{"675269":{"#nid":"675269","#data":{"type":"news","title":"International Conference Meets to Make Math Easier for Computer Models","body":[{"value":"\u003Cp\u003EFrom weather prediction to drug discovery, math powers the models used in computer simulations. To help these vital tools with their calculations, global experts recently met at Georgia Tech to share ways to make math easier for computers.\u003C\/p\u003E\u003Cp\u003ETech hosted the 2024 International Conference on Preconditioning Techniques for Scientific and Industrial Applications (\u003Ca href=\u0022https:\/\/www.math.emory.edu\/~yxi26\/Precond24\/index.html\u0022\u003E\u003Cstrong\u003EPrecond 24\u003C\/strong\u003E\u003C\/a\u003E), June 10-12.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EPreconditioning accelerates matrix computations, a kind of math used in most large-scale models. These computer models become faster, more efficient, and more accessible with help from preconditioned equations.\u003C\/p\u003E\u003Cp\u003E\u201cPreconditioning transforms complex numerical problems into more easily solved ones,\u201d said\u0026nbsp;\u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~echow\/\u0022\u003E\u003Cstrong\u003EEdmond Chow\u003C\/strong\u003E\u003C\/a\u003E, a professor at Georgia Tech and co-chair of Precond 24\u2019s local organization and program committees.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u201cThe new problem wields a better condition number, giving rise to the name preconditioning.\u201d\u003C\/p\u003E\u003Cp\u003EResearchers from 13 countries presented their work through 20 mini-symposia and seven invited talks at Precond 24. Their work showcased the practicality of preconditioners.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/scholar.google.nl\/citations?user=yxEPFl4AAAAJ\u0026amp;hl=en\u0022\u003E\u003Cstrong\u003EVandana Dwarka\u003C\/strong\u003E\u003C\/a\u003E, an assistant professor at Delft University of Technology, shared newly developed preconditioners for electromagnetic simulations. This technology can be used in further applications ranging from imaging to designing nuclear fusion devices.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/math.tufts.edu\/people\/faculty\/xiaozhe-hu\u0022\u003E\u003Cstrong\u003EXiaozhe Hu\u003C\/strong\u003E\u003C\/a\u003E presented a physics-based preconditioner that simulates biophysical processes in the brain, such as blood flow and metabolic waste clearance. Hu brought this research from Tufts University, where he is an associate professor.\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/people.llnl.gov\/hartland1\u0022\u003E\u003Cstrong\u003ETucker Hartland\u003C\/strong\u003E\u003C\/a\u003E, a postdoctoral researcher at Lawrence Livermore National Laboratory, discussed preconditioning in contact mechanics. This work improves the modeling of interactions between physical objects that touch each other. Many fields stand to benefit from Hartland\u2019s study, including mechanical engineering, civil engineering, and materials science.\u003C\/p\u003E\u003Cp\u003EA unique aspect of this year\u2019s conference was an emphasis on machine learning (ML). Between a panel discussion, tutorial, and several talks, experts detailed how to employ ML for preconditioning and how preconditioning can train ML models.\u003C\/p\u003E\u003Cp\u003EPrecond 24 invited seven speakers from institutions around the world to share their research with conference attendees. The presenters were:\u0026nbsp;\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/mdessole.github.io\/\u0022\u003E\u003Cstrong\u003EMonica Dessole\u003C\/strong\u003E\u003C\/a\u003E, CERN, Switzerland\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/selimegurol.com\/\u0022\u003E\u003Cstrong\u003ESelime Gurol,\u003C\/strong\u003E\u003C\/a\u003E CERFACS, France\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/searhein.github.io\/\u0022\u003E\u003Cstrong\u003EAlexander Heinlein\u003C\/strong\u003E\u003C\/a\u003E, Delft University of Technology, Netherlands\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/people.llnl.gov\/li50\u0022\u003E\u003Cstrong\u003ERui Peng Li\u003C\/strong\u003E\u003C\/a\u003E, Lawrence Livermore National