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Exploiting In-Memory Processing Capabilities for Density Functional Theory Applications.

, , , , , and . Euro-Par Workshops, volume 10104 of Lecture Notes in Computer Science, page 750-762. Springer, (2016)

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Apl. Prof. Dr. -Ing. Niels Hansen University of Stuttgart

Generalized DeepONets for Viscosity Prediction Using Learned Entropy Scaling References, , , , and . Dataset, (2025)Related to: Fleck M, Klenk T, Darouich S, Spera MBM, Hansen N. A Generalized Deep Entropy Scaling Architecture Framework to Predict Viscosities. ChemRxiv. 2025; doi: This content is a preprint and has not been peer-reviewed. doi: 10.26434/chemrxiv-2025-jrjj9.
 

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QPACE - a QCD parallel computer based on Cell processors., , , , , , , , , and 25 other author(s). CoRR, (2009)Characterizing Performance of Applications on Blue Gene/Q., , , , , , , and . PARCO, volume 25 of Advances in Parallel Computing, page 113-122. IOS Press, (2013)Early experiences with scientific applications on the IBM Blue Gene/Q supercomputer., , , , , , , , , and 4 other author(s). IBM Journal of Research and Development, 57 (1/2): 14 (2013)QPACE: power-efficient parallel architecture based on IBM PowerXCell 8i., , , , , , , , , and . Comput. Sci. Res. Dev., 25 (3-4): 149-154 (2010)QPACE: Energy-Efficient High Performance Computing., , and . ARCS Workshops, page 103-112. VDE Verlag, (2010)Accelerating LBM and LQCD Application Kernels by In-Memory Processing., , , , , , and . ISC, volume 9137 of Lecture Notes in Computer Science, page 96-112. Springer, (2015)Exploiting In-Memory Processing Capabilities for Density Functional Theory Applications., , , , , and . Euro-Par Workshops, volume 10104 of Lecture Notes in Computer Science, page 750-762. Springer, (2016)