Computing Sciences Summer Program 2023: Talks & Events

Summer Program Kickoff

Deb Agarwal Who: Deborah Agarwal and Stefan Wild
When: June 6, time 11 a.m. - 12 p.m.
Where: B59-3101

Bio: Dr. Deborah (Deb) Agarwal's research focuses on scientific tools which enable sharing of scientific experiments, advanced networking infrastructure to support sharing of scientific data, data analysis support infrastructure for eco-science, and cybersecurity infrastructure to secure collaborative environments. Dr. Agarwal is a Research Affiliate at the Berkeley Institute for Data Science and an Inria International Chair, where she co-leads the DALHIS (Data Analysis on Large-scale Heterogeneous Infrastructures for Science) Inria Associate team. Dr. Agarwal also leads teams developing data server infrastructure to significantly enhance data browsing and analysis capabilities and enable eco-science synthesis at the watershed scale to understand hydrologic and conservation questions and at the global scale to understand carbon flux. Some of the projects Dr. Agarwal is working on include Environmental Systems Science Digital Infrastructure for a Virtual Ecosystem (ESS-DIVE), Watershed Function SFA, AmeriFlux Management Project, FLUXNET, NGEE Tropics, International Soil Carbon Network. Dr. Agarwal received her Ph.D. in electrical and computer engineering from the University of California, Santa Barbara, and a B.S. in Mechanical Engineering from Purdue University.

Bio: Stefan Wild directs the Applied Mathematics and Computational Research (AMCR) Division in the Computing Sciences Area at Lawrence Berkeley National Laboratory (Berkeley Lab). AMCR conducts research and development in mathematical modeling, simulation and analysis, algorithm design, computer system architecture, and high-performance software implementation. Wild came to Berkeley Lab in December of 2022 from Argonne National Laboratory, where he was a senior computational mathematician and deputy division director of the Mathematics and Computer Science Division.

NERSC: Scientific Discovery through Computation

Who: Rebecca Hartman-Baker
When: June 8, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: What is High-Performance Computing (and storage!), or HPC? Who uses it and why? We'll talk about these questions as well as what makes a Supercomputer so super and what's so big about scientific Big Data. Finally, we'll discuss the challenges facing system designers and application scientists as we move into the exascale era of HPC.

Bio: Rebecca Hartman-Baker leads the User Engagement Group at NERSC, where she is responsible for engagement with the NERSC user community to increase user productivity via advocacy, support, training, and the provisioning of usable computing environments. She began her career at Oak Ridge National Laboratory, where she worked as a postdoc and then as a scientific computing liaison in the Oak Ridge Leadership Computing Facility. Before joining NERSC in 2015, she worked at the Pawsey Supercomputing Centre in Australia, where she coached two teams to the Student Cluster Competition at the annual Supercomputing conference, led the HPC training program for a time, and was in charge of the decision-making process for determining the architecture of the petascale supercomputer installed there in 2014. Rebecca earned a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign.

Introduction to NERSC Resources

Who: Yun (Helen) He
When: June 8, afternoon session
Where: TBA

Abstract: This class will provide an informative overview to acquaint students with the basics of NERSC computational systems and programming environment. Topics include systems overview, connecting to NERSC, software environment, file systems and data management/transfer, and available data analytics software and services. More details on how to compile applications and run jobs on NERSC systems will be presented including hands-on exercises on Perlmutter. The class will also showcase various online resources that are available on NERSC web pages. Training accounts will be provided for students who have not yet set up a NERSC account.

Bio: Dr. Yun (Helen) He is a High Performance Computing Consultant at NERSC, Lawrence Berkeley National Laboratory. She has been the main user focus point of contact for several NERSC flagship Cray systems deployed over the past 15 years and is the NERSC training lead. Helen specializes in the software programming environment, parallel programming models, applications porting and benchmarking, and climate models. Helen has served on the Organizing Committees (including Program Chair for Cray User Group) and given technical presentations for many HPC conference series. She is on the OpenMP Language Committee and has provided tutorials at various HPC venues. Helen has co-authored a book, “OpenMP Common Core: Making OpenMP Simple Again”.

