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Heterogeneous computers with processors and accelerators are becoming widespread in scientific computing. However, it is difficult to program hybrid architectures and there is no commonly accepted programming model. Ideally, applications should be written in a way that is portable to many platforms, but providing this portability for general programs is a(More)
We demonstrate an adjoint based approach for accelerating Monte Carlo estimation of risk, and apply it to estimating the probability of unstart in a SCRamjet engine under uncertain conditions that are characterized by various Gaussian and non-Gaussian distributions. The adjoint equation is solved with respect to an objective function that is used to(More)
Adjoint methods are widely used in various areas of computational science to efficiently obtain sensitivities of functionals which result from the solution of partial differential equations (PDEs). In addition, adjoint methods have been used in other settings including error estimation, uncertainty quantification, and inverse problem formulations. When(More)
Standard Gaussian Process (GP) regression, a powerful machine learning tool, is computationally expensive when it is applied to large datasets, and potentially inaccurate when data points are sparsely distributed in a high-dimensional feature space. To address these challenges, a new multiscale, spar-sified GP algorithm is formulated, with the goal of(More)
A modeling paradigm is developed to augment predictive models of turbulence by effectively utilizing limited data generated from physical experiments. The key components of our approach involve inverse modeling to infer the spatial distribution of model discrepancies, and, machine learning to reconstruct discrepancy information from a large number of(More)
In computational fluid dynamics, the solution of the dual (or adjoint) equations in conjunction with the primal (or flow equations) offers valuable information that can be used in design, sensitivity analysis, error estimation, mesh adaptation, uncertainty quantification, etc. From the view point of implementation and application of the ad-joint technique,(More)
In the recent past, adjoint methods have been successfully applied in error estimation of integral outputs (functionals) of the numerical solution of partial differential equations. The adjoint solution can also be used as a grid adaptation indicator, with the objective of optimally targeting and reducing the numerical error in the functional of interest(More)
The dream of a bionic replacement appendage is becoming reality through the use of mechatronic prostheses that utilize the body's myoelectric signals. This paper presents a process to accurately capture the motion of the human hand joints; the obtained information is to be used in conjunction with myoelectric signal identification for motion control. In(More)
A novel 4-quadrant analog multiplier using Floating Gate MOS (FGMOS) transistors operating in saturation region are implemented. Floating gate MOSFETs are being utilized in a number of new and existing analog applications. These devices are not only useful for designing memory elements but also we can implement circuit elements. The main advantage in FGMOS(More)