Early Design Space Exploration Framework for Memristive Crossbar Arrays

For memristive crossbar arrays, currently, no high-level design validation and early space exploration tools exist in the literature. Such tools are essential to quickly verify the design functionality as well as compare design alternatives in terms of power and performance. In this work, we propose...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:ACM journal on emerging technologies in computing systems 2022-04, Vol.18 (2), p.1-26
Hauptverfasser: Zaman, Md Adnan, Joshi, Rajeev, Katkoori, Srinivas
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:For memristive crossbar arrays, currently, no high-level design validation and early space exploration tools exist in the literature. Such tools are essential to quickly verify the design functionality as well as compare design alternatives in terms of power and performance. In this work, we propose a VHDL-based framework that enables us to quickly perform behavioral simulation as well as estimate dynamic energy consumption and speed of any large memristive crossbar array. We propose a high-level (VHDL) model of a memristor based on which crossbar architectures can be modeled. The individual memristor model is embedded with power and delay numbers obtained from a detailed memristor model. We demonstrate the framework for MAGIC-style memristive crossbars. We validate the framework against detailed Verilog-A based model on fifteen combinational benchmarks. For the single row model, we obtained 153x simulation speedup over HSPICE, average estimation errors of 6.64% and 0% for dynamic energy consumption and cycle-time, respectively. For the transpose model, we obtained average estimation errors of 5.51% and 10.90% for dynamic energy consumption and cycle-time, respectively. We also extend our framework to support another prominent logic style and validate through a case study. The proposed framework can be easily extended to other emerging technologies.
ISSN:1550-4832
1550-4840
DOI:10.1145/3461644