Past Event

The Society of HPC Professionals past
Lunch & Learn Round Table Discussion Meeting

Lunch & Learn – April 2019
Hands-on demo on high performance 3D Data Visualization using ParaView

Held 25 April 2019

Note: PLEASE BRING YOUR LAPTOPS AND ALSO DOWNLOAD PARAVIEW BEFORE THE EVENT AT: https://www.paraview.org/download/

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Abstract:

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of petascale size as well as on laptops for smaller data, has become an integral tool in many national laboratories, universities and industry, and has won several awards related to high performance computation.

In this hands-on presentation we will use paraview to explore a CT scan of someone’s head -as it is typically done in medical industry imaging facilities- and also draw wind lines on a computational fluid dynamics simulation sample data to do a popular wind tunnel analysis for turbines.

Speaker Bio:

Martín Huarte-Espinosa
University of Houston HPE Data Science Institute & SHPCP Executive Director

Martín got an equivalent of a MSc. in Theoretical Astrophysics from the Astronomy Institute of UNAM University in Mexico City. Then he won a very competitive scholarship to pursue a Doctorate degree at the University of Cambridge, UK, where he had the opportunity of taking some lectures from Prof. Stephen Hawking and other great scientist. Martín’s Ph.D. dissertation used high performance computing (HPC) systems to model magnetized outflows like some observed to be ejected by very powerful, distant galaxies. In 2009 he was hired by the University of Rochester, Rochester NY, to co-develop the multi-physics, parallel, scalable, adaptive-mesh-refinement, HPC code called AstroBear. He had a joint appointment as Senior Scientist/Application Developer at the Institute of Optics too.  Martín’s Physics/HPC models and algorithms have produced several well cited publications in peer reviewed journals, including Science Magazine. He was elected a member of The Royal Astronomical Society of the UK in 2016, and has also being a member of The American Astronomical Society, The Association of Computer Machinery (ACM) SIGHPC Group, and The Society of HPC Professionals. Martin joined the University of Houston on July 2014 and has been working as an HPC Specialist at the Hewlett Packard Enterprise Data Science Institute. He works on consulting and training on technical/systematic computing, HPC methods for STEM research and has organized multiple workshops on HPC and Data Analytics topics as well. Martin was appointed the Executive Director of the SHPCP on January 2019 and he is leading education and business development campaigns to form a workforce prepared with solid technical computing skills, the latest high performance technology and the fastest data analytics directly driving decision making.