Publications by MPCDF

Journal Article (10)

Journal Article
Kirsebom, O. S.; Jones, S.; Strömberg, D. F.; Martínez-Pinedo, G.; Langanke, K.; Röpke, F. K.; Brown, B. A.; Eronen, T.; Fynbo, H. O. U.; Hukkanen, M. et al.; Idini, A.; Jokinen, A.; Kankainen, A.; Kostensalo, J.; Moore, I.; Möller, H.; Ohlmann, S. T.; Penttilä, H.; Riisager, K.; Rinta-Antila, S.; Srivastava, P. C.; Suhonen, J.; Trzaska, W. H.; Äystö, J.: Discovery of an Exceptionally Strong β-Decay Transition of 20F and Implications for the Fate of Intermediate-Mass Stars. Physical Review Letters 123 (26), 262701 (2019)
Journal Article
Victor, A.; Kormann, K.; Rampp, M.; Reuter, K.: Evaluation of performance portability frameworks for the implementation of a particle-in-cell code. Concurrency and Computing: Practice and Experience, e5640 (2019)
Journal Article
Deák, P.; Khorasani, E.; Lorke, M.; Meisam, F. T.; Aradi, B.; Frauenheim, T.: Defect calculations with hybrid functionals in layered compounds and in slab models. Physical Review B 100 (23), 235304 (2019)
Journal Article
Schneider, F. R. N.; Ohlmann, S. T.; Podsiadlowski, P.; Röpke, F. K.; Balbus, S. A.; Springel, V.; Pakmor , R.: Stellar mergers as the origin of magnetic massive stars. Nature 574 (7777), pp. 211 - 222 (2019)
Journal Article
Kus, P.; Marek, A.; Koecher, S. S.; Kowalski, H.-H.; Carbogno, C.; Scheurer, C.; Reuter, K.; Scheffler, M.; Lederer, H.: Optimizations of the eigensolvers in the ELPA library. Parallel Computing 85, pp. 167 - 177 (2019)
Journal Article
Goicovic, F. G.; Springel, V.; Ohlmann, S. T.; Pakmor, R.: Hydrodynamical moving-mesh simulations of the tidal disruption of stars by supermassive black holes. Monthly Notices of the Royal Astronomical Society 487 (1), pp. 981 - 992 (2019)
Journal Article
Köfinger, J.; Stelzl, L. S.; Reuter, K.; Allande, C.; Reichel, K.; Hummer*, G.: Efficient Ensemble Refinement by Reweighting. Journal of Chemical Theory and Computation 15 (5), pp. 3390 - 3409 (2019)
Journal Article
Kormann, K.; Reuter, K.; Rampp, M.: A massively parallel semi-Lagrangian solver for the six-dimensional Vlasov–Poisson equation. The International Journal of High Performance Computing Applications 33 (5), pp. 924 - 947 (2019)
Journal Article
Bramas, B.: Increasing the degree of parallelism using speculative execution in task-based runtime systems. PeerJ Computer Science 5, e183 (2019)
Journal Article
Jones, S.; Röpke, F. K.; Fryer, C.; Ruiter, A. J.; Seitenzahl, I. R.; Nittler, L. R.; Ohlmann, S. T.; Reifarth, R.; Pignatari, M.; Belczynski, K.: Remnants and ejecta of thermonuclear electron-capture supernovae - Constraining oxygen-neon deflagrations in high-density white dwarfs. Astronomy and Astrophysics 622, A74 (2019)

Proceedings (1)

Implementing FAIR Data Infrastructures (Dagstuhl Reports, 8). Dagstuhl Perspectives Workshop 18472: "Implementing FAIR Data Infrastructures", Dagstuhl, Germany, November 18, 2018 - November 21, 2018. Schloss Dagstuhl, Wadern (2019)

Conference Paper (1)

Conference Paper
Fischer, R.; Bock, A.; Burckhart, A.; Reisner, M.; Stober, J.; Ford, O.; Giannone, L.; Gude, A.; Rampp, M.; Weiland, M. et al.; Willensdorfer, M.; the ASDEX Upgrade Team: Current profile tailoring with the upgraded ECRH system at ASDEX Upgrade. In: 46th EPS Conference on Plasma Physics, P1.1100 (Eds. Riconda, C.; Brezinsek, S.; McCarty, K.; Lancaster, K.; Burgess, D. et al.). 46th EPS Conference on Plasma Physics, Milan, July 08, 2019 - July 12, 2019. European Physical Society, Geneva (2019)

Talk (6)

Christof, H.: From icinga1 to icinga2 + director. A declarative approach. Icinga Camp 2019, Zürich, Schweiz (2019)
Lederer, H.: ELPA eigensolvers: autotunable, energy-efficient, optimized. 9. HPC-Konferenz der Gauss-Allianz, Paderborn, Germany (2019)
Panea-Doblado, M.: Copying 100 million files. HPSS User Forum, Bloomington, USA (2019)
Rampp, M.: Trends in high performance computing technology from the perspective of application development. CECAM Extended Software Development Workshop: Scaling Electronic Structure Applications, Dublin, Ireland (2019)
Rampp, M.; Marek, A.: High-performance Data Analytics - Basic concepts of distributed deep learning. Big Data Summer: A summer school of the BiGmax Network, Platja d’Aro, Spain (2019)
Rampp, M.; Marek, A.: High-performance Data Analytics at the MPCDF. DV-Treffen der Max-Planck-Institute, Göttingen, Germany (2019)

Poster (1)

Ritz, R.; Beck, K.; Zastrow, T.: German node of the Research Data Alliance (RDA). BigMax Workshop 2018 on Big-Data-Driven Materials Science, Espoo, Finnland (2019)

Working Paper (2)

Working Paper
Reuter, K.; Stanisic, L.: MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis. (submitted)
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