System Simulation of Memristor Based Computation in Memory Platforms

Ali BanaGozar, Kanishkan Vadivel, Joonas Multanen, Pekka Jääskeläinen, Sander Stuijk, Henk Corporaal

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)


Processors based on the von Neumann architecture show inefficient performance on many emerging data-intensive workloads. Computation in-memory (CIM) tries to address this challenge by performing the computation on the data location. To realize CIM, memristors, that are deployed in a crossbar structure, are a promising candidate. Even though extensive research has been carried out on memristors at device/circuit-level, the implications of their integration as accelerators (CIM units) in a full-blown system are not studied extensively. To study that, we developed a simulator for memristor crossbar and its analog peripheries. This paper evaluates a complete system consisting of a Transport Triggered Architecture (TTA) based host core integrating one or more CIM units. This evaluation is based on a cycle-accurate simulation. For this purpose we designed a simulator which a) includes the memristor crossbar operations as well as its surrounding analog drivers, b) provides the required interface to the co-processing digital elements, and c) presents a micro-instruction set architecture (micro-ISA) that controls and operates both analog and digital components. It is used to assess the effectiveness of the CIM unit in terms of performance, energy, and area in a full-blown system. It is shown, for example, that the EDAP for the deep learning application, LeNet, is reduced by 84% in a full-blown system deploying memristor based crossbars.

Original languageEnglish
Title of host publicationEmbedded Computer Systems
Subtitle of host publicationArchitectures, Modeling, and Simulation - 20th International Conference, SAMOS 2020, Proceedings
EditorsAlex Orailoglu, Matthias Jung, Marc Reichenbach
Number of pages17
ISBN (Electronic)978-3-030-60939-9
ISBN (Print)978-3-030-60938-2
Publication statusPublished - 2020
Event20th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2020 - Samos, Greece
Duration: 5 Jul 20209 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12471 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference20th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2020


  • Computation in memory
  • Memristor
  • Non-von neumann architectures
  • Simulator
  • Transport Triggered Architecture


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