A Comprehensive Performance Comparison of Dedicated and Embedded GPU Systems

Abstract

General purpose usage of graphics processing units (GPGPU) is becoming increasingly important asgraphics processing units (GPUs) get more powerful and their widespread usage in performance-orientedcomputing. GPGPUs are mainstream performance hardware in workstation and cluster environments andtheir behavior in such setups are highly analyzed. Recently, NVIDIA, the leader hardware and softwarevendor in GPGPU computing, started to produce more energy efficient embedded GPGPU systems, Jetsonseries GPUs, to make GPGPU computing more applicable in domains where energy and space are limited.Although, the architecture of the GPUs in Jetson systems is the same as the traditional dedicated desktopgraphic cards, the interaction between the GPU and the other components of the system such as mainmemory, central processing unit (CPU), and hard disk, is a lot different than traditional desktop solutions.To fully understand the capabilities of the Jetson series embedded solutions, in this paper we run severalapplications from many different domains and compare the performance characteristics of theseapplications on both embedded and dedicated desktop GPUs. After analyzing the collected data, we haveidentified certain application domains and program behaviors that Jetson series can deliver performancecomparable to dedicated GPU performance.