ECSS staff share technical solutions to scientific computing challenges monthly in this open forum.
The ECSS Symposium allows the over 70 ECSS staff members to exchange on a monthly basis information about successful techniques used to address challenging science problems. Tutorials on new technologies may be featured. Two 30-minute, technically-focused talks are presented each month and include a brief question and answer period. This series is open to everyone.
Day and Time: Third Tuesdays @ 1 pm Eastern / 12 pm Central / 10 am Pacific
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Note – Symposium not held in July and November due to conflicts with PEARC and SC conferences.
Webinar (PC, Mac, Linux, iOS, Android): Launch Zoom webinar
Meeting ID: 892 8873 8446
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Find your local number to join by phone: https://illinois.zoom.us/u/konD1P8cl
Upcoming events are also posted to the Training category of XSEDE News.
Due to the large number of attendees, only the presenters and host broadcast audio. Attendees may submit chat questions to the presenters through a moderator.
To better secure Zoom meetings all participants are now required to log in to their Zoom account (personal or university/institution) in order to access any XSEDE meeting. If you do not currently have an account, you can create one at https://zoom.us/signup
Previous years' ECSS seminars may accessed through these links:
March 16, 2021
HPC for epidemic modeling with limited data: COVID-19 case studies
Presenter(s): Kelly Pierce (TACC)
The novel coronavirus (SARS-CoV-2) emerged in late 2019 and spread globally in early 2020. Initial reports suggested the associated disease, COVID-19, produced rapid epidemic growth and caused high mortality. As the virus sparked local epidemics in new communities, health systems and policy makers were forced to make decisions with limited information about the spread of the disease. The UT COVID-19 Modeling Consortium formed in response to the urgent need for increased situational awareness and developed a library of COVID-19 models to project infections and healthcare burdens. These models were used to inform policy decisions in the city of Austin, Texas and as part of the CDC COVID-19 mortality and infection model ensembles. Now one year into the pandemic, the Consortium has expanded the scope of its work to include estimates of infection introductions in schools, statistically informed guidelines for genomic surveillance to detect novel variants, and equitable vaccine distribution. As an early partner in the Consortium, the Texas Advanced Computing Center (TACC) has provided support in software development, data management, and long-term modeling infrastructure development. This talk will overview the joint work of the Consortium and TACC, with an emphasis on the impact of limited data availability in epidemiological modeling and the role of high-performance computing in supporting fast turn-around of time-sensitive results.
February 16, 2021
MuST – A high performance computing software package for the ab initio study of materials
Presenter(s): Yang Wang (Pittsburgh Supercomputing Center)
Ab initio calculation is one of the most popular computational practices in the HPC user community. It aims to study molecules or materials using quantum mechanics as its fundamental principle, rather than being based upon empirical or semi-empirical models. In the past decade, several computational tools developed for ab initio calculation have become available to the research community. In this presentation, I will introduce MuST, an open source software project supported by NSF CSSI program. MuST package is designed for enabling ab initio investigation of disordered materials. It is developed based on multiple scattering theory with Green function approach in the framework of density functional theory, and is built upon decades of development of research codes that include 1) KKR method, which is an all-electron, full-potential, ab initio electronic structure calculation method; 2) KKR-CPA method, which is a highly efficient ab initio method for the study of random alloys, and 3) Locally Self-consistent Multiple Scattering (LSMS) method, which is a linear scaling ab initio code capable of treating extremely large disordered systems from the first principles using the largest parallel supercomputers available. Strong disorder and localization effects can also be studied in real system within the LSMS formalism with cluster embedding in an effective medium, e.g., DMFT, DCA, or TMDCA, enabling a scalable approach for the ab initio studies of quantum materials. I will show the latest development of the MuST project, and discuss its potential applications.
January 19, 2021
Introduction to Jetstream2 - Accelerating Science and Engineering on Demand
Presenter(s): Jeremy Fischer (Indiana University)
This talk will give an overview of Jetstream and the award of Jetstream2. We'll discuss successes, failures, and some things we learned along the way. We'll discuss use cases and try to provide plenty of time for questions about the system at the end of the session.
Exosphere, User-Friendly Interface for Research Clouds
Presenter(s): Chris Martin (University of Arizona) Julian Pistorius (University of Arizona)
Exosphere is a client interface for managing computing workloads on OpenStack cloud infrastructure. It is a user-friendly alternative to Horizon, the default OpenStack graphical interface. Exosphere can be used with most research cloud infrastructure, requiring near-zero custom integration work. The Exosphere team aims to bring advanced features of research clouds within reach of non-advanced users, such as elastic workload scaling, GPU-accelerated streaming desktops, and secure, reproducible sharing of data science workbench environments. Link to Slides
October 20, 2020
Presenter(s): Sergiu Sanielevici (PSC)
Neocortex will be a highly innovative resource at PSC that will accelerate AI-powered scientific discovery by vastly shortening the time required for deep learning training, foster greater integration of artificial deep learning with scientific workflows, and provide revolutionary new hardware for the development of more efficient algorithms for artificial intelligence and graph analytics.
Presenter(s): Shawn Brown (PSC)
Bridges-2, PSC's newest supercomputer, will provide transformative capability for rapidly evolving, computation-intensive and data-intensive research, creating opportunities for collaboration and convergent research. It will support both traditional and non-traditional research communities and applications. Bridges-2 will integrate new technologies for converged, scalable HPC, machine learning and data; prioritize researcher productivity and ease of use; and provide an extensible architecture for interoperation with complementary data-intensive projects, campus resources, and clouds.
September 15, 2020
High Resolution Spatial Temporal Analysis of Whole-Head 306-Channel Magnetoencephalography & 66-Channel Electroencephalography Brain Imaging in Humans During Sleep
Presenter(s): David Shannahoff-Khalsa (UCSD) Mona Wong (SDSC) Jeff Sale (SDSC)
In chronobiology, the circadian rhythm is known as the 24-hr sleep-wake cycle. The ultradian rhythm has a shorter cycle with approximately a 1-3 hour periodicity, with considerable variability. This project's goal is to follow up on our earlier EEG work during sleep, and that of others, that has identified a rhythm of how the two cerebral hemispheres alternate in dominance with coupling to the ultradian rhythm of the rapid eye movement (REM) and non-rapid eye movement (NREM) sleep cycle. Here we are also comparing whole head and regional variations in cerebral dominance to gain better insight to this novel rhythm during sleep. This rhythm of alternating cerebral hemispheric dominance also manifests during the waking state, and it is apparently coupled to every major bodily system and now presents as a novel rhythm regulated by the central and autonomic nervous systems via the hypothalamus. With the support of XSEDE ECSS, this project has processed 306-channel magnetoencephalography that includes 3 signal types (1 magnetometer, 2 opposing gradiometers) and 66-channel EEG recordings from 4 normal healthy sleep subjects. We are analyzing the data to compare the 4 signal types filtered into 6 frequency bands, over the whole head and 6 discrete regions of the head to see how they vary with the REM and NREM sleep stages. Our analysis includes a relatively new algorithm called Fast Orthogonal Search that is well suited for analyzing the periodicity in nonlinear dynamical systems. Our analysis also includes unique methods in visualization for observing how these patterns of left minus right hemisphere power exhibit during sleep stages.