Data storage and processing for the ‘tactical edge’ in military operations

This article originally appeared in the March ’22 issue of Electronic Specifier Design– see ES's Magazine Archives for more featured publications.

Embedded computing systems feature on the frontline of many military and defence applications and many of these technologies serve the purpose of collecting and sharing information. Overhauling and modernising military operations is particularly challenging due to the requirements of the given embedded systems at the tactical edge. These systems must first process input data efficiently and effectively in harsh operating environments, which involves an ever-increasing amount of processing power and careful design considerations. The processed data then needs to be communicated rapidly, reliably and securely to other networked systems.

In military operations it is not only the quantity of data that has increased in recent years but the quality, which in turn increases the required processing capabilities.

To handle the increase in data intensity, embedded computing has seen a rise in the use of AI and general-purpose calculation on GPUs to accelerate computing capabilities. By relying on proven ruggedisation techniques as well as verified testing methodologies, GPU-accelerated computing can offer unique data processing, memory, and power efficiency system performance advantages in even in the harshest of environments.

AI and general-purpose GPU (GPGPU) computing is based on parallel computing architectures, such as NVIDIA’s Compute Unified Device Architecture (CUDA). This allows GPGPUs to process tens of thousands of data points simultaneously (versus the hundreds that use serial processing). Even a typical multicore CPU-based architecture only offers a handful of cores running in parallel. When integrated into a ruggedised system, GPGPUs can meet the growing data requirements of today’s military applications in terms of raw processing capacity at the edge. With the data pre-processed or locally processed, it then generally needs to be communicated. However, unlike more stationary operating environments, rugged, mobile and mission-critical systems operate in places with volatile connections and may need to house data onboard until the network is restored. As such, storage is a key consideration: such developments as compact, high-density, flash-based modules have increased onboard storage capacities alongside the edge processing potentials of GPGPUs that reduce the data footprint. The potential of GPGPU and AI at the military tactical edge not only supports the modernisation efforts of forces globally, it is also accelerating the manufacturing and design capabilities of entirely new systems. Finding success in military data processing The key to military data processing success is ensuring that embedded systems at the tactical edge are up to the task – and this can only be achieved by giving due consideration to the processing and storage technologies required. Accordingly, systems such as those mentioned above are emerging and offering military operations the tactical ‘edge’ they need.