A Framework for Task Scheduling and Memory Partitioning for Multi-Processor System-on-Chip

Abstract

The growing trend in current complex embedded systems is the use of multiprocessor system-on-chip (MPSoC). An MPSoC consists of multiple heterogeneous processing elements, a memory hierarchy, and input/output components which are linked together by an on-chip interconnect structure. Using such an architecture provides the flexibility to meet the performance requirements of multimedia applications while respecting the constraints on memory, cost, size, time and power. Such embedded systems employ software-managed memories known as scratch-pad memories (SPM). Scratchpad memories, unlike caches, are software-controlled and hence the execution time of applications on such systems can be accurately predicted and controlled. Scheduling the tasks of an application on the processors as well as partitioning the available SPM budget among those processors are two critical issues in reducing the overall computation time as well as the communication overhead. Traditionally, the step of task scheduling is applied separately from the memory partitioning step. Such a decoupled approach may miss better quality schedules. In this paper, we present an effective heuristic that integrates task allocation and SPM partitioning to further reduce the execution time of embedded applications. Results on several real life benchmarks show the significant improvement of our proposed technique compared to decoupled techniques as well as to an integer-linear programming approach.