* Due to COVID-19, this year workshops will be offered online only
ICME offers a variety of summer workshops to students, ICME partners, and the wider community. This year's series of day-long workshops is happening from August 17-22, 2020, as detailed below. All workshops are from 9:00 am to 4:45 pm (made of several sessions separated by time for breaks).These are full-day workshops - you can register for one workshop per day only.Please check our website for updated course descriptions and instructor bios, and soon registration dates.
Introduction to High Performance Computing
In the past 50 years, supercomputers have achieved what was once considered only possible in Sci-Fi movies. The key to the tremendous success of supercomputers has been a combination of outstanding architectures plus software that uses all the available resources and makes parallelization possible. This secret sauce has led to different implementations across fields. A mechanical engineer would use MPI and OpenMP to have a balance between computations and memory load to deal with millions of nodes in physical simulations, whereas a data scientist would use MapReduce and Spark to have an adaptable and resilient algorithm for the challenges of big data. This workshop explores the key features of these two approaches, explaining their underground philosophy and how they use the architecture. The final goal is to give the student a taste of the different programming paradigms and the tools to decide which is the best approach.
About the Instructor: Cindy Orozco is a 5th year PhD student at ICME working with Professor Lexing Ying in matrix and tensor optimization applied to computer vision and quantum physics. She did her undergrad in Mathematics and Civil Engineering in Universidad de Los Andes, Colombia, and a masters in Applied Mathematics at King Abdullah University of Science and Technology, Saudi Arabia. Her sweet spot is the intersection between simulation, physical sciences and pure math, producing algorithms to model physical phenomena based on abstract mathematical structures. Her interest in High Performance Computing comes after an internship in Hewlett Packard Labs estimating the performance of future supercomputers and recognizing the gap between the optimal usage of these machines and the typical practices among researchers.