Laboratory, USA\u0026nbsp;\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/pazner.github.io\/\u0022\u003E\u003Cstrong\u003EWill Pazner\u003C\/strong\u003E\u003C\/a\u003E, Portland State University, USA\u0026nbsp;\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/www.numerical.rl.ac.uk\/people\/tyrone-rees\/\u0022\u003E\u003Cstrong\u003ETyrone Rees\u003C\/strong\u003E\u003C\/a\u003E, Science and Technology Facilities Council, UK\u003C\/li\u003E\u003Cli\u003E\u003Ca href=\u0022https:\/\/www.unm.edu\/~jbschroder\/\u0022\u003E\u003Cstrong\u003EJacob B. Schroder\u003C\/strong\u003E\u003C\/a\u003E, University of New Mexico, USA\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EAlong with hosting Precond 24, several Georgia Tech researchers participated in the conference through presentations.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EPh.D. students\u0026nbsp;\u003Ca href=\u0022https:\/\/huanghua1994.github.io\/\u0022\u003E\u003Cstrong\u003EHua Huang\u003C\/strong\u003E\u003C\/a\u003E and\u0026nbsp;\u003Ca href=\u0022https:\/\/www.cc.gatech.edu\/people\/shikhar-shah\u0022\u003E\u003Cstrong\u003EShikhar Shah\u003C\/strong\u003E\u003C\/a\u003E each presented a paper on the conference\u2019s first day. Alumnus \u003Ca href=\u0022https:\/\/www.anl.gov\/profile\/srinivas-eswar\u0022\u003E\u003Cstrong\u003ESrinivas Eswar\u003C\/strong\u003E\u003C\/a\u003E (Ph.D. CS 2022) returned to Atlanta to share research from his current role at Argonne National Laboratory. Chow chaired the ML panel and a symposium on preconditioners for matrices.\u003C\/p\u003E\u003Cp\u003E\u201cIt was an engaging and rewarding experience meeting so many people from this very tight-knit community,\u201d said Shah, who studies computational science and engineering (CSE). \u201cGetting to see talks close to my research provided me with a lot of inspiration and direction for future work.\u201d\u003C\/p\u003E\u003Cp\u003EPrecond 2024 was the thirteenth meeting of the conference, which occurs every two years.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe conference returned to Atlanta this year for the first time since 2005. Atlanta joins Minneapolis as one of only two cities in the world to host Precond more than once. Precond 24 marked the sixth time the conference met in the U.S.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGeorgia Tech and Emory University\u2019s Department of Mathematics organized and sponsored Precond 24. The U.S. Department of Energy Office of Science co-sponsored the conference with Tech and Emory.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGeorgia Tech entities swarmed together in support of Precond 24. The Office of the Associate Vice President for Research Operations and Infrastructure, College of Computing, and School of CSE co-sponsored the conference.\u003C\/p\u003E\u003Cp\u003E\u201cThe enthusiasm at the conference has been very gratifying. So many people organized sessions at the conference and contributed to the very strong attendance,\u201d Chow said.\u0026nbsp;\u003Cbr\u003E\u003Cbr\u003E\u201cThis is a testament to the continued importance of preconditioning and related numerical methods in a rapidly changing technological world.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EFrom weather prediction to drug discovery, math powers the models used in computer simulations. To help these vital tools with their calculations, global experts recently met at Georgia Tech to share ways to make math easier for computers.\u003C\/p\u003E\u003Cp\u003ETech hosted the 2024 International Conference on Preconditioning Techniques for Scientific and Industrial Applications (\u003Ca href=\u0022https:\/\/www.math.emory.edu\/~yxi26\/Precond24\/index.html\u0022\u003E\u003Cstrong\u003EPrecond 24\u003C\/strong\u003E\u003C\/a\u003E), June 10-12.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EPreconditioning accelerates matrix computations, a kind of math used in most large-scale models. These computer models become faster, more efficient, and more accessible with help from preconditioned equations.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech hosted the 2024 International Conference on Preconditioning Techniques for Scientific and Industrial Applications (Precond 24), June 10-12. 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