The rise of the Internet of Things has led to an explosion of new sensor computing platforms. The complexity and application domains of IoT devices range from simple self-monitoring devices in vending machines to complex interactive devices with artificial intelligence in smart vehicles and drones. As IoT developers wish to meet more aggressive platform objectives and protect market share through feature differentiation, they must choose between low-cost, and lowperformance CPU-based commercial-off-the-shelf (COTS) systems, and high-performance custom platforms with hardware accelerators such as GPU and FPGA. Both COTS and custom platform designs introduce a variety of design challenges -the extreme pressures on time-to-market, design cost, and development risk are also driving a voracious demand for new CAD technologies to enable rapid, low cost design of effective IoT platforms with smaller design teams and lower risk. In this article, we present a generic IoT device design flow and discuss platform choices available for IoT devices to efficiently tradeoff cost, power, performance and volume constraints: CPUbased systems, and custom platforms that contain hardware accelerators such as FPGA and embedded GPUs. We demonstrate this design process through a driving application in computer vision. We also present current critical design automation needs for IoT development and demonstrate how our prior work in CAD for FPGAs and SoCs begin to address these needs.
While REF presents the generic IoT device design flow and various platform choices for IoT devices to efficiently tradeoff cost, power, performance and volume constraints.
Platform choices and design demands for IoT platforms: cost, power, and performance tradeoffs
IET Cyper-Phys. Syst.: Theory & Appl.
IET Cyper-Phys. Syst.: Theory & Appl.
Engineering Computer Science