Usable and Integrated Data Systems and Software Engineering for Collaborative Science

Who: Dan Gunter
When: June 13, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: Software is ubiquitous and is critical to all scientific research, from data collection at experiments or instruments to running large simulations or data analysis on large supercomputers. Scientific software often emerges as an effort to solve a specific need and evolves with the complex and iterative scientific inquiry and needs of the project. This software may include user interfaces, databases and archives, workflow systems, and security models. There is also a need for R&D that can bridge the datasets and tools across projects and domains to support collaborative science. This talk will describe our experiences and approach to efficiently uncover the needs of scientific projects and perform targeted research and engineering to meet those needs, in collaboration with scientists from the Earth Sciences, Chemical Engineering, Biology, Material Science, and Physics.

Bio: Dan Gunter leads the Usable Data Systems (UDS) group in the Scientific Data Division (SciData). Dan's interests include usability for scientific interfaces and workflows, data management and data processing pipelines in heterogeneous environments, software engineering for distributed multidisciplinary scientific teams, and building usable interfaces to enable scientific exploration. He has led software efforts in projects for multiple domains, collaborating with science divisions at LBNL as well as other research institutions in the DOE and academia.

Topic TBA

Who: Anastasiia Butko
When: June 15, 11 a.m. - 12 p.m.
Where: B50 Auditorium

Abstract: TBA

Bio: Anastasiia Butko is part of the Applied Mathematics and Computational Research Division of Computing Sciences at Berkeley Lab.

Designing and Presenting a Science Poster

Who: Jonathan Carter
When: June 20, 11 a.m. – 12 p.m.
Where: B59-3101

Abstract: During the poster session on August 8th, members of our summer visitor program will get the opportunity to showcase the work and research they have been doing this summer. Perhaps some of you have presented posters before, or perhaps not. This talk will cover the basics of poster presentation: designing an attractive format; how to present your information clearly; what to include and what not to include. Presenting a poster is different from writing a report or giving a presentation. This talk will cover the differences, and suggest ways to avoid common pitfalls and make poster sessions work more effectively for you.

Bio: Jonathan Carter is the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory (Berkeley Lab). The Computing Sciences Area at Berkeley Lab encompasses the National Energy Research Scientific Computing Division (NERSC), the Scientific Networking Division (home to the Energy Sciences Network, ESnet) and the Computational Research Division.

Panel: Career Paths

Who: Deb Agarwal, Andy Nonaka, and Osman Malik
When: June 21, 3 - 4 p.m.
Where: B59-3101

Dr. Deb Agarwal is a Senior Scientist and Division Director for the Scientific Data Division (http://crd.lbl.gov), at Lawrence Berkeley National Laboratory (LBNL). The Scientific Data Division (SciData) transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures with scientific partners. Dr. Agarwal’s current research focuses on developing computational tools to enable scientists to organize and use Earth Science data to address challenges more effectively. She has worked on projects involving carbon flux, watershed understanding, tropical forests, soil carbon, carbon capture, cosmology, particle accelerators, data repositories, and satellite data. She is also active in efforts to broaden diversity in computing research and a member of the Computing Research Association Committee on Widening Participation.

Andy Nonaka is a Staff Scientist and Group Lead of the Center for Computational Sciences and Engineering (CCSE) at Lawrence Berkeley National Laboratory. He is interested in HPC implementations of multiphysics and multiscale algorithms for PDEs using structured grid, adaptive mesh, particle/grid, and machine learning algorithms.

Osman Malik received his PhD in Applied Mathematics from the University of Colorado Boulder. His research interests are numerical linear algebra, tensor decomposition, randomized algorithms and optimization. He is also interested in the application of these tools in machine learning and scientific computing.

High-Order Discontinuous Galerkin Methods for Fluid and Solid Mechanics

Who: Per-Olaf Persson
When: June 22, time TBA
Where: 11 a.m. - 12 p.m.

Abstract: Forthcoming

Bio: Forthcoming

Crash Course in Supercomputing

Who: Rebecca Hartman-Baker
When: June 22, 1 – 5 p.m.
Where: B59-3101

Abstract: In this two-part course, participants will learn to write parallel programs that can be run on a supercomputer. We begin by discussing the concepts of parallelization before introducing MPI and OpenMP, the two leading parallel programming libraries. Finally, participants will put together all the concepts from the class by programming, compiling, and running a parallel code on one of the NERSC supercomputers. Recommend attending AM and PM Sessions.

