Quantifying Process Variations and Its Impacts on Smartphones

Guru Prasad Srinivasa, University at Buffalo
Scott Haseley, University of Illinois at Urbana-Champaign
Mark Hempstead, Tufts University
Geoffrey Challen, University of Illinois at Urbana-Champaign

Proceedings of the 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2019). March 2019. Madison, WI.



Process variation can cause the performance and energy consumption of smartphones of the same model to vary significantly. While process variation has been studied in detail, the effects on smartphone performance have not been quantified and evaluated. In this work we study the performance and energy differences of 5 recent SoC generations caused by underlying process variation.

We make two important contributions. First, we present a methodology to construct a temperature-stabilized environment to perform repeatable power and performance measurements. Studying power-performance characteristics of smartphones is difficult. Running a benchmark back-to-back often produces significantly different results due to heat. Temperature, both device and ambient, play a significant role in determining performance and energy. Our methodology allows us to control for various factors and isolate the effects of the underlying process variation. We then apply our methodology to investigate performance and energy characteristics of several recent generations of smartphone CPUs that result from process variation. Our results show that devices of the same model may exhibit differences of 10% and 12% difference in performance and energy over a fixed-duration workload.