Skip to main content
Disciplines
Automotive
Business IT + Informatics
Construction + Real Estate
Electrical Engineering + Electronics
Energy + Sustainability
Insurance + Risk
Finance + Banking
Management + Leadership
Marketing + Sales
Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Start single access now
Request access for companies
EXTENDED SEARCH
Log in
Top

Hint

Swipe to navigate through the chapters of this book

Published in:
Memristor Fundamentals Read chapter Read first chapter

2016 | OriginalPaper | Chapter

6. High-Radix Arithmetic-Logic Unit (ALU) Based on Memristors

Authors : Ioannis Vourkas, Georgios Ch. Sirakoulis

Published in: Memristor-Based Nanoelectronic Computing Circuits and Architectures

Publisher: Springer International Publishing

Login to get access

Abstract

This chapter presents a novel method for implementing crossbar-based multi-level memories, where each cross-point cell stores multiple bits. Furthermore, a conceptual solution for novel CMOS-compatible, memristive, high-radix arithmetic logic units (ALUs) is proposed, for future computing systems. More specifically, a hybrid ALU circuit nano-architecture is described, where: (a) CMOS peripheral circuits are used for binary arithmetic operations; (b) a memristive reconfigurable crossbar-based memory block is used to: (i) allow parallel read/write of data; (ii) facilitate the implementation of efficient arithmetic algorithms (e.g. fast partial product creation for multiplication); and (iii) store information in a compact, high-radix form. Instead of single memristors, the crossbar nodes comprise a type of multi-state composite memristive switches, described in Chap. 3, which permit multi-bit storage in a more robust manner. Radix-4 representation is used because: (i) it balances the offered advantages with the peripheral binary conversion circuitry overhead; and (ii) it provides a good density/reliability trade-off. The fine operation and accuracy of the proposed system architecture is demonstrated through SPICE-level simulations.

To get access to this content you need the following product:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt 90 Tage mit der neuen Mini-Lizenz testen!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe



 


Jetzt 90 Tage mit der neuen Mini-Lizenz testen!

