PIM-IoT: Enabling hierarchical, heterogeneous, and agile Processing-in-Memory in IoT systems

Abstract

The Internet of Things (IoT) is an emerging concept that senses the physical world by connecting various “things” and objects to the Internet. Conventional cloud-based IoT systems are unlikely to keep up with the diverse needs of IoT applications and have some issues, such as privacy and latency. Edge computing based IoT systems solve these issues by placing data processing and inference tasks near the data source. However, due to the increasing complexity of IoT applications, performing data processing and inference tasks in edge computing based IoT systems can lead to high energy consumption and latency.

Processing-in-Memory (PIM) is a promising solution to reduce the energy consumption of data processing and inference tasks by closely integrating computational logics with memory device. Therefore, in this paper, we propose PIM-IoT, a PIM architectures enabled IoT system to reduce the energy consumption. To accommodate various data processing tasks, we architect PIM-IoT as a hierarchical system that consists of 3 tiers: sensing tier, gateway tier, and edge computing tier. We first analyze the dataflow of typical IoT applications and map tasks to different tiers. To handle the data processing and inference tasks effectively in each tier, we then propose hierarchical, heterogeneous, and collaborative PIM architectures for each tier. Finally, we show how multi-tier can be co-optimized under latency and power constraints. To our knowledge, this is the first work to explore novel PIM architectures in IoT systems. Detailed analysis and experimental results show that PIM-IoT can achieve 5.6x performance improvement and 6x energy consumption reduction for IoT applications.