[Abstract]
Title:
Can deep learning replace current numerical weather prediction models?
DURRAN Dale, (Atmospheric Sciences, Univ of Washington) WEYN Jonathan, CARUANA Rich (Microsoft), CRESSWELL-CLAY Nathaniel (Atmospheric Sciences, Univ of Washington)
Development and application of real-time time-dependent density functional theory (RT-TDDFT) code, INQ, optimized for hybrid CPU-GPU HPC systems
Tadashi Ogitsu (Lawrence Livermore National Laboratory)
The emergence of Density Functional Theory (DFT) together with breakthroughs in algorithms and rapid increases in computer performance contributed significantly to the success of modern electronic structure theory. While DFT has been being widely used by scientists and engineers as parameter free atomistic electronic structure simulation tool due to its practicality, eg. good balance between accuracy and affordable computational cost, time dependent counter part to DFT, time dependent DFT (TDDFT) method is yet to be mature enough to be a practical tool.
In this presentation, we will introduce the open-source real-time time-dependent density-functional-theory (RT-TDDFT) code, named INQ, being developed under DOE Computational Materials Science Software Center for Nonperturbative Studies of Functional Materials Under Nonequilibrium Conditions. INQ code takes a modular design and being optimized for CPU+GPU hybrid HPC systems such as Sierra at Lawrence Livermore National Laboratory. The software design prioritizes the code portability for future HPC systems such as El Capitan (LLNL) or Frontier (Oakridge National Laboratory). The code validation will be performed comprehensively based on comparisons to the currently available ab-initio (TD)DFT codes such as Quantum-Espresso, VASP, Octopus, Siesta, as well as comparison with experiments taking advantage of the ultrafast experimental capability at Stanford Linear Accelerator National Laboratory complemented by expert theoreticians at The Molecular Foundry.
The work was performed under the auspices of the U.S. Department of Energy by LLNL under contract DE-AC52-07NA27344 and was supported by the U.S. Department of Energy, Office of Science, Materials Sciences and Engineering Division, Computational Materials Science Program.
Title:
Robust fault detection and clustering in semiconductor manufacturing processes
LOH Woong-Kee (Gachon University)
The semiconductor manufacturing consists of a number of processes, and even a small fault occurring at any stage can damage the overall product quality. Fast and accurate detection of such faults is essential to maintain high manufacturing yields. In this talk, we present algorithms for fault detection and clustering in semiconductor manufacturing processes. The fault detection algorithm is a modification of the discord detection algorithm called HOT SAX, which adopted the SAX representation of time-series for efficient storage and computation. The clustering algorithm can be used to find the causes of faults by grouping the fault detection results. We evaluate our algorithms through experiments using the time-series data obtained from real-world semiconductor plasma etching processes. As a result, our fault detection algorithm achieved 100% accuracy without any false positive or false negative. Our clustering algorithm formed good clusters of process runs having similar sources of faults.
Title:
General relativistic radiation magnetohydrodynamics simulations of black hole accretion flows based on solving the radiative transfer equation
ASAHINA Yuta (University of Tsukuba)
An accretion disk is formed around a compact object such as a black hole (BH) when rotating gas accretes onto it. In order for the gas to accrete, angular momentum must be transported, and magnetic fields play an important role. We also need to consider general relativistic effects in order to solve the structure near a black hole. In addition, radiation effects cannot be ignored for very bright objects such as ultra-luminous X-ray sources. Therefore, general relativistic radiation magnetohydrodynamics (GR-RMHD) simulations are essential to study the structure near a BH. However, most of the simulations solve the radiation transport approximatively to reduce the computational cost. Hence the accuracy of the calculation in the optically thin region is reduced. Therefore, we have developed the GR-RMHD code based on solving the frequency-integrated time-dependent radiation transfer equation. In this talk, we will present the results of the BH accretion flow simulations using this code and compare them with the approximate method. Although the computational cost is high, we show that the code can accurately solve the structure of the radiation field in the optically thin region such as near the rotation axis.
Title:
Bioinformatics in the 21st century: populations, viruses and proteins for a better future
KOPELMAN Naama (Holon Institute of Technology)
The history of genetics is filled with exciting breakthroughs, among which is the emergence of Next-Generation Sequencing (NGS) technologies. The increased throughput of the sequencing data has enabled thorough investigations of the genetic variation in various species and populations including in applications such as single-cell genomics. In parallel, advances were made at the theoretical and computational level, supporting large-scale genomic analyses. In this talk I will present my research on three case studies of genetic variation analyses: 1) Jewish populations’ history, and historical questions in light of population diversity; 2) Dynamics of SARS-CoV-2 spread in Israel in spring 2020, and epidemiological reconstruction of the history of this virus; 3) Design of improved proteins for the food and beverage industry – and an improved future for us all.