conference-talk

Utilizing Machine Learning to Build a Gridded Real-time Fuel Moisture Content System from Sparsely Measured Surface Observations and Satellite Data

Date and Time: 
Tuesday April 9th 2019
Location: 
CG Auditorium
Speaker: 
Tyler McCandless
Speaker Description: 
Tyler McCandless is a Machine Learning Scientist in the Research Applications Laboratory at the National Center for Atmospheric Research in Boulder, Colorado. He earned three degrees in Meteorology from Penn State University: PhD - 2015, MS - 2010 and BS - 2010. After earning his doctorate, Tyler worked in the private sector until May 2018, with his previous position as Manager of Services at Ascend Analytics, which is a energy risk modeling software company in Boulder. At NCAR, Tyler is responsible for providing high level machine learning expertise to various projects, including using machine learning techniques to improve wind and solar power prediction for a project in Kuwait, and building an algorithm to improve wildfire prediction with gridded fuel moisture content estimates.
 

Event Category:

Comparison of Univariate Time Series Prediction Methods

Date and Time: 
Tuesday April 9th 2019
Location: 
CG Auditorium
Speaker: 
Maggie Sleziak-Sallee
Speaker Description: 
Maggie has been working as a Software Engineer for the University Corporation for Atmospheric Research (UCAR) since 2002. As part of her duties, she oversees data transfer and processing operations for Radio Occultation satellite missions such as the COSMIC-1 mission launched in 2006. Maggie holds a Bachelor of Science in Computer Science, as well as a Master of Science in Data Science from Regis University. She also holds a Bachelor of Arts and a Master of Music degrees, and she enjoys playing the violin with her Gypsy Jazz quartet.
 

Event Category:

Applications of Machine Learning to Analysis and Computation for Particle Accelerators

Date and Time: 
Tuesday April 9th 2019
Location: 
CG Auditorium
Speaker: 
Jonathan Edelen
Speaker Description: 
Jonathan Edelen is an accelerator physicist with a broad range of experience across the field. Currently, He is working on the development of symplectic space charge algorithms, novel symplectic algorithms for phase space deposition, machine learning for modeling and control of particle accelerators, and the application of nonlinear optimization methods to accelerator technology such as thermionic energy converters.
 

Event Category:

A New Deep Learning Software to Extract Tropical and Extratropical Cyclone Information from Different Data Sources

Date and Time: 
Tuesday April 9th 2019
Location: 
CG Auditorium
Speaker: 
Christina Kumler
Speaker Description: 
Christina comes from a math background and got her undergrad degree at CU Boulder in Applied Math. She then went to University of Miami FL to get her masters in Meteorology and Oceanography. She enjoys taking photos while perusing her hobbies of cooking and baking as well as being outside where she can be found hiking or racing triathlons. This sparked her interest in weather and feeds her drive to make weather forecasts better with improving how we handle big data.
 
 

Event Category:

Arm HPC EcoSystem

Date and Time: 
Monday April 8th 2019
Location: 
CG Auditorium
Speaker: 
Srinath Vadlamani
We will present the current state of the Arm HPC ecosystem. This will include current vendor hardware, software tools from Arm and other vendors. We will present features of the A-Profile Arm architecture that are beneficial for HPC applications. A survey of affiliated scientific applications performance on Arm will also be presented.
 
Speaker Description: 
Srinath Vadlamani is a Field Application Engineer at Arm. His primary goal is Techinical Account Manager for the US Tri-labs.
 

Event Category:

It's HIP to Enhance Performance Portability of GPU Accelerated Software

Date and Time: 
Monday April 8th 2019
Location: 
CG Auditorium
Speaker: 
Joe Schoonover
Speaker Description: 
Dr. Joseph Schoonover holds degrees in Applied Mathematics, Physics, and Geophysical Fluid Dynamics from Florida State University. His graduate studies focused on Gulf Stream separation dynamics and high order methods for computational fluid dynamics. After graduating from FSU, he held a post-doc position at the Center for Non-Linear Studies at Los Alamos National Laboratory. This is where his interest in GPU acceleration was born through mentorship activities at the Parallel Computing Summer Research Internship. After leaving CNLS and LANL, Joe became an associate scientist at CU Boulder to work at NOAA's Space Weather Prediction Center to accelerate the operational WAM-IPE code for modeling ionosphere phenomena. Joe has since moved on to a startup company, Fluid Numerics, founded with Guy Thorsby and Elizabeth Simons, that aims to help domain scientists and software developers leverage the latest compute technologies and cloud computing platforms for high performance computing.
 

