Case Study on Integrated Architecture for In-Memory and In-Storage Computing

Since the advent of computers, computing performance has been steadily increasing. Moreover, recent technologies are mostly based on massive data, and the development of artificial intelligence is accelerating it. Accordingly, various studies are being conducted to increase the performance and computing and data access, together reducing energy consumption. In-memory computing (IMC) and in-storage computing (ISC) are currently the most actively studied architectures to deal with the challenges of recent technologies. Since IMC performs operations in memory, there is a chance to overcome the memory bandwidth limit. ISC can reduce energy by using a low power processor inside storage without an expensive IO interface. To integrate the host CPU, IMC and ISC harmoniously, appropriate workload allocation that reflects the characteristics of the target application is required. In this paper, the energy and processing speed are evaluated according to the workload allocation and system conditions. The proof-of-concept prototyping system is implemented for the integrated architecture. The simulation results show that IMC improves the performance by 4.4 times and reduces total energy by 4.6 times over the baseline host CPU. ISC is confirmed to significantly contribute to energy reduction.