Article Title

A Comprehensive Performance Comparison of Dedicated and Embedded GPU Systems


General purpose usage of graphics processing units (GPGPU) is becoming increasingly important as graphics processing units (GPUs) get more powerful and their widespread usage in performance-oriented computing. GPGPUs are mainstream performance hardware in workstation and cluster environments and their behavior in such setups are highly analyzed. Recently, NVIDIA, the leader hardware and software vendor in GPGPU computing, started to produce more energy efficient embedded GPGPU systems, Jetson series 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 desktop graphic cards, the interaction between the GPU and the other components of the system such as main memory, 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 several applications from many different domains and compare the performance characteristics of these applications on both embedded and dedicated desktop GPUs. After analyzing the collected data, we have identified certain application domains and program behaviors that Jetson series can deliver performance comparable to dedicated GPU performance.