Compilers for Low Power with Design Patterns on Embedded Multicore Systems

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Minimization of power dissipation can be considered at algorithmic, compilers, architectural, logic, and circuit levels. Recent research trends for multicore programming models have come to the direction that parallel design patterns can be a solution to develop multicore applications. As parallel design patterns are with regularity, we view this as a great opportunity to exploit power optimizations in the software layer. In this paper, we present case studies to investigate compilers for low power with parallel design patterns on embedded multicore systems. We evaluate two major parallel design patterns, Pipe and Filter and MapReduce with Iterator. Our work, attempts to devise power optimization schemes in compilers by exploiting the opportunities of the recurring patterns of embedded multicore programs. In all two cases of the patterns investigated, the common recurring patterns of programs are exploited to seek the opportunity for compiler optimizations for low power. Proposed optimization schemes are rate-based optimization for Pipe and Filter pattern and early-exit power optimization for MapReduce with Iterator pattern. Our experiment is based on a power simulator simulating a heterogeneous multicore system under SID simulation framework. In our experiments, a finite impulse response (FIR) program with Pipe and Filter pattern and an image recognition application applied MapReduce with Iterator pattern are evaluated by incorporating our proposed power optimization schemes for each pattern. Significant power reductions are observed in all two cases. With the case study, we present a direction for power optimizations that one can further identify additional key design patterns for embedded multicore systems to explore power optimization opportunities via compilers.