Snowflakes at the Edge: A Study of Variability among NVIDIA Jetson AGX Xavier Boards

Abstract

While applications deployed at the edge often rely on performance stability (or, at a minimum, on a predictable level of performance), variability at the edge remains a real problem [4]. This study uncovers a surprising source of variability: intrinsic variability (in performance and power consumption) among edge platforms that are nominally identical. We focus on a popular platform designed for edge applications, the NVIDIA Jetson AGX, and aim to answer the following high-level questions through rigorous statistical analysis: (i) are the edge devices in our study statistically different from each other in terms of applications’ runtime performance and power draw (although they are sold under the same product model and family)?, (ii) if the differences between these edge devices are statistically significant, what is the magnitude of these differences?, and (iii) do these differences matter from the application’s perspective?.

Publication
In Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking (EdgeSys)
Hazem A. Abdelhafez
Hazem A. Abdelhafez
Senior GPU Compiler Engineer

My research interests lie in the intersection of compilers, GPU and heterogeneous computing systems, performance and power consumption modeling and characterization.