Understanding the landscape of accelerators for vision

Visual analytics applications are becoming ubiquitous and embedded in various systems that we interact with daily. Limited power budgets and the need for high performance for cognitive visual analytics have led to a three-pronged approach of integrating advances in algorithms, architectures and technology towards designing next generation vision accelerators. Vision applications benefit from increasing processor customization, emerging devices and technologies such as Tunnel-FETs and Resistive- RAMs, and trends in non-Boolean computing such as Cellular Neural Networks (CNNs) and neuromorphic architectures. This paper provides an overview of the evolving landscape of vision accelerators.