inform now
previous chapter Memristive Crossbar-Based Nonvolatile Memory
next chapter Networks of Memristors and Memristive Components
Literature
1.
R.P. Brent, P. Zimmermann, Modern Computer Arithmetic (Cambridge University Press, Cambridge, 2010) CrossRefMATH
2.
3.
S. Hamdioui, H. Aziza, G.C. Sirakoulis, “Memristor Based Memories: Technology, Design and Test, in 9th IEEE International Conference on Design & Technology of Integrated Systems in Nanoscale Era (DTIS), Santorini island, Greece (2014)
4.
Y. Pershin, M. Di Ventra, Practical approach to programmable analog circuits with memristors. IEEE Trans. Circ. Syst. I, Reg. Papers 57(8), 1857–1864 (2010) MathSciNetCrossRef
5.
E. Lehtonen, M. Laiho, Stateful implication logic with memristors, in IEEE/ACM International Symposium on. Nanoscale Architectures (NANOARCH), San Francisco, CA (2009)
6.
S. Kvatinsky, G. Satat, N. Wald, E.G. Friedman, A. Kolodny, U.C. Weiser, Memristor-based material implication (IMPLY) logic: design principles and methodologies, IEEE Trans. Very Large Scale Integr. (VLSI) Syst. 22(10), 2054–2066 (2014)
7.
S. Paul, S. Bhunia, A scalable memory-based reconfigurable computing framework for nanoscale crossbar. IEEE Trans. Nanotechnol. 11(3), 451–462 (2012) CrossRef
8.
G.S. Rose, J. Rajendran, H. Manem, R. Karri, R.E. Pino, Leveraging memristive systems in the construction of digital logic circuits. IEEE Proc. 100(6), 2033–2049 (2012) CrossRef
9.
G. Papandroulidakis, I. Vourkas, N. Vasileiadis, G.C. Sirakoulis, Boolean logic operations and computing circuits based on memristors. IEEE Trans. Circuits Syst. II Expr. Briefs 61(12), 972–976 (2014) CrossRef
10.
R. Patel, E.G. Friedman, Arithmetic encoding for memristive multi-bit storage, in 20th IEEE/IFIP International Conference on VLSI and System-on-Chip (VLSI-SoC), Santa Cruz, CA (2012)
11.
12.
13.
C.E. Merkel, N. Nagpal, S. Mandalapu, D. Kudithipudi, Reconfigurable N-level memristor memory design, in International Joint Conference on Neural Networks (IJCNN), San Jose, CA (2011)
14.
K. Hyongsuk, M.P. Sah, C. Yang, L.O. Chua, Memristor-based multilevel memory, in 12th International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), Berkeley, CA (2010)
15.
H. Manem, J. Rajendran, G.S. Rose, Design considerations for multilevel CMOS/Nano memristive memory. ACM J. Emerg. Technol. Comput. Syst. 8(16), 1–22 (2012) CrossRef
16.
A. Emara, M. Ghoneima, M. El-Dessouky, Differential 1T2M memristor memory cell for single/multi-bit RRAM modules, in 6th Computer Science and Electronic Engineering Conference (CEEC), Colchester (2014)
17.
D. Fey, Using the multi-bit feature of memristors for register files in signed-digit arithmetic units. Semicond. Sci. Technol. 29, 104008 (2014) CrossRef
18.
Y.V. Pershin, M. Di Ventra, Memory effects in complex materials and nanoscale systems. Adv. Phys. 60(2), 145–227 (2011) CrossRef
19.
E. Linn, R. Rosezin, S. Tappertzhofen, U. Bottger, R. Waser, Beyond von Neumann-logic operations in passive crossbar arrays alongside memory operations, Nanotechnology 23, 305205 (2012)
20.
M. Di Ventra, Y.V. Pershin, The parallel approach. Nat. Phys. 9, 200–202 (2013) CrossRef
21.
K.H. Kim, S. Gaba, D. Wheeler, J.M. Cruz-Albrecht, T. Hussain, N. Srinivasa, W. Lu, A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications. Nano Lett. 12(1), 389–395 (2012) CrossRef
22.
H. Kim, M.P. Sah, C. Yang, T. Roska, L.O. Chua, Neural synaptic weighting with a pulse-based memristor circuit. IEEE Trans. Circ. Syst. I Reg. Papers 59(1), 148–158 (2012) MathSciNetCrossRef
23.
C. Yakopcic, R. Hasan, T.M. Taha, M. McLean, D. Palmer, Memristor-based neuron circuit and method for applying learning algorithm in SPICE?, IET Electron. Lett. 50(7), 492–494 (2014)
24.
H. Manem, G.S. Rose, X. He, W. Wang, Design considerations for variation tolerant multilevel CMOS/nano memristor memory, in 20th Great Lakes Symposium on VLSI (GLSVLSI), Providence, Rhode Island (2010)
25.
P. Junsangsri, F. Lombardi, A memristor-based TCAM (ternary content addressable memory) cell: design and evaluation, in Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI), Salt Lake City, Utah, USA (2012)
26.
I. Vourkas, G.C. Sirakoulis, On the analog computational characteristics of memristive networks, in 20th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Abu Dhabi (2013)
27.
I. Vourkas, G.C. Sirakoulis, On the generalization of composite memristive network structures for computational analog/digital circuits and systems. Microelectron. J. 45(11), 1380–1391 (2014) CrossRef
28.
I. Vourkas, A. Batsos, G.C. Sirakoulis, SPICE modeling of nonlinear memristive behavior, Int. J. Circ. Theor. Appl. 43(5), 553–565(2015)
29.
Y. Yilmaz, P. Mazumder, Threshold read method for multi-bit memristive crossbar memory, in Int. Symposium on Electronic System Design (ISED), Kochi, Kerala (2011)
30.
K. Cho, S.J. Lee, K. Eshraghian, Memristor-CMOS logic and digital computational components. Microelectron. J. 46(3), 214–220 (2015) CrossRef
31.
A.A. El-Slehdar, A.H. Fouad, A.G. Radwan, Memristor-based redundant binary adder, in International Conference on Engineering and Technology (ICET), Cairo (2014)
32.
A.A. El-Slehdar, A.H. Fouad, A.G. Radwan, Memristor-based balanced ternary adder, in 25th International Conference on Microelectronics (ICM), Beirut (2013)
33.
A.A. El-Slehdar, A.H. Fouad, A.G. Radwan, Memristor based N-bits redundant binary adder. Microelectron. J. 46(3), 207–213 (2015) CrossRef
34.
M. Laiho, E. Lehtonen, Arithmetic operations within memristor-based analog memory, in 12th International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), Berkeley, CA (2010)
35.
K. Bickerstaff, E.E. Swartzlander, Memristor-based arithmetic, in 44th Asilomar Conference on Signals, Systems and Computers (ASILOMAR), Pacific Grove, CA (2010)
36.
F. Merrikh-Bayat, S. Bagheri Shouraki, Memristor-based circuits for performing basic arithmetic operations, in Procedia Computer Science—Proceedings of 2010 World Conference on Information Technology (WCIT), vol. 3 (2011), pp. 128–132
37.
A.H. Shaltoot, A.H. Madian, Memristor based carry lookahead adder architectures, in 55th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Boise, ID (2012)
38.
Y. Yang, J. Mathew, D.K. Pradhan, M. Ottavi, S. Pontarelli, Complementary resistive switch based stateful logic operations using material implication, in Design, Automation and Test in Europe Conference and Exhibition (DATE), Dresden (2014)
39.
S.J. Lee, B.S. Park, S.W. Cho, K. Cho, K. Eshraghian, Memristor-CMOS reconfigurable multiplier architecture, in 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA), Notre Dame, IN (2014)
Metadata
Title
High-Radix Arithmetic-Logic Unit (ALU) Based on Memristors
Authors
Ioannis Vourkas
Georgios Ch. Sirakoulis
Copyright Year
2016
Book
Memristor-Based Nanoelectronic Computing Circuits and Architectures

Print ISBN: 978-3-319-22646-0

Electronic ISBN: 978-3-319-22647-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-22647-7_6

Premium Partners

in-adhesives MKVS Ecoclean Hellmich GmbH Krahn Ceramics
    Image Credits