A Processing-in-Memory Architecture Programming Paradigm for Wireless Internet-of-Things Applications

The widespread applications of the wireless Internet of Things (IoT) is one of the leading factors in the emerging of Big Data. Huge amounts of data need to be transferred and processed. The bandwidth and latency of data transfers have posed a new challenge for traditional computing systems. Under Big Data application scenarios, the movement of large scales of data would influence performance, power efficiency, and reliability, which are the three fundamental attributes of a computing system. Thus, changes in the computing paradigm are demanding. Processing-in- Memory (PIM), aiming at placing computation as close as possible to memory, has become of great interest to academia as well as industries. In this work, we propose a programming paradigm for PIM architecture that is suitable for wireless IoT applications. A data-transferring mechanism and middleware architecture are presented. We present our methods and experiences on simulation-platform design, as well as FPGA demo design, for PIM architecture. Typical applications in IoT, such as multimedia and MapReduce programs, are used as demonstration of our method's validity and efficiency. The programs could successfully run on the simulation platform built based on Gem5 and on the FPGA demo. Results show that our method could largely reduce power consumption and execution time for those programs, which is very beneficial in IoT applications.