ROBCOMM: Robust Compute-in Memory using Memristors

• Applicants: Professor Mehdi B. Tahoori, Ph.D.; Dr. Dirk Wouters
• Subject Area: Computer Architecture, Embedded and Massively Parallel Systems ; Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 441857533

Emerging applications (such as Internet-of-Things and Big Data analytics) are posing serious challenges on current computer architectures and technologies. Therefore, there is an urgent need to explore alternative architectures, not only to further increase the computing efficiency at lower cost, but also to further reduce the overall energy. Further, new device technologies are emerging that, in combination with new architectures, may compete with no-longer-scaling CMOS. Moving computation to memory (data-centric computing) is an emerging computing paradigm shown to have a huge potential in terms of overall computing efficiency. This computing paradigm is also referred to as Computation-in-Memory (CIM). Moving the computation to the memory (rather than doing it in the CPU) will significantly reduce the communication and therefore reduce the power consumption and increase the performance.The most promising solutions for CIM architectures are based on the use of emerging device technologies, such as resistive or magneto-resistive devices, that are able to act as both storage and information processing unit. These, more generally called memristive devices, reduce the overall energy consumption as the devices are non-volatile and the leakages is practically zero, and also they do not require any refresh as it is the case for DRAM, etc. Hence, memristive devices favour increasing system complexity and performance at lower power consumption; thus, providing the scientific community with opportunities for new computer architecture innovations being able to track today’s limitation. However, realizing such a paradigm strongly depends on the development of high quality, reliable and power efficient circuit primitives that enable both storage and computing.This project aims at designing and demonstrating high quality, reliable, robust and energy efficient primitive circuits based on memristive devices to enable computation-in-memory architectures. In particular, we aim at the development of robust CIM circuits based on memristive device by i) carefully modeling and analyzing the effects of memristive device (un)reliability on CIM operation and ii) develop reliability-aware and fault/variation tolerant design of CIM circuits.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2262: Memristive Devices Toward Smart Technical Systems