Overview of Research and Developments in Scalable Solvers Group

Who: Xiaoye (Sherry) Li
When: June 28, 11 a.m. – 12 p.m.
Where: Zoom (see calendar)

Abstract: We will highlight various ongoing projects in SSG. They span many areas of numerical linear algebra and high-performance scientific computing. The group members are also actively engaged in many application areas, such as material sciences, computational chemistry, machine learning, and quantum computing.

Bio: Sherry Li is a Senior Scientist in the Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory. She has worked on diverse problems in high-performance scientific computations, including parallel computing, sparse matrix computations, high precision arithmetic, and combinatorial scientific computing. She is the lead developer of SuperLU, a widely-used sparse direct solver, and has contributed to the development of several other mathematical libraries, including ARPREC, LAPACK, PDSLin, STRUMPACK, and XBLAS. She earned a Ph.D. in Computer Science from UC Berkeley and B.S. in Computer Science from Tsinghua Univ. in China. She has served on the editorial boards of the SIAM J. Scientific Comput. and ACM Trans. Math. Software, as well as many program committees of the scientific conferences. She is a SIAM Fellow and an ACM Senior Member.

LaTex Workshop

Who: Lipi Gupta
When: June 28, 3 p.m. - 4:30 pm
Where: Zoom Only

Abstract: For participants: This is an interactive activity, and it is encouraged that anyone participating have access to a LaTeX compiler.

Bio: Lipi Gupta defended her Ph. D. in Physics at the University of Chicago in July 2021. She was awarded an Office of Science Graduate Student Research Program award from the US Department of Energy to complete her Ph.D research at the SLAC National Accelerator Lab in Menlo Park, California. At SLAC, Lipi worked on studying how to apply machine learning techniques to improve particle accelerator operation and control. Lipi also has a background in nonlinear beam dynamics, focusing on sextupole magnet resonance elimination, through her research at University of Chicago and research conducted while earning a Bachelor of Arts in Physics with a minor in mathematics at Cornell University.

Securing DoE's Energy Sciences Network

Who: Fatema Wala
When: June 29, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: Forthcoming

Bio: Forthcoming

Topic TBA

Who: Talita Perciano
When: July 06, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: TBA

Bio: Forthcoming

How do Granular Materials Deform and Flow? From Particle to Continuum

Who: Ishan Srivastava
When: July 11, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: Forthcoming

Bio: Forthcoming

ALS Facility Tour

Who: Ina Reichel
When: July 12, 2 - 3 p.m. – 4 p.m.
Where: In Person at the ALS

Details: In-person tour of the Advanced Light Source (ALS) at Berkeley Lab with Ina Reichel of the Accelerator Technology and Applied Physics Division of Berkeley Lab.

Literature Surveys and Reviews: Where do we stand?

Who: Jean Luca Bez
When: July 13, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: Forthcoming

Bio: Forthcoming

Engineering Self-driving Networks

Who: Mariam Kiran
When: July 18, 11 a.m. – 12 p.m.
Where: B59-3101

Abstract: The pandemic and ongoing data challenges have highlighted the need for reliable network connectivity, but upgrading these systems is not only expensive but complex due to the many vendors involved. In my work, I've been exploring how deep learning methods that allow large data sets and train simple neural networks on these data sets, can be used to perform classification and reinforcement learning to help control and optimize the network for large-scale science transfers and give them optimal performance. In my talk I will describe the challenges faced in understanding and deploying AI models, and also how to interface these with real-world network systems paving the future for future research challenges in digital twins and self-driving infrastructures.