Event Category:

Introduction to Modern HPC Architectures

Date and Time: 
Monday April 8th 2019
Location: 
CG Auditorium
Speaker: 
Alessandro Fanfarillo

In this talk, a broad introduction to modern HPC architectures will be provided.

Speaker Description: 
Alessandro Fanfarillo is a Senior Software Engineer at the National Center for Atmospheric Research. His work is mostly devoted to performance enhancement of parallel weather models, GPGPU computing and software design/refactoring of scientific codes. His research focuses on how to exploit heterogeneous architectures CPU+Accelerators and Partitioned Global Address Space (PGAS) languages (in particular coarray Fortran) for scientific purposes. He is also the lead developer of OpenCoarrays, the open-source library that implements the coarray support in the GNU Fortran compiler.
 

Event Category:

Building data centric website for research projects and research groups

Date and Time: 
Thursday 2018 Apr 5th
Location: 
CG North Auditorium
Speaker: 
Amit Chourasia

Duration: Half day
Level: Beginner (No pre-requisites, minimal familiarity with command line helpful)

Speaker Description: 

Amit Chourasia is a Sr. Visualization Scientist at the San Diego Supercomputer Center, UC San Diego where he leads the Visualization Group. His work is focused on leading the research, development and application of software tools and techniques for visualization. Result and data sharing are also at a forefront of his interests, to this end he has developed a web based cloud infrastructure to enable this important and at times critical gap in scientific process via the SeedMe project.

Event Category:

Exploiting Computation and Communication Overlap in MVAPICH2 and MVAPICH2-GDR MPI Libraries

Date and Time: 
Wednesday 2018 Apr 4th
Location: 
CG Center Auditorium
Speaker: 
DK Panda

This talk will focus on the set of features available in MVAPICH2 and MVAPICH2-GDR MPI libraries to exploit overlap of computation and communication on modern clusters. Sample features will include: job start-up, point-to- point operations, RMA operations, kernel-based collectives, and non-blocking collectives (with and without core- direct support). For MVAPICH2-GDR, we will additionally focus on the use of GPU Direct RDMA, kernel-based reduction and datatype operations. Performance benefits of these features will be presented.

Speaker Description: 

DK Panda is a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. He has published over 400 papers in the area of high-end computing and networking. The MVAPICH2 (High Performance MPI and PGAS over InfiniBand, Omni-Path, iWARP and RoCE) libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 2,875 organizations worldwide (in 86 countries). More than 451,000 downloads of this software have taken place from the project's site. This software is empowering several InfiniBand clusters (including the 1 st , 9 th , 12 th , 17 th , and 48 th ranked ones) in the TOP500 list. The RDMA packages for Apache Spark, Apache Hadoop and Memcached together with OSU HiBD benchmarks from his group (http://hibd.cse.ohio-state.edu) are also publicly available. These libraries are currently being used by more than 275 organizations in 34 countries. More than 25,300 downloads of these libraries have taken place. A high-performance and scalable version of the Caffe framework is available from https://hidl.cse.ohio-state.edu. Prof. Panda is an IEEE Fellow. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Event Category:

Keynote: Designing HPC, Big Data, Deep Learning, and Cloud Middleware for Exascale Systems: Challenges and Opportunities

Date and Time: 
Tuesday 2018 Apr 3rd
Location: 
CG Auditorium
Speaker: 
DK Panda

This talk will focus on challenges and opportunities in designing HPC, Big Data, Deep Learning, and HPC Cloud middleware for Exascale systems with millions of processors and accelerators. For the HPC domain, we will discuss about the challenges in designing runtime environments for MPI+X (PGAS - OpenSHMEM/UPC/CAF/UPC++, OpenMP, and CUDA) programming models by taking into account support for multi-core systems (KNL and OpenPower), high-performance networks, GPGPUs (including GPUDirect RDMA), and energy-awareness.

Speaker Description: 

DK Panda is a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. He has published over 400 papers in the area of high-end computing and networking. The MVAPICH2 (High Performance MPI and PGAS over InfiniBand, Omni-Path, iWARP and RoCE) libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 2,875 organizations worldwide (in 86 countries). More than 451,000 downloads of this software have taken place from the project's site. This software is empowering several InfiniBand clusters (including the 1 st , 9 th , 12 th , 17 th , and 48 th ranked ones) in the TOP500 list. The RDMA packages for Apache Spark, Apache Hadoop and Memcached together with OSU HiBD benchmarks from his group (http://hibd.cse.ohio-state.edu) are also publicly available. These libraries are currently being used by more than 275 organizations in 34 countries. More than 25,300 downloads of these libraries have taken place. A high-performance and scalable version of the Caffe framework is available from https://hidl.cse.ohio-state.edu. Prof. Panda is an IEEE Fellow. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Event Category:

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