Iterative Optimization in the Polyhedral Model: Part I, One-Dimensional Time
Proceedings of the International Symposium on Code Generation and Optimization
Evaluating Heuristic Optimization Phase Order Search Algorithms
Proceedings of the International Symposium on Code Generation and Optimization
A tuning framework for software-managed memory hierarchies
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Quick and Practical Run-Time Evaluation of Multiple Program Optimizations
Transactions on High-Performance Embedded Architectures and Compilers I
Combined Iterative and Model-driven Optimization in an Automatic Parallelization Framework
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Predictive modeling in a polyhedral optimization space
CGO '11 Proceedings of the 9th Annual IEEE/ACM International Symposium on Code Generation and Optimization
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Modern compilers have limited ability to exploit the performance improvement potential of complex transformation compositions. This is due to the ad-hoc nature of different transformations. Various frameworks have been proposed to provide a unified representation of different transformations, among them is Pughýs Unified Transformation Framework (UTF) [10]. It presents a unified and systematic representation of iteration reordering transformations and their arbitrary combination, which results in a large and complex optimisation space for a compiler to explore. This paper presents a heuristic search algorithm capable of efficiently locating good program optimisations within such a space. Preliminary experimental results on Java show that it can achieve an average speedup of 1.14 on Linux+Celeron and 1.10 on Windows+PentiumPro, and more than 75% of the maximum performance available can be obtained within 20 evaluations or less.