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The Impact of Precision Tuning on Embedded Systems Performance: A Case Study on Field-Oriented Control

Authors Gabriele Magnani , Daniele Cattaneo , Michele Chiari , Giovanni Agosta

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Author Details

Gabriele Magnani
  • DEIB, Politecnico di Milano, Italy
Daniele Cattaneo
  • DEIB, Politecnico di Milano, Italy
Michele Chiari
  • DEIB, Politecnico di Milano, Italy
Giovanni Agosta
  • DEIB, Politecnico di Milano, Italy

Funding

Work supported by the FET-HPC project RECIPE, G.A. n. 801137.

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Gabriele Magnani, Daniele Cattaneo, Michele Chiari, and Giovanni Agosta. The Impact of Precision Tuning on Embedded Systems Performance: A Case Study on Field-Oriented Control. In 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021). Open Access Series in Informatics (OASIcs), Volume 88, pp. 3:1-3:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/OASIcs.PARMA-DITAM.2021.3

Abstract

Field Oriented Control (FOC) is an industry-standard strategy for controlling induction motors and other kinds of AC-based motors. This control scheme has a very high arithmetic intensity when implemented digitally - in particular it requires the use of trigonometric functions. This requirement contrasts with the necessity of increasing the control step frequency when required, and the minimization of power consumption in applications where conserving battery life is paramount such as drones. However, it also makes FOC well suited for optimization using precision tuning techniques. Therefore, we exploit the state-of-the-art FixM methodology to optimize a miniapp simulating a typical FOC application by applying precision tuning of trigonometric functions. The FixM approach itself was extended in order to implement additional algorithm choices to enable a trade-off between execution time and code size. With the application of FixM on the miniapp, we achieved a speedup up to 278%, at a cost of an error in the output less than 0.1%.

Subject Classification

ACM Subject Classification
  • Hardware → Power estimation and optimization
  • Software and its engineering → Compilers
  • Applied computing → Consumer health
Keywords
  • Approximate Computing
  • Field-oriented control
  • Precision Tuning

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