Researchers from UC Berkeley and Lawrence Berkeley National Laboratory credit ArrayFire in a paper published in the 2020 IEEE High-Performance Extreme Computing Conference (HPEC). The paper is titled “GPU Accelerated Anomaly Detection of Large Scale Light Curves.” In this work, the authors present a new algorithm for reconstructing the three-dimensional (3D) electrostatic potential of a sample at atomic resolution from phase contrast imaging using high-resolution transmission electron microscopy. Summary Transmission electron microscopy (TEM) offers various imaging modes, allowing for quantitative 3D estimations of local structure, electrostatic and magnetic potentials, and local chemistry, significantly impacting biology and materials science. It is now possible to measure the 3D position of individual atoms with high precision and even determine both the 3D position and species …

Researchers from Tsinghua University, the Chinese Academy of Sciences, and David Bader of the New Jersey Institute of Technology credit ArrayFire in a paper published in the 2020 IEEE High-Performance Extreme Computing Conference (HPEC). The paper is titled “GPU Accelerated Anomaly Detection of Large Scale Light Curves.” In this research, light from 200,000 stars is tracked, looking for events of high-mass dark objects that bend light from the source, indicating the discovery of planets and black holes. Summary Microlensing is a unique anomaly that occurs when a lens (or lenses) passes between a light source (star) and an observer (Earth). These lenses are high-mass objects that bend the light from the source. This anomaly is helpful in the detection of “dark” objects. …

Researchers from the University Bordeaux credit ArrayFire in a paper published in a Master’s Thesis by André Almeida. The thesis is titled “Soliton Excitations in Open Systems using GPGPU Supercomputing.” It investigates the stability of nonlinear excitations in open optical systems modeled by the Complex Ginzburg Landau Equation when influenced by effects such as dissipation and gain, using numerical simulations. Summary In the early years of the 19th century the naval engineer James Scott Russell made the first observation of a very uniform accumulation of water in a boat canal that was capable to propagate for many kilometers without any losses in amplitude and with constant width. This was a very strange phenomenon at the time because no known description of hydrodynamics …

Researchers from the University Bordeaux in France credit ArrayFire in a paper published in ICPR 2020’s workshop on Explainable Deep Learning for AI. The paper is titled “Samples Classification Analysis Across DNN Layers with Fractal Curves.” It provides a tool for visualizing where the deep neural network starts to be able to discriminate the classes. Summary Deep neural networks (DNN) are becoming the prominent solution when using machine learning models. However, they suffer from a black-box effect that complicates their inner workings interpretation and thus the understanding of their successes and failures. Information visualization is one way, among others, to help in their interpretability and hypothesis deduction. This paper presents a novel way to visualize atrained DNN to depict at the same …