A Technologically Agnostic Framework for Cyber-Physical and IoT Processing-in-Memory-based Systems Simulation

Smart devices based on Internet of Things (IoT) and Cyber-Physical System (CPS) are emerging as an important and complex set of applications in the modern world. These systems can generate a massive amounts of data, due to the enormous quantity of sensors being used in modern applications, which can either stress the communication mechanisms or need extra resources to treat data locally. In the era of efficient smart devices, the idea of transmitting huge amounts of data is prohibitive. Furthermore, implementing traditional architectures imposes limits on achieving the required efficiency. Within the area, power, and energy constraints, Processing-in-Memory(PIM) has emerged as a solution for efficiently processing big data. By using PIM, the generated data can be processed locally, with reduced power and energy costs, allowing an efficient solution for CPS and IoT data management problem. However, two main tools are fundamental on this scenario: a simulator that allows architectural performance and behavior analysis is essential within a project life-cycle, and a compiler able to automatically generate code for the targeted architecture with obvious improvements of productivity. Also, with the emergence of new technologies, the ability to simulate PIM coupled to the latest memory technologies is also important. This work presents a framework able to simulate and automatically generate code for IoT PIM-based systems. Also, supported by the presented framework, this work proposes an architecture that shows an efficient loT PIM system able to compute a real image recognition application. The proposed architecture is able to process 6 x more frames per second than the baseline, while improving the energy efficiency by 30 x. (C) 2019 Elsevier B.V. All rights reserved.