Perspectives on Emerging Computation-in-Memory Paradigms
Shubham Rai1, Mengyun Liu2, Anteneh Gebregiorgis3, Debjyoti Bhattacharjee4, Krishnendu Chakrabarty2, Said Hamdioui3, Anupam Chattopadhyay5, Jens Trommer6 and Akash Kumar1
1Chair for Processor Design, Technische Universität Dresden, Germany
2Department of Electrical and Computer Engineering, Duke University, USA
3Department of Quantum and Computer Engineering, Delft University of Technology, The Netherlands
4imec, Leuven, Belgium
5School of Computer Science and Engineering, Nanyang Technological University, Singapore
6Namlab gGmbH, Dresden, Germany
ABSTRACT
The traditional Von-Neumann architecture is reaching its limits and finding it difficult to cope up with the ever-increasing demands of modern workloads like artificial intelligence. This demand has fueled the search of technologies that can mimic human brain to efficiently combine both memory and computation within a single device. In this work, we present the state-of-the-art research in the domain of computation-inmemory. In particular, we take a look at memristors and its widespread application in neuromorphic computation. We introduce ReRAMs in terms of their novel computing paradigms and present ReRAM-specific design flows.We address the various circuit opportunities and challenges related to reliability and fault tolerance associated with them. Another high-potential candidate to leverage memory and computation from a single device is Ferroelectric Field-effect Transistor (FeFET). Here we present a co-integration of such FeFETs with another emerging nanotechnology concept, called Reconfigurable Field Effect Transistor (RFET) and discuss the impact of the higher amount of states provided by this combination.
