Magnetic Cellular Automata

We are interested in Low Energy Computing where computing occurs due to the coupling of the computing elements. In conventional computing, electrons flow from one points to another to process information. In Nano-computing-Resaerch-Group@EE-Univ. of South florida, we pursue a novel cellular automata computing paradigm, where state of the computing elements change and the next computing element couples to the change in the previous computing element and extreme low power dissipation is possible.

We are currently exploring computing with nano-scale soft magnets that are easy to switch, requires no power in the memory state, and can be operated at room temperature. Each magnetic cell is a single domain nano magnet in which all the spins are aligned to one direction. By shape engineering, we can have two dominant state "0" and "1" as shown here. Information processing occurs due to neighbor interactions and there is no physical movement of magnets. In this sense, requirement from Magnetic Cellular automata (MCA) is orthogonal to Magnetic RAM when inter-cell interaction are prohibited. We are however interested in interfacing such systems with MRAM, and sensors providing low energy embedded computing.

In this work, we fabricate nano magnetic structure by E-beam Lithography and observe them qualitatively using Scanning Probe Mucroscope in magnetic mode. So far, varous length of magnetic interconnects, and magnetic crosswires are fabricated.

We have also proposed a spatially moving clocking field for the ordering of the magnets. We are also interested in defect characterization, shape engineering, scaling limits on such devices.

Our recent interest is in creating multi-layer magnetic cells as MQCA elements. We are exploring various clocking and device designs and architectures that can resolve some of the criticism of device integration and low power operation of its previous generation.
We will post a Verilog A model for the cell and architecture shortly once the copyright issues are resolved.

Quantum Cellular Automata

We are interested in Low Energy Computing where computing occurs due to the coupling of the computing elements. In conventional computing, electrons flow from one points to another to process information. In Nano-computing-Resaerch-Group@EE-Univ. of South florida, we pursue a novel cellular automata computing paradigm, where state of the computing elements change and the next computing element couples to the change in the previous computing element and extreme low power dissipation is possible. In Quantum Cellular Automata, each computing cell has four Q-dot and two electrons. Electrons occupy the diagonal Q-dots to minimize the overall energy. Inter-cell barrier confines the electrons in the cell. However, electrons in the neighboring cells allign themselves accroding to the driver cell transfering information. Various cells including a shift register, inverter etc are fabricated and large designs are have been proposed using four phase clocking scheme. We are interested in modeling reliablity, defect, design and power-error trade-offs in Quantum Cellular Automata.

 

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Reliability Analysis for post-CMOS Devices

We work on probabilistic graph structures like Bayesian Networks to model statistical variability of nano-devices. Note that this problem is not new and huge literature exists on"computing with unreliable components" and bounds.

What changed though from before is the phenomenal error rates simply due to extremely low energy computing requirements that random thermal energy can cause temporary errors. We transform the circuit (shown in Figure) into a probabilistic network which in turn is transformed into a junction tree for local computing advantages.

Problems that we intend to look at are

1. Can we arrive at models driven by the underlying Physics of the devices?
2. What would be best heuristics to track worst case scenario?
3. Error/Defect at the boundaries of integration of various devices.
4. Are we heading back to analog? If so, why not use some of the strength?
5. Can we learn structures successfully in inputs and in defects?

Magnetic Cellular Automata Coplanar Cross Wire Systems

J. Pulecio and S.Bhanja,"Magnetic Cellular Automata Coplanar Cross Wire Systems", Accepted to Nano-DDS (Platform paper, oral), 2009.

Work In Progress - An Education Module on Engineering Ethics Concentrating on Environment-Friendly Engineering for Computer Engineers

K. Lingasubramanian and S. Bhanja, " Work In Progress - An Education Module on Engineering Ethics Concentrating on Environment-Friendly Engineering for Computer Engineers", Accepted for publication in IEEE Frontiers in Education (FIE), 2009

Dr. Bhanja delivers invited Talk in Intl. Workshop on QCA

Dr. Bhanja presents the NCRG's Nano-Electronics research effort in Intl. Workshop on QCA, held in Univ. of British Columbia.

Fast Estimation of Power Dissipation in QCA Circuits

S. Srivastava, S. Sarkar and S. Bhanja, “Estimation of Upper Bound of Power Dissipation in QCA Circuits”, Accepted, IEEE Transactions on Nanotechnology, vol. 8-1, pp. 116--127, 2009. @ARTICLE{4625949, title={Estimation of Upper Bound of Power Dissipation in QCA Circuits}, author={Srivastava, S. and Sarkar, S. and Bhanja, S.}, journal={Nanotechnology, IEEE Transactions on}, year={2009}, month={Jan. }, volume={8}, number={1}, pages={116-127}, abstract={Quantum-dot cellular automata (QCA) is a field-coupled computing paradigm. States of a cell change due to mutual interactions of either electrostatic or magnetic fields. Due to their small sizes, power is an important design parameter. In this paper, we derive an upper bound for power loss that will occur with input change, even with the circuit staying at respective ground states before and after the change. This bound is computationally efficient to compute for large QCA circuits since it just requires the knowledge of the before and after ground states due to input change. We categorize power loss in clocked QCA circuits into two types that are commonly used in circuit theory: switching power and leakage power. Leakage power loss is independent of input states and occurs when the clock energy is raised or lowered to depolarize or polarize a cell. Switching power is dependent on input combinations and occurs at the instant when the cell actually changes state. Total power loss is controlled by changing the rate of change of transitions in the clocking function. Our model provides an estimate of power loss in a QCA circuit for clocks with sharp transitions, which result in nonadiabatic operations and gives us the upper bound of power expended. We derive expressions for upper bounds of switching and leakage power that are easy to compute. Upper bounds obviously are pessimistic estimates, but are necessary to design robust circuits, leaving room for operational manufacturing variability. Given that thermal issues are critical to QCA designs, we show how our model can be valuable for QCA design automation in multiple ways. It can be used to quickly locate potential thermal hot spots in a QCA circuit. The model can also be used to correlate power loss with different input vector switching; power loss is dependent on the input vector. We can study the tradeoff between switching and leakage power in QCA circuits. And, we can use the model to vet different designs of the - - same logic, which we demonstrate for the full adder.}, keywords={cellular automata, ground states, integrated circuit design, quantum dotsQCA circuits, clock energy, ground states, leakage power, power dissipation, power loss, quantum-dot cellular automata, switching power, upper bound estimation}, doi={10.1109/TNANO.2008.2005408}, ISSN={1536-125X}, }

 

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