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DOE OSTI · 1569151

Resilient Computing with Dynamical Systems

Rothganger, Fredrick H.·Cardwell, Suma George
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Abstract

We reformulate fundamental numerical problems to run on novel hardware inspired by the brain. Such "neuromorphie hardware consumes less energy per computation, promising a means to augment next-generation exascale computers. However, their programming model is radically different from floating-point machines, with fewer guarantees about precision and communication. The approach is to pass each given problem through a sequence of transformations (algorithmic "reductions") which change it from conventional form into a dynamical system, then ultimately into a spiking neural network. Results for the eigenvalue problem are presented, showing that the dynamical system formulation is feasible.

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BibTeXRIS

Rothganger, Fredrick H., Cardwell, Suma George. 2019-09-01. Resilient Computing with Dynamical Systems. https://doi.org/10.2172/1569151

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