• DocumentCode
    2793127
  • Title

    Automatic Program Segment Similarity Detection in Targeted Program Performance Improvement

  • Author

    Wu, Haiping ; Park, Eunjung ; Kaplarevic, Mihailo ; Zhang, Yingping ; Bolat, Murat ; Li, Xiaoming ; Gao, Guang R.

  • Author_Institution
    Electr. & Comput. Eng. Dept., Delaware Univ., Newark, DE
  • fYear
    2007
  • fDate
    26-30 March 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Targeted optimization of program segments can provide an additional program speedup over the highest default optimization level, such as -O3 in GCC. The key challenge is how to automatically search for performance sensitive program segments in a given code, to which a customized set of optimization compiler options could be applied. In this paper we propose a method for automatic detection of performance sensitive program segments based on program segment similarity. First we create a proxy segment template database trained over a set of random input programs. The compiler identifies program segments by correlating them to the pre-build proxy segment templates using the syntax structure and architecture-dependent behavior similarity. We argue that the identified program segments can be custom optimized to improve the overall program performance. The method is evaluated on the Intel XScale PXA255 platform using randomly selected benchmarks. The experimental results show that our method can provide additional speedups over the highest optimization level in GCC 3.3 (-O3) for an arbitrary set of applications.
  • Keywords
    optimising compilers; program diagnostics; software performance evaluation; GCC 3.3; Intel XScale PXA255 platform; architecture-dependent behavior similarity; automatic performance sensitive program segment detection; optimization compiler; program performance improvement; program segment optimization; program segment similarity detection; proxy segment template database; syntax structure; Data structures; Databases; High performance computing; Kernel; Learning systems; Optimization methods; Optimizing compilers; Program processors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    1-4244-0910-1
  • Electronic_ISBN
    1-4244-0910-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2007.370642
  • Filename
    4228370