PVT Analysis for RRAM and STT-MRAM-based Logic Computation-in-Memory

Abstract

Emerging non-volatile resistive memories like Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) and Resistive RAM (RRAM) are in the focus of today's research. They offer promising alternative computing architectures such as computation-in-memory (CiM) to reduce the transfer overhead between CPU and memory, usually referred to as the memory wall, which is present in all von Neumann architectures. A multitude of architectures with CiM capabilities are based on these devices, due to their inherent resistive behavior and thus their ability to perform calculation directly within the memory, and thus without invoking the CPU at all. However, emerging memories are sensitive to Process, Voltage and Temperature (PVT) variations. This sensitivity has an even larger impact on CiM architectures. In this paper, we analyze and compare the impact of PVT variations on STT-MRAM and RRAM-based CiM architectures. We perform a sensitivity analysis to identify which parts of the CiM structure are most susceptible to PVT variations, for each technology. Based on these analyses, we recommend that STT-MRAM is used in highperformance CiM, while RRAM is used for edge CiM.

Open Automation Framework for Complex Parametric Electrical Simulations

“…This allows the user to have all the information about the executed operation in the same CSV and it supports directly performing data analysis from the collected data to assess the correct behaviour of the studied operations. Another example where this framework could have facilitated the parametric simulations and the data analysis is in the work described in [11], which presents an in-depth analysis of the process, voltage and temperature variability for CIM.…”