Characterizing Variability in Heterogeneous Edge Systems: A Methodology & Case Study

Hazem A. Abdelhafez, Hassan Halawa, Amr Almoallim, Amirhossein Ahmadi, Karthik Pattabiraman, and Matei Ripeanu. To appear in the ACM/IEEE International Symposium on Edge Computing (SEC), 2022. (Acceptance Rate: TBD) [ PDF (coming soon) | Talk ]

Abstract: This study offers a methodology to characterize intra- and inter-node variability and applies it for two heterogeneous edge platforms (the NVIDIA Jetson AGX and Nano) for performance and power consumption. Firstly, we explore intra-node variability: understand to what degree deployment decisions can limit it, highlight that it is unavoidable, and offer a scale so that one can compare to what other studies report. Secondly, we characterize inter-node variability by answering two questions: (i) Are the platforms we study statistically different in terms of the applications’ power draw and runtime?, and (ii) What is the magnitude of these differences?. Finally, we attempt to answer the question of why is it paramount to characterize variability and take it into account?, to achieve this, we discuss examples from the compiler and runtime optimization domains.

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