Optimizing ML with run-time code generation
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Dynamic feedback: an effective technique for adaptive computing
Proceedings of the ACM SIGPLAN 1997 conference on Programming language design and implementation
An evaluation of staged run-time optimizations in DyC
Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation
Calpa: a tool for automating selective dynamic compilation
Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture
High-level adaptive program optimization with ADAPT
PPoPP '01 Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming
Adaptive Optimizing Compilers for the 21st Century
The Journal of Supercomputing
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
A Feasibility Study in Iterative Compilation
ISHPC '99 Proceedings of the Second International Symposium on High Performance Computing
Compiler optimization-space exploration
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
A comparison of empirical and model-driven optimization
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Meta optimization: improving compiler heuristics with machine learning
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
ADAPT: Automated De-Coupled Adaptive Program Transformation
ICPP '00 Proceedings of the Proceedings of the 2000 International Conference on Parallel Processing
Automatically Tuned Linear Algebra Software
Automatically Tuned Linear Algebra Software
Fast and Effective Orchestration of Compiler Optimizations for Automatic Performance Tuning
Proceedings of the International Symposium on Code Generation and Optimization
Fast, automatic, procedure-level performance tuning
Proceedings of the 15th international conference on Parallel architectures and compilation techniques
Speculative thread decomposition through empirical optimization
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
PEAK—a fast and effective performance tuning system via compiler optimization orchestration
ACM Transactions on Programming Languages and Systems (TOPLAS)
Collective optimization: A practical collaborative approach
ACM Transactions on Architecture and Code Optimization (TACO)
Deconstructing iterative optimization
ACM Transactions on Architecture and Code Optimization (TACO)
On the determination of inlining vectors for program optimization
CC'13 Proceedings of the 22nd international conference on Compiler Construction
Algorithms of the combination of compiler optimization options for automatic performance tuning
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
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To achieve maximum performance gains through compiler optimization, most automatic performance tuning systems use a feed-back directed approach to rate the code versions generated under different optimization options and to search for the best one. They all face the problem that code versions are only comparable if they run under the same execution context. This paper proposes three accurate, fast and flexible rating approaches that address this problem. The three methods identify comparable execution contexts, model relationships between contexts, or force re-execution of the code under the same context, respectively. We apply these methods in an automatic offline tuning scenario. Our performance tuning system improves the program performance of a selection of SPEC CPU 2000 benchmarks by up to 178% (26% on average). Our techniques reduce program tuning time by up to 96% (80% on average), compared to the state-of-the-art tuning scenario that compares optimization techniques using whole-program execution.