Construction
Performance potential of optimization phase selection during dynamic JIT compilation
Proceedings of the 9th ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
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The problem of defining optimal optimization strategies for compilers is well known and has been studied extensively over the last years. The problem arises from the fact that the sheer number of possible combinations of optimizations, their order, and their setting creates a search space which cannot adequately be searched. Although it has been shown that compiler settings can be found that outperform standard -Ox switches for a single application, it is not known how to find such settings that work well for sets of applicationsIn this paper, we introduce a statistical technique to derive a methodology which trims down the search space considerably, thereby allowing a feasible and flexible solution for defining high performance optimization strategies. We show that our technique finds a single compiler setting for a collection of programs (SPECint95) that performs better than the standard -Ox settings of gcc. 3.3.1.