{"688716":{"#nid":"688716","#data":{"type":"news","title":"New Research Priorities Chart Course Toward Impactful, Energy-Efficient Computing","body":[{"value":"\u003Cp\u003EGeorgia Tech researchers applied their expertise to a national research program that will shape the future of computing. Their work may yield more energy-efficient computers and better predictions for environmental challenges like carbon storage, tsunamis, wildfires, and sustainable energy.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe Department of Energy Office of Science recently released two reports through its Advanced Scientific Computing Research (\u003Ca href=\u0022https:\/\/www.energy.gov\/science\/ascr\/advanced-scientific-computing-research\u0022\u003EASCR\u003C\/a\u003E) program. The\u0026nbsp;\u003Ca href=\u0022https:\/\/science.osti.gov\/ascr\/Community-Resources\/Program-Documents\u0022\u003Ereports\u003C\/a\u003E were produced by workshops that brought together researchers from universities, national labs, government, and industry to set priorities for scientific computing.\u003C\/p\u003E\u003Cp\u003EProfessor\u0026nbsp;\u003Ca href=\u0022https:\/\/slim.gatech.edu\/people\/felix-j-herrmann\u0022\u003EFelix Herrmann\u003C\/a\u003E served on the organizing committee for the Workshop on Inverse Methods for Complex Systems under Uncertainty. Assistant Professor\u0026nbsp;\u003Ca href=\u0022https:\/\/faculty.cc.gatech.edu\/~pchen402\/group.html\u0022\u003EPeng Chen\u003C\/a\u003E joined Herrmann as a workshop participant, contributing expertise in data science and machine learning.\u003C\/p\u003E\u003Cp\u003EInverse methods work backward from outcomes to find their causes. Scientists use these tools to study complex systems, like designing new materials with targeted properties and using past wildfires to map vulnerable areas and behavior of future fires.\u003C\/p\u003E\u003Cp\u003EThe\u0026nbsp;\u003Ca href=\u0022https:\/\/www.osti.gov\/biblio\/2583339\u0022\u003EASCR report\u003C\/a\u003E highlighted Herrmann\u2019s work on seismic exploration and monitoring through digital twins. Founded on inverse methods, digital twins upgrade from static models to virtual systems that accurately mirror their physical counterparts.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDigital twins integrate real-time data sources, including fluid flows, monitoring and control systems, risk assessments, and human decisions. These models also account for uncertainty and address data gaps or limitations.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe DOE organized the workshop to support the growing role of inverse modeling. The group identified four priority research directions (PRDs) to guide future work. The PRDs are:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EPRD 1: Discovering, exploiting, and preserving structure\u003C\/li\u003E\u003Cli\u003EPRD 2: Identifying and overcoming model limitations\u003C\/li\u003E\u003Cli\u003EPRD 3: Integrating disparate multimodal and\/or dynamic data\u003C\/li\u003E\u003Cli\u003EPRD 4: Solving goal-oriented inverse problems for downstream tasks\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u201cA digital twin is a system you can control, like to optimize operations or to minimize risk,\u201d said Herrmann, who holds joint appointments in the Schools of Earth and Atmospheric Sciences, Electrical and Computer Engineering, and Computational Science and Engineering.\u003C\/p\u003E\u003Cp\u003E\u201cDigital twins give you a principled way to consider uncertainties, which there are a lot in subsurface monitoring. If you inject carbon dioxide too fast, you will will increase the pressure and may fracture the rock. If you inject too slow, then the process may become too costly. Digital twins help us make balanced decisions under uncertainty.\u201d\u003C\/p\u003E\u003Cp\u003ESupercomputers, algorithms, and artificial intelligence now power modern science. However, these tools consume enormous amounts of energy. This raises concerns about how to sustain computing and scientific research as we know them in the decades ahead.\u003C\/p\u003E\u003Cp\u003EProfessors\u0026nbsp;\u003Ca href=\u0022https:\/\/vuduc.org\/v2\/\u0022\u003ERich Vuduc\u003C\/a\u003E and\u0026nbsp;\u003Ca href=\u0022https:\/\/hyesoon.github.io\/\u0022\u003EHyesoon Kim\u003C\/a\u003E co-authored\u0026nbsp;\u003Ca href=\u0022https:\/\/www.osti.gov\/biblio\/2476961\u0022\u003Ethe report\u003C\/a\u003E from the Workshop on Energy-Efficient Computing for Science. At the three-day ASCR workshop, participants identified five key research directions:\u003C\/p\u003E\u003Cul\u003E\u003Cli\u003EPRD 1: Co-design energy-efficient hardware devices and architectures for important workloads\u003C\/li\u003E\u003Cli\u003EPRD 2: Define the algorithmic foundations of energy-efficient scientific computing\u003C\/li\u003E\u003Cli\u003EPRD 3: Reconceptualize software ecosystems for energy efficiency\u003C\/li\u003E\u003Cli\u003EPRD 4: Enable energy-efficient data management for data centers, instruments, and users\u003C\/li\u003E\u003Cli\u003EPRD 5: Develop integrated, scalable energy measurement and modeling capabilities for next-generation computing systems\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u201cI\u2019m cautiously optimistic about the future of energy-efficient computing. The ASCR report says, from a technological point of view, there are things we can do,\u201d said Vuduc.