Fix the code. Don't tweak the hardware: A new compiler approach to Voltage-Frequency scaling

  • Authors:
  • Alexandra Jimborean;Konstantinos Koukos;Vasileios Spiliopoulos;David Black-Schaffer;Stefanos Kaxiras

  • Affiliations:
  • Uppsala University;Uppsala University;Uppsala University;Uppsala University;Uppsala University

  • Venue:
  • Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization
  • Year:
  • 2014

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Abstract

Traditional compiler approaches to optimize power efficiency aim to adjust voltage and frequency at runtime to match the code characteristics to the hardware (e.g., running memory-bound phases at a lower frequency). However, such approaches are constrained by three factors: (i) voltage-frequency transitions are too slow to be applied at instruction granularity, (ii) larger code regions are seldom unequivocally memory- or compute-bound, and, (iii) the available voltage scaling range for future technologies is rapidly shrinking. These factors necessitate new approaches to address power-efficiency at the code-generation level. This paper proposes one such approach to automatically generate power-efficient code using a decoupled access/execute (DAE) model. In DAE a program is split into tasks, where each task consists of two sufficiently coarse-grained phases to enable effective Dynamic Voltage Frequency Scaling (DVFS): (i) the access-phase for data prefetch (heavily memory-bound), and (ii) the execute-phase that performs the actual computation (heavily compute-bound). Our contribution is to provide a compiler methodology to automatically generate the access-phases for a task-based programming system. Our approach is capable of handling both affine (through a polyhedral analysis) and non-affine codes (through optimized task skeletons). Our evaluation shows that the automatically generated versions improve EDP by 25% on average compared to a coupled execution, without any performance degradation, and surpasses the EDP savings of the corresponding hand-crafted tasks by 5%.