Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization
Although automated empirical performance optimization and tuning is well-studied for kernels and domain-specific libraries, a current research grand challenge is how to extend these methodologies and tools to significantly larger sequential and parallel applications. In this context, we present the ROSE source-to-source outliner, which addresses the problem of extracting tunable kernels out of whole programs, thereby helping to convert the challenging whole-program tuning problem into a set of more manageable kernel tuning tasks. Our outliner aims to handle large scale C/C++, Fortran and OpenMP applications. A set of program analysis and transformation techniques are utilized to enhance the portability, scalability, and interoperability of source-to-source outlining. More importantly, the generated kernels preserve performance characteristics of tuning targets and can be easily handled by other tools. Preliminary evaluations have shown that the ROSE outliner serves as a key component within an end-to-end empirical optimization system and enables a wide range of sequential and parallel optimization opportunities.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 966918
- Report Number(s):
- LLNL-CONF-414916; TRN: US200922%%313
- Resource Relation:
- Journal Volume: 5898; Conference: Presented at: International Workshop on Languages and Compilers for Parallel Computing, Newark, DE, United States, Oct 08 - Oct 10, 2009
- Country of Publication:
- United States
- Language:
- English
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