Domain-driven models yield better predictions at lower cost than reservoir computers in Lorenz systems.

Recent advances in computing algorithms and hardware have rekindled interest in developing high-accuracy, low-cost models for simulating physical systems. The idea is to replace expensive numerical integration of complex coupled partial differential equations at fine time scales performed on supercomputers, with machine-learned surrogates that efficiently and accurately forecast future system states using data sampled from the underlying system. One particularly popular technique being explored within the weather and climate modelling community is the (ESN), an attractive alternative to other well-known deep learning architectures.

On the use of inexact, pruned hardware in atmospheric modelling.

Inexact hardware design, which advocates trading the accuracy of computations in exchange for significant savings in area, power and/or performance of computing hardware, has received increasing prominence in several error-tolerant application domains, particularly those involving perceptual or statistical end-users. In this paper, we evaluate inexact hardware for its applicability in weather and climate modelling. We expand previous studies on inexact techniques, in particular probabilistic pruning, to floating point arithmetic units and derive several simulated set-ups of pruned hardware with reasonable levels of error for applications in atmospheric modelling.

Inexactness and a future of computing.

As pressures, notably from energy consumption, start impeding the growth and scale of computing systems, inevitably, designers and users are increasingly considering the prospect of trading accuracy or exactness. This paper is a perspective on the progress in embracing this somewhat unusual philosophy of innovating computing systems that are designed to be inexact or approximate, in the interests of realizing extreme efficiencies. With our own experience in designing inexact physical systems including hardware as a backdrop, we speculate on the rich potential for considering inexactness as a broad emerging theme if not an entire domain for investigation for exciting research and innovation.

High-performance and low-power rewritable SiOx 1 kbit one diode-one resistor crossbar memory array.

An entire 1-kilobit crossbar device based upon SiOx resistive memories with integrated diodes has been made. The SiOx -based one diode-one resistor device system has promise to satisfy the prerequisite conditions for next generation non-volatile memory applications.