<p>Probabilistic
computing has been proposed as an attractive alternative for bridging the computational
gap between the classical computers of today and the quantum computers of
tomorrow. It offers to accelerate the solution to many combinatorial
optimization and machine learning problems of interest today, motivating the
development of dedicated hardware. Similar to the ‘bit’ of classical computing
or ‘q-bit’ of quantum computing, probabilistic bit or ‘p-bit’ serve as a
fundamental building-block for probabilistic hardware. p-bits are robust
classical quantities, fluctuating rapidly between its two states, envisioned as
three-terminal devices with a stochastic output controlled by its input. It is
possible to implement fast and efficient hardware p-bits by modifying the
present day magnetic random access memory (MRAM) technology. In this
dissertation, we evaluate the design and performance of low-barrier magnet
(LBM) based p-bit realizations.<br> </p>
<p>LBMs
can be realized from perpendicular magnets designed to be close to the in-plane
transition or from circular in-plane magnets. Magnetic tunnel junctions (MTJs) built
using these LBMs as free layers can be integrated with standard transistors to
implement the three-terminal p-bit units. A crucial parameter that determines
the response of these devices is the correlation-time of magnetization. We show
that for magnets with low energy barriers (Δ ≤ k<sub>B</sub>T) the circular
disk magnets with in-plane magnetic anisotropy (IMA) can lead to
correlation-times in <i>sub-ns</i> timescales; two orders of magnitude smaller
compared to magnets having perpendicular magnetic anisotropy (PMA). We show
that this striking difference is due to a novel precession-like fluctuation mechanism
that is enabled by the large demagnetization field in mono-domain circular disk
magnets. Our predictions on fast fluctuations in LBM magnets have recently
received experimental confirmation as well.<br></p>
<p>We
provide a detailed energy-delay performance evaluation of the stochastic MTJ
(s-MTJ) based p-bit hardware. We analyze the hardware using benchmarked SPICE
multi-physics modules and classify the necessary and sufficient conditions for
designing them. We connect our device performance analysis to systems-level
metrics by emphasizing problem and substrate independent figures-of-merit such
as flips per second and dissipated energy per flip that can be used to classify
probabilistic hardware. </p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/13402097 |
| Date | 17 December 2020 |
| Creators | Orchi Hassan (9862484) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/Evaluation_of_Stochastic_Magnetic_Tunnel_Junctions_as_Building_Blocks_for_Probabilistic_Computing/13402097 |
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