University of Central Florida Research Foundation Inc

The University of Texas System

Alvaro Velasquez

Sumit Kumar Jha

Joseph S Friedman

Joseph E Van Nostrand

Naimul Hassan

Xuan Hu

Dilia E Rodriguez

Wesley H Brigner

The present disclosure provides a domain wall magnetic tunnel junction device. Integration of input spikes pushes a domain wall within a ferromagnetic track toward a magnetic tunnel junction (MTJ). An energy gradient within the track pushes the domain wall away from the MTJ by leaking accumulated energy from the input spikes. If the integrated input spikes exceed the energy leak of the gradient within a specified time period, the domain wall reaches the MTJ and reverses its resistance, producing an output spike. The leaking energy gradient can be created by a magnetic field, a trapezoidal shape of the ferromagnetic track, or nonuniform material properties in the ferromagnetic track. A feedback and feedforward crossbar configuration is disclosed that provides for a neuromorphic computing system suitable for unsupervised learning.

Spintronic computing architecture and method

An in-memory computing architecture is disclosed that can evaluate the transitive closure of graphs using the natural parallel flow of information in 3-D nanoscale crossbars. The architecture can be implemented using 3-D crossbar architectures with as few as two layers of 1-diode 1-resistor (1D1R) interconnects. The architecture avoids memory-processor bottlenecks and can hence scale to large graphs. The approach leads to a runtime complexity of O(n) using O(n) memristor devices. This compares favorably to conventional algorithms with a time complexity of O((n)/p+(n) log p) on p processors. The approach takes advantage of the dynamics of 3-D crossbars not available on 2-D crossbars.

3-D crossbar architecture for fast energy-efficient in-memory computing of graph transitive closure

Memristor-based nano-crossbar computing is a revolutionary computing paradigm that does away with the traditional Von Neumann architectural separation of memory and computation units. The computation of Boolean formulas using memristor circuits has been a subject of several recent investigations. Crossbar computing, in general, has also been a topic of active interest, but sneak paths have posed a hurdle in the design of pervasive general-purpose crossbar computing paradigms. Various embodiments are disclosed which demonstrate that sneak paths in nano-crossbar computing can be exploited to design a Boolean-formula evaluation strategy. Such nano-crossbar designs are also an effective approach for synthesizing high performance customized arithmetic and logic circuits.

Computation of boolean formulas using sneak paths in crossbar computing

Growing community of inventors

West Palm Beach, FL, United States of America

Alvaro Velasquez