Refactoring for Data Locality

Author

Beyls, K. ; D´Hollander, E.H.

Volume

42

Issue

2

fYear

2009

Firstpage

62

Lastpage

71

Abstract

Refactoring for data locality opens a new avenue for performance-oriented program rewriting. SLO has broken down a large part of the complexity that software developers face when speeding up programs with numerous cache misses. Therefore, we consider SLO to belong to a new generation of program analyzers. Whereas existing cache profilers (generation 1.0) highlight problems such as cache misses, second-generation analyzers (such as SLO) highlight the place to fix problems. Improving data locality is also important in hardware-based applications. SLO was already used to optimize the frame rate and energy consumption in a wavelet decoder implemented on an FPGA. In another vein, the SLO concepts could be incorporated in interactive performance debuggers and profile-directed compilers. We believe that SLO will be useful in the optimization of many data-intensive applications.

Keywords

data handling; program compilers; program debugging; software maintenance; software metrics; FPGA; SLO; cache misses; cache profiler; data locality; energy consumption; interactive performance debuggers; performance-oriented program rewriting; profile-directed compilers; refactoring; second-generation analyzers; software complexity; wavelet decoder; Data visualization; Fuses; Optimizing compilers; Particle measurements; Program processors; Programming profession; Size measurement; Tracking loops; SPEC2000 benchmarks; benchmarks; compilers; computing methodologies; development tools; operating systems; processors; programming languages; simulation; software engineering; visualization;

fLanguage

English

Journal_Title

Computer

Publisher

ieee

ISSN

0018-9162

Type

jour

DOI

10.1109/MC.2009.57

Filename

4781973