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A model for computing and energy dissipation of molecular QCA devices and circuits
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ACM Journal on Emerging Technologies in Computing Systems (JETC) archive
Volume 3 ,  Issue 4  (January 2008) table of contents
Article No. 3  
Year of Publication: 2008
ISSN:1550-4832
Authors
Xiaojun Ma  Northeastern University, Boston
Jing Huang  Northeastern University, Boston
Fabrizio Lombardi  Northeastern University, Boston
Publisher
ACM  New York, NY, USA
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ABSTRACT

Quantum-dot Cellular Automata is an emerging technology that offers significant improvements over CMOS. Recently QCA has been advocated as a technology for implementing reversible computing. However, existing tools for QCA design and evaluation have limited capabilities. This paper presents a new mechanical-based model for computing in QCA. By avoiding a full quantum-thermodynamical calculation, it offers a classical view of the principles of QCA operation and can be used in evaluating energy dissipation for reversible computing. The proposed model is mechanically based and is applicable to six-dot (neutrally charged) QCA cells for molecular implementation. The mechanical model consists of a sleeve of changing shape; four electrically charged balls are connected by a stick that rotates around an axle in the sleeve. The sleeve acts as a clocking unit, while the angular position of the stick within the changing shape of the sleeve, identifies the phase for quasi-adiabatic switching. A thermodynamic analysis of the proposed model is presented. The behaviors of various QCA basic devices and circuits are analyzed using the proposed model. It is shown that the proposed model is capable of evaluating the energy consumption for reversible computing at device and circuit levels for molecular QCA implementation. As applicable to QCA, two clocking schemes are also analyzed for energy dissipation and performance (in terms of number of clocking zones).


REFERENCES

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1
Amlani, I., Orlov, A. O., Toth, G., Lent, C. S., Bernstein, G. H., and Snider, G. L. 1999. Digital logic gate using quantum-dot cellular automat. Science 284 (5412), 289--291.
2
 
3
Bennett, C. H. 1973. Logic reversibility of computation. IBM J. Res. Dev. 17, 525--532.
 
4
Bennett, C. H. 2000. Notes on the history of reversible computation. IBM J. Res. Dev. 44, 44, 525--532.
 
5
Compano, R., Molenkamp, L., and Paul, D. J. 2003. Technology roadmap for nanoelectronics. European Commission IST Programme, Future and Emerging Technologies. www.itrs.net/Links/2003ITRS/LinkedFiles/ERD/NanoeletronicsRdmp.pdf
 
6
Dimitrov, V. S., Jullien, G. A., and Walus, K. 2002. Quantum-dot cellular automata carry-look-ahead adder and barrel shifter. In Proceedings of the IEEE Emerging Telecommunications Technologies Conference. 2/1--2/4.
 
7
Fermi, E. 1956. Thermodynamics. Dover Publications Inc., New York, NY.
 
8
Fredkin, E. and Toffoli, T. 1982. Conservative logic. Int. J.Theor. Phys. 21, 219--253.
 
9
Frost, S. E., Rodrigues, A. F., Janiszewski, A. W., Rausch, R. T. and Kogge, P. M. 2002. Memory in motion: A study of storage structures in QCA. In Proceedings of the Workshop on Non-Silicon Computation.
 
10
Hu, W., Sarveswaran, K., Lieberman, M., and Bernstein, G. H. 2005. High-resolution electron beam lithography and DNA nano-patterning for molecular QCA. IEEE Trans. Nanotech. 4, 3, 312--316.
 
11
Huang, J., Ma, X., and Lombardi, F. 2006. Energy analysis of QCA circuits for reversible computing. In Proceedings of the 6th IEEE Conference on Nanotechnology (NANO) 1, 39--42.
 
12
Huang, J., Momenzadeh, M. Schiano, L., and Lombardi, F. 2005. Simulation-based design of modular QCA circuits. In Proceedings of the 5th IEEE Conference on Nanotechnology 2, 533--536.
13
 
14
Huang, J., Momenzadeh, M., Tahoori, M., and Lombardi. F. 2005. On the evaluation of scaling of QCA devices in the presence of defects. IEEE Trans. Nanotech 4, 6, 740--743.
 
