A framework for automatic parallelization, static and dynamic memory optimization in MPSoC platforms

The key characteristic of next generation embedded applications will be the intensive data transfer and storage and the need for efficient memory management. The embedded system designer community needs optimization methodologies and techniques, which do not change the input-output functionality of the software applications or the design of the underlying hardware platform. In this paper, the key focus is the efficient data access and memory storage of both dynamically and statically allocated data and their assignment on the data memory hierarchy of an MPSoC platform. We propose a design tool framework to efficiently automate the time-consuming optimizations for parallelization and memory mapping of static and dynamic data for MPSoCs.