Michael Crocker

Design and comparison of NML systolic architectures

Nanomagnet Logic (NML) is a device architecture that utilizes the magnetization of nano-scale magnets to perform logical operations. NML has been experimentally demonstrated and operates at room temperature. Because the nanomagnets are non-volatile, as data flows through a circuit, it is inherently pipelined. This feature makes NML an excellent fit for systolic architectures, which could enable low-power, high-throughput systems that can address a variety of application-level tasks. When considering possible NML systolic systems, the underlying systolic clocking scheme affects both architectural design and performance. In this paper we explore these issues in the context of two NML designs for convolution. One design is based on a 3-phase clocking scheme and uni-directional dataflow, and another is based on a 2-phase clocking scheme and bi-directional dataflow. We compare the two NML systolic designs in terms of area, delay, and energy. We also compare the NML and CMOS implementations of the design in terms of energy and delay. Results are supported by physical level simulation.

Molecular QCA design with chemically reasonable constraints

In this article we examine the impacts of the fundamental constraints required for circuits and systems made from molecular Quantum-dot Cellular Automata (QCA) devices. Our design constraints are “chemically reasonable” in that we consider the characteristics and dimensions of devices and scaffoldings that have actually been fabricated. This work is a necessary first step for any work in QCA CAD, and can also help shape experiments in the physical sciences for emerging, nano-scale devices. Our work shows that QCA circuits, scaffoldings, substrates, and devices should all be considered simultaneously. Otherwise, there is a very real possibility that the devices and scaffoldings that are eventually manufactured will result in devices that only work in isolation. “Chemically reasonable” also means that expected manufacturing defects must be considered. In our simulations we introduce defects associated with self-assembled systems into various designs to begin to define manufacturing tolerances. This work is especially timely as experimentalists are beginning to work on merging experimental tracks that address devices and scaffolds—and the end result should facilitate correct logical operations.

Fabrication Variations and Defect Tolerance for Nanomagnet-Based QCA

Tolerating defects and fabrication variations will be critical in any system made with devices that have nanometer feature sizes. This paper considers how fabrication variations and defects might lead to faulty behavior in Magnetic Quantum-dot Cellular Automata (MQCA) circuits and systems. Here, we leverage physical-level simulation to consider how fabrication variations might affect a circuits logical correctness. We then discuss how we can tolerate fabrication variations at the device, circuit, and architectural level.

PLAs in quantum-dot cellular automata

Research in the fields of physics, chemistry and electronics has demonstrated that quantum-dot cellular automata (QCA) is a viable alternative for nano-scale computing. However, little work on QCA has studied designing implementation-friendly programmable QCA circuits. This paper fills this gap by presenting a novel QCA-based programmable logic array (PLA) structure. In addition to being compact, the proposed PLA structure exploits some unique properties of QCA cells to achieve ease of implementation, programming and defect detection. These features are indispensable to the successful adoption of any nano-scale circuits

Fault Models and Yield Analysis for QCA-Based PLAs

Various implementations of the quantum-dot cellular automata (QCA) device architecture may help many performance scaling trends continue as we approach the nano-scale. Experimental success has led to the evolution of a research track that looks at QCA-based design. The work presented in this paper follows that track and looks at implementation friendly, programmable QCA circuits. Specifically, we analyze a novel, QCA-based, programmable logic array (PLA) structure, develop an implementation independent fault model, discuss how expected defects and faults might affect yield, and look at the design in the context of a magnetic implementation of QCA.

Defects and faults in QCA-based PLAs

Defect tolerance will be critical in any system with nanoscale feature sizes. This article examines some fundamental aspects of defect tolerance for a reconfigurable system based on Quantum-dot Cellular Automata (QCA). We analyze a novel, QCA-based, Programmable Logic Array (PLA) structure, develop an implementation independent fault model, and discuss how expected defects and faults might affect yield. Within this context, we introduce techniques for mapping Boolean logic functions to a defective QCA-based PLA. Simulation results show that our new mapping techniques can achieve higher yields than existing techniques.

Defect tolerance in QCA-based PLAs

Defect tolerance will be critical in any system with nano-scale feature sizes. This paper examines some fundamental aspects of defect tolerance for a reconfigurable system based on magnetic quantum-dot cellular automata (MQCA). MQCA performs logical operations and moves data by manipulating the polarizations of nano-scale magnets, has been experimentally demonstrated, and operates at room temperature. We consider how specific defects will impact device functionality. Within this context, we introduce techniques for mapping Boolean logic functions to a defective system architecture (a reconfigurable programmable logic array design for MQCA). Simulation results show that our new mapping techniques can achieve much higher yields than existing techniques for nanowire crossbar PLAs.

A Reconfigurable PLA Architecture for Nanomagnet Logic

In order to continue the performance and scaling trends that we have come to expect from Moore’s Law, many emergent computational models, devices, and technologies are actively being studied to either replace or augment CMOS technology. Nanomagnet Logic (NML) is one such alternative. NML operates at room temperature, it has the potential for low power consumption, and it is CMOS compatible. In this aricle, we present an NML programmable logic array (PLA) based on a previously proposed reprogrammable quantum-dot cellular automata PLA design. We also discuss the fabrication and simulation validation of the circuit structures unique to the NML PLA, present area, energy, and delay estimates for the NML PLA, compare the area of NML PLAs to other reprogrammable nanotechnologies, and analyze how architectural-level redundancy will affect performance and defect tolerance in NML PLAs. We will use results from this study to shape a concluding discussion about, which architectures appear to be most suitable for NML.

MDSIMAID: Automatic parameter optimization in fast electrostatic algorithms

MDSIMAID is a recommender system that optimizes parallel Particle Mesh Ewald (PME) and both sequential and parallel multigrid (MG) summation fast electrostatic solvers. MDSIMAID optimizes the running time or parallel scalability of these methods within a given error tolerance. MDSIMAID performs a run time constrained search on the parameter space of each method starting from semiempirical performance models. Recommended parameters are presented to the user. MDSIMAIDs optimization of MG leads to configurations that are up to 14 times faster or 17 times more accurate than published recommendations. Optimization of PME can improve its parallel scalability, making it run twice as fast in parallel in our tests. MDSIMAID and its Python source code are accessible through a Web portal located at http://mdsimaid.cse.nd.edu.