15
Landauer, R. 1961. Irreversibility and heat generation in the computing process. IBM J. Res. Dev. 5, 183--191.
 
16
Lent, C. S., Liu, M., and Lu, Y. 2006. Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling. Nanotech. 17, 16, 4240--4251.
 
17
Lent, C. S. and Tougaw, P. D. 1997. A device architecture for computing with quantum dots. In Proceedings of the IEEE 85, 4, 541--557.
 
18
Lent, C. S., Tougaw, P. D., and Porod, W. 1994. Quantum cellular automata: the physics of computing with arrays of quantum dot molecules. In Proceedings of the Workshop on Physics and Computing, 5--13.
 
19
 
20
Niemier, M. T. and Kogge, P. M. 1999. Logic-in-wire: using quantum dots to implement a microprocessor. In Proceedings of the International Conference on Electronics, Circuits, and Systems (ICECS) 3, 1211--1215.
 
21
Niemier, M. T. and Kogge, P. M. 2001. Problems in designing with QCAs: layout=timing. Int. J. Circ. Theory Appl. 29, 1, 49--62.
22
 
23
Niemier, M. T., Rodrigues, A. F., and Kogge, P. M. 2002. A potentially implementable FPGA for quantum dot cellular automata. In Proceedings of the 1st Workshop on Non-Silicon Computation (NSC-1). Held in Conjunction with the 8th International Symposium on High Performance Computer Architecture (HPCA).
 
24
 
25
Smith, C. G. 1999. Computation without current. Science 284, 2, 274.
 
26
Tahoori, M., Momenzadeh, M., Huang, J., and Lombardi, F. 2004. Testing of quantum cellular automata. IEEE Trans. Nanotechn. 3, 4, 432--442.
 
27
Tang, R., Zhang, F., and Kim, Y. B. 2005. QCA-based nano circuits design. In Proceedings of the IEEE International Symposium on Circuits and Systems. Kobe, Japan, 2527--2530.
28
 
29
Timler, J. and Lent, C. S. 2003. Maxwell's demon and quantum-dot cellular automata. J. Appl. Phys. 94, 2 1050--1060.
 
30
Toffoli, T. 1980. Reversible computing. Tech. Rep. MITLCSTM151, MIT Laboratory for Computer Science.
 
31
Toth, G. 2000. Correlation and coherence in quantum-dot cellular automata. Ph.D. Thesis, University of Notre Dame.
 
32
Tougaw, P. D. and Lent, C. S. 1994. Logical devices implemented using quantum cellular automata. J. Appl. Phys. 75, 3, 1818--1825.
 
33
Tougaw, P. D. and Lent, C. S. 1996. Dynamic behavior of quantum cellular automata. J. Appl. Phys. 80, 15, 4722--4736.
 
34
Walus, K., Budiman, R. A., and Jullien, G. A. 2002. Effects of morphological variations of self-assembled nanostructures on quantum-dot cellular automata (QCA) circuits. Frontiers of Integration, An International Workshop on Integrating Nanotechnologies.
 
35
Walus, K., Dysart, T., Jullien, G. A., and Budiman, R. A. 2003. QCADesigner: A rapid design and simulation tool for quantum-dot cellular automata. In Proceedings of the 2nd International Workshop on Quantum Dots for Quantum Computing and Classical Size Effect Circuits. Notre Dame, IN.
 
36
Walus, K., Dysart, T., Jullien, G. A., and Budiman, R. A. 2004. QCADesigner: A rapid design and simulation tool for quantum-dot cellular automata. IEEE Trans. Nanotech. 3, 26--29.
 
37
Walus, K., Vetteth, A., Jullien, G. A. and Dimitrov, V. S. 2003. RAM design using quantum-dot cellular automata. In Proceedings of the Nanotechnology Conference. 2, 160--163.


Collaborative Colleagues:
Xiaojun Ma: colleagues
Jing Huang: colleagues
Fabrizio Lombardi: colleagues