Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …

Graphics processing units (GPUs) are used today in a wide range of applications, mainly
because they can dramatically accelerate parallel computing, are affordable and energy …

The rapid increase in the performance of graphics hardware, coupled with recent
improvements in its programmability, have made graphics hardware a compelling platform …

In this paper, we present Brook for GPUs, a system for general-purpose computation on
programmable graphics hardware. Brook extends C to include simple data-parallel …

Utilizing graphics hardware for general purpose numerical computations has become a
topic of considerable interest. The implementation of streaming algorithms, typified by highly …

We present novel algorithms for computing discrete Fourier transforms with high
performance on GPUs. We present hierarchical, mixed radix FFT algorithms for both power …

We present a system for real-time animation and rendering of large particle sets using GPU
computation and memory objects in OpenGL. Memory objects can be used both as …

We present Mint, a programming model that enables the non-expert to enjoy the
performance benefits of hand coded CUDA without becoming entangled in the details. Mint …

We develop a flat, analytic, and nonlinear placement algorithm, ePlace, which is more
effective, generalized, simpler, and faster than previous works. Based on the analogy …

Abstract SHapley Additive exPlanation (SHAP) values (Lundberg & Lee, 2017) provide a
game theoretic interpretation of the predictions of machine learning models based on …