SPECIAL FEATURE
Edge Computing Embraces AI-GPGPU-based System Performance By Dan Mor, Director, Video & GPGPU Product Line, Aitech Today’s military systems are built with far more functionality in a much smaller footprint, typically referred to as optimized SWaP—size, weight, and power—while still needing to keep costs low. In addition, these systems function in extremely harsh environments and carry with them the need to operate reliably all the time, every time. These rugged HPEC (high-performance embedded computer) systems not only support crucial, lifesaving, and security-focused applications, but must withstand extreme shock and vibration as well as severe and expansive tem-
perature and humidity fluctuations, ranging from sub-zero to triple digits. And they need to capture and process real-time data and graphics from several inputs simultaneously and manage it all from many I/O interfaces, providing what is known as “AI at the Edge.” (Figure 1) Data Challenges in Military Computing Balancing all these requirements pose challenges, but with the right ruggedization and system development techniques, embedded designers are developing AI-based supercomputers used throughout several military applications, such as situation awareness systems,
EW systems, and drones as well as a smart soldier and man-portable systems and augmented reality. Especially noteworthy is the growing field of autonomous operations utilizing this powerful technology including UAVs (unmanned aerial vehicles) and unmanned ground vehicles (UGVs). These real-time response applications require this AI at the edge, where processing that is happening at the sensors is exponentially increasing computing requirements. (Figure 2 on next page)
Figure 1: Military applications are increasingly using rugged, SWaP-optimized HPEC systems based on leading-edge technologies, like GPGPU, that facilitate AI computing. 16
COTS Journal | February 2022
