Comunicação apresentada no International Workshop on Model-Based Methodologies for Pervasive and Embedded Software (MOMPES 2004), 1, Hamilton, Ontario, Canada, 15-18 June 2004.This paper proposes an automatic partition methodology oriented to develop
data flow dominated embedded systems. The target architecture is
CPU-based with reconfigurable devices on attached board(s), which closely
matches the PSM meta-model applied to system modelling. A PSM flow
graph was developed to represent the system during the partitioning process.
The partitioning task applies known optimization algorithms - tabu search
and cluster growth algorithms - which were enriched with new elements to
reduce computation time and to achieve higher quality partition solutions.
These include the closeness function that guides cluster growth algorithm,
which dynamically adapts to the type of object and partition under analysis.
The methodology was applied to two case studies, and some evaluation
results are presented
