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UID:submissions.pasc-conference.org_PASC24_sess156@linklings.com
SUMMARY:Flash Poster Session - Part I
DESCRIPTION:Poster\n\nThe aim of this rapid-fire session is to allow poste
 r presenters to introduce the topic of their poster and motivate the audie
 nce to visit them at the poster session scheduled on the following day. Pr
 esenters will have 30 seconds to engage the audience.\n\nP14 - DynaHGraph:
  Learning Hidden Relationships in Dynamic Graphs\n\nDynamic graphs, whose 
 topologies are defined by a time-evolving set of nodes or entities and cor
 responding edges or relationships between such entities, are an important 
 field of study across many scientific domains.  Often, it is desirable to 
 learn graph topologies when nodes and edges in the graph...\n\n\nKurtis Sh
 uler and Lekha Patel (Sandia National Laboratories)\n---------------------
 \nP01 - Accelerating the Computation of Koopmans Functionals Using the SIR
 IUS Library\n\nThe evaluation of Koopmans functionals is a subject of comm
 on interest for the scientific community, as it has been proved that by us
 ing them it is possible to correct DFT theory predictions with accuracy in
  line with the state-of-the-art many-body perturbation theory (GW), which 
 on the other hand i...\n\n\nGiovanni Consalvo Cistaro (EPFL), Nicola Colon
 na and Iurii Timrov (Paul Scherrer Institute), Anton Kozhevnikov (ETH Zuri
 ch / CSCS), and Nicola Marzari (EPFL)\n---------------------\nP11 - The Co
 ulomb Perturbed Fragmentation (CPF) Method\n\nCorrelated electronic struct
 ure calculations enable accurate determination of the physicochemical prop
 erties of complex molecular systems. Nevertheless, the computational cost 
 of these calculations sets constraints on their ability to be scaled up. T
 he Fragment Molecular Orbital (FMO) method is wide...\n\n\nFazeleh Sadat K
 azemian, Jorge L. Galvez Vallejo, and Giuseppe Barca (Australian National 
 University)\n---------------------\nP18 - Exact Conservation Laws for Neur
 al Network Integrators of Dynamical Systems\n\nWe consider the constructio
 n of neural network surrogates for the solution of differential equations 
 that describe the time evolution of physical systems. In contrast to other
  problems that are tackled by machine learning, in this case usually a lot
  is known about the system at hand: for many dynami...\n\n\nEike Mueller (
 University of Bath)\n---------------------\nP13 - A Distributed LogStore D
 esign with Multi-Reader, Multi-Writer Semantics for Streaming Applications
 \n\nIn this work we describe the design and implementation of a distribute
 d logstore that can be used for storing events from streaming applications
  such as Telemetry and Satellite Remote Sensing. The logstore provides mul
 ti-writer, multi-reader (MWMR) semantics. It also totally orders events us
 ing time...\n\n\nAparna Sasidharan, Anthony Kougas, and Xianhe Sun (Illino
 is Institute of Technology)\n---------------------\nP07 - Automatic Genera
 tion of Block-Structured Grids on Complex Ocean Domains for High Performan
 ce Simulation\n\nClimate change research increasingly relies on interdisci
 plinary scientific studies utilizing advanced computational methods. For m
 odeling climate compartments, the choice of the underlying grid is difficu
 lt; therefore, unstructured grids are often preferred. An alternative are 
 block-structured grid...\n\n\nSara Faghih-Naini (ECMWF), Daniel Zint (New 
 York University), Vadym Aizinger and Jonathan Schmalfuß (University of Bay
 reuth), and Roberto Grosso and Julian Stahl (Friedrich-Alexander-Universit
 ät Erlangen-Nürnberg)\n---------------------\nP02 - Accurate Machine Learn
 ing Force Fields via Experimental and Simulation Data Fusion\n\nIn molecul
 ar dynamics, Machine Learning potentials (MLPs) have seen tremendous succe
 ss when trained bottom-up on ab initio forces and energies. MLPs enable si
 mulation times out of reach for ab initio computations at accuracies out o
 f reach for classical force fields. However, due to the underlying a...\n\
 n\nSebastien Röcken and Julija Zavadlav (Technical University of Munich)\n
 ---------------------\nP15 - Enabling Message-Driven Architecture Evaluati
 on for the Extreme Heterogeneity Era with MOSAIC\n\nMassive parallelism an
 d extreme heterogeneity are key to enabling futuristic exascale high-perfo
 rmance computing (HPC). Parallelism usually involves a shared-memory model
  with hardware-based cache-coherence mechanisms that enforce atomicity, en
 suring transparent data movement and memory consistency....\n\n\nPatricia 
 Gonzalez-Guerrero and Anastasiia Butko (Lawrence Berkeley National Laborat
 ory); Chris Neely (AMD); and Farzad Fatollahi-Fard, Jordi Wolfson-Pou, Mar
 io Vega, Thom Popovici, and John Shalf (Lawrence Berkeley National Laborat
 ory)\n---------------------\nP04 - Advancing Fault Tolerance in Graph Proc
 essing Engines Based on Total Order Multicast\n\nData for many problem dom
 ains are naturally well represented as graphs, and graph analytics has thu
 s become an important tool in many areas of business and science alike. In
  order to support increasingly large data sets and thus graph with increas
 ingly large sets of vertices and edges, scalable grap...\n\n\nEkkehard Ste