\u003C\/p\u003E\u003Cp\u003E\u201cThe report lays out paths for how we might design better apps, hardware systems, and algorithms that will use less energy. This is recognition that we should think about how architectures and software work together to drive down energy usage for systems.\u201d\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech researchers applied their expertise to a national research program that will shape the future of computing. Their work may yield more energy-efficient computers and better predictions for environmental challenges like carbon storage, tsunamis, wildfires, and sustainable energy.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe Department of Energy Office of Science recently released two reports through its Advanced Scientific Computing Research (\u003Ca href=\u0022https:\/\/www.energy.gov\/science\/ascr\/advanced-scientific-computing-research\u0022\u003EASCR\u003C\/a\u003E) program. The\u0026nbsp;\u003Ca href=\u0022https:\/\/science.osti.gov\/ascr\/Community-Resources\/Program-Documents\u0022\u003Ereports\u003C\/a\u003E were produced by workshops that brought together researchers from universities, national labs, government, and industry to set priorities for scientific computing.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech faculty members contributed to two DOE Advanced Scientific Computing Research program workshops. Recently published reports of their work may yield more energy-efficient computers and better predictions for environmental challenges."}],"uid":"36319","created_gmt":"2026-03-04 13:29:44","changed_gmt":"2026-03-04 21:01:18","author":"Bryant Wine","boilerplate_text":"","field_publication":"","field_article_url":"","location":"Atlanta, GA","dateline":{"date":"2026-02-27T00:00:00-05:00","iso_date":"2026-02-27T00:00:00-05:00","tz":"America\/New_York"},"extras":[],"hg_media":{"679513":{"id":"679513","type":"image","title":"ASCR-Report-Authors.png","body":null,"created":"1772630996","gmt_created":"2026-03-04 13:29:56","changed":"1772630996","gmt_changed":"2026-03-04 13:29:56","alt":"DOE Office of Science ASCR Reports","file":{"fid":"263685","name":"ASCR-Report-Authors.png","image_path":"\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Authors.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Authors.png","mime":"image\/png","size":578789,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/04\/ASCR-Report-Authors.png?itok=dQ53-joi"}},"679514":{"id":"679514","type":"image","title":"ASCR-Report-Inverse-methods.jpg","body":null,"created":"1772631052","gmt_created":"2026-03-04 13:30:52","changed":"1772631052","gmt_changed":"2026-03-04 13:30:52","alt":"ASCR Workshop on Inverse Methods for Complex Systems under Uncertainty","file":{"fid":"263686","name":"ASCR-Report-Inverse-methods.jpg","image_path":"\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Inverse-methods.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Inverse-methods.jpg","mime":"image\/jpeg","size":56325,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/04\/ASCR-Report-Inverse-methods.jpg?itok=rZGhJhnP"}},"679515":{"id":"679515","type":"image","title":"ASCR-Report-Energy-Efficient-Computing.jpg","body":null,"created":"1772631087","gmt_created":"2026-03-04 13:31:27","changed":"1772631087","gmt_changed":"2026-03-04 13:31:27","alt":"ASCR Workshop on Energy-Efficient Computing for Science","file":{"fid":"263687","name":"ASCR-Report-Energy-Efficient-Computing.jpg","image_path":"\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Energy-Efficient-Computing.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/03\/04\/ASCR-Report-Energy-Efficient-Computing.jpg","mime":"image\/jpeg","size":58857,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/03\/04\/ASCR-Report-Energy-Efficient-Computing.jpg?itok=-0arX_Rb"}}},"media_ids":["679513","679514","679515"],"related_links":[{"url":"https:\/\/www.cc.gatech.edu\/news\/new-research-priorities-chart-course-toward-impactful-energy-efficient-computing","title":"New Research Priorities Chart Course Toward Impactful, Energy-Efficient Computing"}],"groups":[{"id":"1188","name":"Research Horizons"}],"categories":[{"id":"194606","name":"Artificial Intelligence"},{"id":"153","name":"Computer Science\/Information Technology and Security"},{"id":"144","name":"Energy"},{"id":"154","name":"Environment"},{"id":"150","name":"Physics and Physical Sciences"},{"id":"135","name":"Research"}],"keywords":[{"id":"654","name":"College of Computing"},{"id":"166983","name":"School of Computational Science and Engineering"},{"id":"9153","name":"Research Horizons"},{"id":"187915","name":"go-researchnews"},{"id":"10199","name":"Daily Digest"},{"id":"181991","name":"Georgia Tech News Center"},{"id":"663","name":"Department of Energy"},{"id":"179230","name":"digital twin"},{"id":"15030","name":"high-performance computing"},{"id":"9167","name":"machine learning"},{"id":"187812","name":"artificial intelligence (AI)"}],"core_research_areas":[{"id":"193655","name":"Artificial Intelligence at Georgia Tech"},{"id":"39431","name":"Data Engineering and Science"},{"id":"39531","name":"Energy and Sustainable Infrastructure"}],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003EBryant Wine, Communications Officer\u003Cbr\u003E\u003Ca href=\u0022mailto:bryant.wine@cc.gatech.edu\u0022\u003Ebryant.wine@cc.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}