|
|
8th International Workshop on
Software and Compilers for Embedded Systems
SCOPES 2004
Workshop Program - Presentation Abstract
| An Automated C++ Code and Data Partitioning Framework for Data
Management of Data-Intensive Applications |
Athanasios Milidonis - VLSI Design Lab., Dept. of Elect. and
Comp. Eng., University of Patras
Grigoris Dimitroulakos - VLSI Design Lab., Dept. of Elect. and Comp.
Eng., University of Patras
Michalis Galanis - VLSI Design Lab., Dept. of Elect. and Comp. Eng.,
University of Patras
George Theodoridis - Section of Electr. & Computers, Dept. of
Physics, Aristotle Univ. of Thessaloniki
Francky Catthoor - IMEC, Kapeldreef 75 B-3001 Leuven, Belgium
Costas Goutis - VLSI Design Lab., Dept. of Elect. and Comp. Eng.,
University of Patras
|
| An automated framework for code and data partitioning for the needs
of data management is presented. The goal is to identify the main data
types from the data management perspective and to separate them from the
many smaller data in the code. First, static and dynamic analysis is
performed on the initial C++ specification code. Based on the analysis
results the data types of the application are characterized as crucial
or non-crucial. Afterwards, the code is automatically rewritten in such
a way that the crucial data types and the code portions that manipulate
them are separated from the rest of the code. Thus, the complexity is
reduced allowing the designer to easily focus on the important parts of
the code to perform further refinements and optimizations. Experiments
on well-known multimedia and telecom applications prove the correctness
of the performed automated analysis and code rewriting as well as the
applicability of the introduced framework in terms of execution time and
memory requirements. Comparisons with Rationals QuantifyTM suite
demonstrate the failure of Quantify to analyze correctly the initial
code for the needs of data management. |
Presentation
|