 inmacher, Fernando Pedone, Olaf Schenk, and Patrick Eugster (Università de
 lla Svizzera italiana)\n---------------------\nP12 / ACMP01 - DeCovarT, a 
 Multidimensional Probalistic Model for the Deconvolution of Heterogeneous 
 Transcriptomic Samples\n\nAlthough bulk transcriptomic analyses have great
 ly contributed to a better understanding of complex diseases, their sensib
 ility is hampered by the highly heterogeneous cellular compositions of bio
 logical samples. To address this limitation, computational deconvolution m
 ethods have been designed to a...\n\n\nBastien Chassagnol (University of P
 aris VI, ardata); Grégory Nuel (University of Paris VI); and Etienne Becht
  (INSERM)\n---------------------\nP09 - Contribution of Latent Variables t
 o Emulate the Physics of the IPSL Model\n\nAtmospheric general circulation
  models include two main distinct components: the dynamical one solves the
  Navier-Stokes equations to provide a mathematical representation of atmos
 pheric movements while the physical one includes parameterizations represe
 nting small-scale phenomena such as turbulence ...\n\n\nSégolène Crossouar
 d (Laboratoire des Sciences du Climat et de l’Environnement, CEA); Masa Ka
 geyama and Mathieu Vrac (Laboratoire des Sciences du Climat et de l’Enviro
 nnement, CNRS); Thomas Dubos (Laboratoire de Météorologie Dynamique, École
  Polytechnique); and Soulivanh Thao and Yann Meurdesoif (Laboratoire des S
 ciences du Climat et de l’Environnement, CEA)\n---------------------\nP19 
 - Fast and Scalable Algorithms for Selected Matrix Inversions\n\nThe inver
 sion of sparse linear systems gives rise to dense matrices. Their computat
 ion poses not only a computational but also a memory bottleneck. Numerous 
 applications from various fields require, however, only particular, i.e. s
 elected entries of the complete inverse. Applications range from area...\n
 \n\nLisa Gaedke-Merzhäuser (Università della Svizzera italiana); Vincent M
 aillou, Alexandros N. Ziogas, and Mathieu Luisier (ETH Zurich); and Olaf S
 chenk (Università della Svizzera italiana)\n---------------------\nP06 - A
 tlas as a Unified Data Structure Interface for Computation on Heterogeneou
 s Architectures\n\nAt ECMWF, the Integrated Forecasting System (IFS) is un
 dergoing an incremental code refactoring aimed at running the forecast on 
 heterogeneous computing architectures. One strategy is using the open-sour
 ce and in-house developed Atlas library, which provides data structures, m
 emory management and pa...\n\n\nSlavko Brdar, Willem Deconinck, and Michae
 l Lange (ECMWF)\n---------------------\nP03 - Additively Preconditioned Tr
 ust Region Strategies for Machine Learning\n\nIn our work we adopt a novel
  variant of the “Additively Preconditioned Trust-Region Strategy” (APTS) t
 o train neural networks (NNs). APTS is based on a right preconditioned Tru
 st-Region (TR) method, which utilizes an additive \ndomain-decomposition-b
 ased preconditioner. In the context of ...\n\n\nSamuel Cruz (Università de
 lla Svizzera italiana, UniDistance Suisse); Ken Trotti (Università della S
 vizzera italiana); Alena Kopaničáková (Brown University, Università della 
 Svizzera italiana); and Rolf Krause (Università della Svizzera italiana, U
 niDistance Suisse)\n---------------------\nP08 - Complete Asynchronous Tas
 k-Based Implementation of a Particle-In-Cell Code: Performance Studies and
  Benchmark\n\nIn this work, a cutting-edge full implementation of task-bas
 ed programming paradigms applied to a complete particle-in-cell code is sh
 own. The core of the implementation has been based on the algorithm of the
  particle-in-cell code Smilei (https://smileipic.github.io/Smilei/), altho
 ugh a complete cod...\n\n\nJuan José Silva Cuevas (Maison de la Simulation
 )\n---------------------\nP16 - Enhancing Aerosol Predictions on the Globa
 l Scale with Particle-Resolved Modeling and Machine Learning\n\nAtmospheri
 c aerosols play an important role in several key processes related to atmo
 spheric chemistry and physics. However, to limit computational expense, cu
 rrent regional and global chemical transport models need to grossly simpli
 fy the representation of aerosols, thereby introducing errors and un...\n\
 n\nNicole Riemer (University of Illinois Urbana-Champaign), Zhonghua Zheng
  (University of Manchester), Jeffrey H. Curtis (University of Illinois Urb
 ana-Champaign), Justin L. Wang (WorldQuant), Po-Lun Ma (Pacific Northwest 
 National Laboratory), Xiaohong Liu (Texas A&M University), and Matthew Wes
 t (University of Illinois Urbana-Champaign)\n---------------------\nP10 - 
 Controlling Parallel CFD Simulations in Julia from C/C++/Fortran Programs 
 with libtrixi\n\nWith libtrixi we present a software library to control co
 mplex Julia code from a main program written in a different language. Spec
 ifically, libtrixi provides an API to Trixi.jl, a Julia package for adapti
 ve numerical simulations of conservation laws, used to accurately predict 
 naturally occurring p...\n\n\nBenedict Geihe (University of Cologne); Mich
 ael Schlottke-Lamkemper (RWTH Aachen University, High-Performance Computin
 g Center Stuttgart); and Gregor Gassner (University of Cologne)\n\nSession
  Chair: Erik W. Draeger (Lawrence Livermore National Laboratory)
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