Light from the Dark: How Supercomputer Simulations of Binary Black Holes and Neutron Stars Can Reveal the Hidden Universe — Manuela Campanelli

The recent discoveries of gravitational waves from several binary black hole mergers, including the 2017 Nobel Prize-winning discovery, and a neutron star merger by the advanced LIGO and Virgo detectors are giving us the first glimpses of the hidden side of the universe. The first images of a supermassive black hole at the core of a galaxy have further demonstrated our incredible ability to capture the dimmest light from the invisible. In the next decade, the detection of low frequency gravitational waves by the Pulsar timing arrays and Laser Interferometer Space Antenna projects will unveil the mystery of merging supermassive black holes at the center of galaxies.

Docker containers + supercomputers = ?? — Justin Flory

How do you deliver research software into research computing environments? Or supercomputers? Docker containers and related products are revolutionizing IT infrastructure, but where do containers belong in supercomputing / High-Performance Computing (HPC) infrastructure, on large distributed computing grids? In a world of proprietary hardware and drivers, large-scale distributed systems, and emphasis on bare-metal performance, are containers another virtualization fad to skip over supercomputing? Guess again.

Distributed Capsule Neural Networks – Applied Computer Vision Research — Perry Deng

In this session, the presenter will briefly describe the use of distributed and parallel GPU computing in his research experiments. He will also talk about the researched topic, a new type of neural network inspired by data structures used in computer vision, and Expectation-Maximization statistical algorithm.

Intro to Neural Networks with Applications to Function Approximation — Marko Ristic

Within the past decade, deep learning has become widely utilized in both academic and industry settings. At the heart of deep learning lie neural networks which combine linear algebra and statistics to mimic the learning process which our brains undergo on a daily basis. The beginning of the talk will focus on an elementary introduction to neural networks and their functionalities. The latter portion of the talk will discuss how neural networks can be used for function approximation in the context of parameter estimation.

Programming in R — Jeffery Russell

Swing by this week’s meeting to learn about the scientific programming language R. We will cover the basics of the language and dive into a fun interactive workshop.