001041786 001__ 1041786
001041786 005__ 20250512202214.0
001041786 0247_ $$2datacite_doi$$a10.34734/FZJ-2025-02426
001041786 037__ $$aFZJ-2025-02426
001041786 041__ $$aEnglish
001041786 1001_ $$0P:(DE-Juel1)144723$$aDi Napoli, Edoardo$$b0$$ufzj
001041786 1112_ $$aISC High Performance 2024$$cHamburg$$d2024-05-12 - 2024-05-16$$gISC24$$wGermany
001041786 245__ $$aLearning Materials at eXascale
001041786 260__ $$c2024
001041786 3367_ $$033$$2EndNote$$aConference Paper
001041786 3367_ $$2BibTeX$$aINPROCEEDINGS
001041786 3367_ $$2DRIVER$$aconferenceObject
001041786 3367_ $$2ORCID$$aCONFERENCE_POSTER
001041786 3367_ $$2DataCite$$aOutput Types/Conference Poster
001041786 3367_ $$0PUB:(DE-HGF)24$$2PUB:(DE-HGF)$$aPoster$$bposter$$mposter$$s1747025026_12849$$xAfter Call
001041786 520__ $$aSolving large and sparse numerical linear systems in materials science on massively parallel supercomputers is a complex endeavour that requires a delicate balance between accuracy and computational efficiency. Challenges include managing the scale and complexity of these systems, optimising scalability on parallel architectures, and addressing real-world material complexities. The LimitX project represents a ground-breaking step in the field of computational Materials Science and aims to develop an innovative recommender system. This system aims to revolutionise the solution of large-scale sparse linear systems by accelerating and scaling the solutions of linear systems so that materials science research can be routinely performed on exascale clusters. At its core, this system relies on a two-pronged approach: first, the development of a spectral predictor system and, second, the use of an extensive database of matrices that encapsulate the essence of surrogate space in the field of materials science. The spectral predictor system is the heart of the recommendation system. It utilises deep learning techniques to predict spectral properties that are crucial for the efficient solution of linear systems. The extensive matrix dataset captures the diversity of spectral patterns that occur in material science calculations. The application of this recommender system promises to be transformative, as it enables simulations with hundreds of thousands of atoms, a feat previously unrealisable on current pre-exascale clusters. The linear scaling of DFT (density functional theory) codes such as BigDFT will enable researchers to simulate and analyse complex material systems with unprecedented accuracy and computational efficiency, opening up new horizons for scientific exploration in this field.Item Type:
001041786 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001041786 536__ $$0G:(DE-Juel1)SDLQM$$aSimulation and Data Laboratory Quantum Materials (SDLQM) (SDLQM)$$cSDLQM$$fSimulation and Data Laboratory Quantum Materials (SDLQM)$$x1
001041786 536__ $$0G:(EU-Grant)101118139$$aInno4Scale - Innovative Algorithms for Applications on European Exascale Supercomputers (101118139)$$c101118139$$fHORIZON-EUROHPC-JU-2022-ALG-02$$x2
001041786 7001_ $$0P:(DE-HGF)0$$aDavidovic, Davor$$b1$$eCorresponding author
001041786 7001_ $$0P:(DE-HGF)0$$aGenovese, Luigi$$b2
001041786 8564_ $$uhttp://fulir.irb.hr/id/eprint/8922
001041786 8564_ $$uhttps://juser.fz-juelich.de/record/1041786/files/Limit%20x%20poster%20V3%20Final.pdf$$yOpenAccess
001041786 909CO $$ooai:juser.fz-juelich.de:1041786$$popenaire$$popen_access$$pVDB$$pdriver$$pec_fundedresources
001041786 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144723$$aForschungszentrum Jülich$$b0$$kFZJ
001041786 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001041786 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
001041786 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001041786 980__ $$aposter
001041786 980__ $$aVDB
001041786 980__ $$aUNRESTRICTED
001041786 980__ $$aI:(DE-Juel1)JSC-20090406
001041786 9801_ $$aFullTexts