ECSS Symposium

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.

Symposium coordinates

Day and Time: Third Tuesdays @ 1 pm Eastern / 12 pm Central / 10 am Pacific
Add this event to your calendar. 
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

Password: 398208

One tap mobile

+13462487799,,89288738446# US (Houston)

+16027530140,,89288738446# US (Phoenix)


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

Key Points
Monthly technical exchange
ECSS community present
Open to everyone
Tutorials and talks with Q & A
Contact Information

The June, July and August 2021 ECSS Symposia were canceled. Note that there is no Symposium in July due to proximity to PEARC.

Previous years' ECSS seminars may accessed through these links:

September 21, 2021

InterACTWEL Cyberinfrastructure: Enabling Long-term AI-driven Decision Support for Adaptive Management of Water, Energy, and Land Resources in Watershed Communities

Presenter(s): Meghna Babbar-Sebens (Oregon State University) Samuel Rivera (Oregon State University) Eroma Abeysinghe (Indiana University) Eric Coulter (Indiana University)

Cyberinfrastructure serves as backbone to many of the complex and data-intensive computational analyses typically conducted for climate change impact assessment and decision support. However, cyberinfrastructure research in the recent past has been primarily focused on supporting the needs of researchers via support of networking, storage, standards, middleware, and computation capabilities. Adaptation to climate change in watershed communities will require long-term interactions with stakeholders for coordination of context-sensitive decisions, as conditions evolve over time. This means that application of Artificial Intelligence (AI) in adaptation research will need to consider the social-physical and dynamic nature of climate-change resilience problems in order to be decision-relevant. This has necessitated a broader vision for the role of AI-ready cyberinfrastructure in supporting multi-years stakeholder engagement for climate-change resilience. In this presentation, we present a novel, use-inspired, cyberinfrastructure InterACTWEL, which is being created to support longitudinal collaboration between researchers and decision makers on stakeholder-driven planning of adaptation to climate-change impacts in local watershed communities. We demonstrate how InterACTWEL cyberinfrastructure is being used to support AI-assisted and stakeholder-driven planning of water supply resilience in a testbed local community within the Columbia River Basin.


May 18, 2021

COVID-19 Drug Repurposing Guidance using Fragment Molecular Orbital (FMO) Calculations

Presenter(s): Aaron Frank (University of Michigan) Dimuthu Wannipurage (Indiana University Pervasive Technology Institute) Suresh Marru (Indiana University Pervasive Technology Institute)

Presentation Slides Dimuthu Upeksha Wannipurage Slides

Presentation Slides Aaron Frank Slides

Presentation Slides Suresh Marru Slides

In this talk, we share our experiences and updates of a COVID-19 HPC Consortium project (https://covid19-hpc-consortium.org/projects/5eb5c8784c0571007b307650). Motivated by the need to rapidly identify drugs that are likely to bind to targets implicated in SARS-CoV-2, the virus that causes COVID-19, we present a framework for Fragment Molecular Orbital (FMO) calculations to speed up quantum mechanical calculations that can be used to explore structure-energy relationships in large and complex biomolecular systems. These calculations are still onerous, especially when applied to large sets of molecules.. We will share our XSEDE ECSS collaboration in assisting with cyberinfrastructure aspects, mechanisms and user interfaces that manage job submissions, data retrieval, and data storage for the FMO calculations. The talk will summarize how we used the Apache Airavata science gateway platform to apply FMO calculations to complexes formed between SARS-CoV-2 Mpro (the main protease in SARS-CoV-2) and 2820 approved and experimental drugs in a drug-repurposing library. The talk will highlight Airavata's job submission and monitoring enhancements to support static and parallel parameter sweeping capability on remote compute clusters across a batch of input data. We will discuss integration of a data parsing workflow to capture, filter out, and validate the enriched metadata from the outputs. Finally, we will discuss generalization of the extensions made in support of large-scale FMO calculations for SARS-CoV-2 Mpro-drug complexes and potential use in other biomolecular systems.


April 20, 2021

Leveraging Augmented Reality to Enhance Remote Collaboration

Presenter(s): Max Collins (UC Irvine)

Presentation Slides

Augmented Reality (AR) is a medium that gives people the ability to engage with digital information in ways that deviate from more traditional HCI methods (e.g. WIMP user interfaces). Remote work experiences leveraging teleconferencing are becoming increasingly prevalent as many are working together remotely in higher frequencies. In this talk we cover our investigation into the ways that AR can support efforts to work together across distance, and how invoking AR may create a sense of joint focus and engagement beyond what traditional remote collaboration tools afford. We outline the design process of an AR add-on to teleconferencing tools (e.g. Zoom) that allows participants to interact with one another around digital assets in AR, and share objects with one another through the screen. We investigate the use cases of this tool and describe the evaluation methods and preliminary user testing results of this system.

Best Practices for Research Software Engineers

Presenter(s): Rudi Eigenmann (University of Delaware)

Presentation Slides

The Xpert Network brings together teams and individuals that support domain scientists in developing, optimizing and running computational and data-intensive applications. One goal is to develop best practices. In this talk I will summarize initial results. They include both software engineering advice and recommendations for team organization and collaboration. The results also include experiences with tools that can accelerate the work of research software engineers. A particular emphasis will be on practices that differ from those applicable in a general software engineering context.


March 16, 2021

HPC for epidemic modeling with limited data: COVID-19 case studies

Presenter(s): Kelly Pierce (TACC)

Presentation Slides

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)

Presentation Slides

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.


Showing 1 - 5 of 95 results.
Items per Page 5
of 19