Bio: Dr. Kiran is a Computer Scientist in the Scientific Networking Division, Lawrence Berkeley National Laboratory. She currently leads the AI for networking research group building solutions for operational network research and engineering problems. She received her Ph.D. and MSc (Eng) in Computer Science from the University of Sheffield, UK, in 2011 and 2009, respectively. Before joining Berkeley Lab in 2016, Kiran worked at the Universities of Sheffield, Leeds, Oxford, and University College London with collaborations with European industries such as SAP, ATOS, and BT. Her research explores machine learning and decentralized optimization for wide area networks, wireless, and Cloud infrastructures, needed for building 'self-driving networks'. She also helped develop FLAME, an open-source agent-based platform, currently used worldwide for complexity research. Her notable awards include the Royal Society Scientist in Westminster in 2015, the 2017 U.S. DOE Early Career Award, and ACM's N2Women Rising Stars in Networking Award in 2021. She is an active member of ACM and a Senior Member of IEEE communities.

Scientific-driven Neural Networks for Modeling Dynamical Systems

Who: Ben Erichson
When: July 20, 11 a.m. - 12 p.m.
Where: B50 Auditorium

Abstract: Forthcoming

Bio: Forthcoming

Topic TBA

Who: Michael Wehner
When: July 25, 11 a.m. - 12 p.m.
Where: B59-3101

Abstract: TBA

Bio: Forthcoming

Topic TBA

Who: Dan Martin
When: June 16, 11 a.m. – 12 p.m.
Where: B59-3101

Abstract: TBA

Bio: Dan Martin is a computational scientist and group leader for the Applied Numerical Algorithms Group at Lawrence Berkeley National Laboratory. After earning his Ph.D. in mechanical engineering from U.C. Berkeley, Dan joined ANAG and Berkeley Lab as a post-doc in 1998. He has published in a broad range of application areas including projection methods for incompressible flow, adaptive methods for MHD, phase-field dynamics in materials, and Ice sheet modeling. His research involves the development of algorithms and software for solving systems of PDEs using adaptive mesh refinement (AMR) finite volume schemes, high (4th)-order finite volume schemes for conservation laws on mapped meshes, and Chombo development and support. Current applications of interest are developing the BISICLES AMR ice sheet model as a part of the SCIDAC-funded ProSPect application partnership, and some development work related to the COGENT gyrokinetic modeling code, which is being developed in partnership with Lawrence Livermore National Laboratory as a part of the Edge Simulation Laboratory (ESL) collaboration.

Scientific Applications in the NESAP Program

Who: Lecturer(s) TBA
When: August 1, 11 a.m. – 12 p.m.
Where: B59-3101

Abstract: NERSC Exascale Scientific Application Program started in 2014 and has been forming collaborations with application development teams and vendors in preparing scientific applications for the current and upcoming architectures. These collaborations involve NERSC staff taking deep dives into the application codes and engineering them to give optimal performance on NERSC and other systems. In this talk NERSC engineers will give an overview of their collaborations with four science teams and provide an insight into efforts involved in adapting their applications to take advantage of the next generation of supercomputing architectures. This talk will cover optimization and development efforts for applications for metagenome analysis, computational fluid dynamics, Machine learning assisted Molecular Dynamics and Climate Science.

Behavioral Based Interviewing Workshop: Effective Interviewing Techniques

Who: Bill Cannan & Nicolette Carroll
When: August 3, 11 a.m. – 12 p.m.
Where: B59-3101

Abstract: Past Behavior is the best predictor of future performance! Behavioral-based interviewing is a competency-based interviewing technique in which employers evaluate a candidate's past behavior in different situations in order to predict their future performance. This technique is the new norm for academic and industry-based organizations searching for talent. This workshop will provide information and tools to help you prepare for your next interview including an overview of the behavioral-based interview process, sample questions, and techniques on how to prepare.

Bio: Bill Cannan is the Sr. HR Division Partner that supports Computing Sciences and IT. Bill has over 20 years of HR related experience as a recruiter and HR Generalist in both industry and National Lab environments. This includes over 12 years at Berkeley Lab and three years with Lawrence Livermore National Lab. Bill is responsible for providing both strategic and hands-on full cycle Human Resources support and consultation to employees and managers.

Bio: Nicolette Carroll is a Staff HR Division Partner that supports Computing Sciences and IT.

Summer Program Poster Session

Who: All Summer Program Participants are Welcome to Attend
When: August 8, Time TBA
Where: B59, Room/Location TBA