Coupled Spin Torque Nano-Oscillators for efficient non-Boolean computation
Non-Boolean computation for applications such as edge detection, pattern matching, content addressable memory etc. using non-silicon devices have gained an enormous interest in the recent past because of the possibility of achieving ultra-low energy consumption. Hardware implementation for these applications using CMOS (Complementary Metal Oxide Semiconductor) devices in standard von-Neumann architecture is known to be energy inefficient. To address the aforementioned issue, a new computation method based on a network of coupled Spin Torque Nano Oscillators (STNOs) is investigated. Recent experiments on STNOs have demonstrated their frequency of oscillation in few tens of gigahertz (GHz) range, operating at low input currents. These attractive features and the ability to obtain frequency locking using a variety of techniques, make STNOs an attractive candidate for non-Boolean computing. In this work, the “unconventional computing” ability of coupled STNOs is demonstrated through example cases like edge detection of an image, magnetic pattern recognition and neuromorphic computing. A detailed scaling and variation analysis of STNOs is also provided to identify the most effective locking mechanism in coupled STNOs. Finally, a magnetic field free 3 terminal (3T) STNO based on Spin Hall effect (Spin Hall Nano Oscillator-SHNO) is proposed, which helps overcome the disadvantages of conventional 2T STNOs. Design challenges associated with SHNOs is also discussed in detail with possible solutions to address these challenges.
Roy, Purdue University.
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