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Improving Operational Intensity in Data Bound Markov Chain Monte Carlo.

, , , and . ICCS, volume 108 of Procedia Computer Science, page 2348-2352. Elsevier, (2017)

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Hiding Global Communication Latency in the GMRES Algorithm on Massively Parallel Machines., , , and . SIAM J. Sci. Comput., (2013)The Impact of Global Communication Latency at Extreme Scales on Krylov Methods., , , and . ICA3PP (1), volume 7439 of Lecture Notes in Computer Science, page 428-442. Springer, (2012)Guidelines for enhancing data locality in selected machine learning algorithms., , and . CoRR, (2020)MPA: Parallelizing an Application onto a Multicore Platform Made Easy., , , , , and . IEEE Micro, 29 (3): 31-39 (2009)Exploring parallelizations of applications for MPSoC platforms using MPA., , , and . DATE, page 1148-1153. IEEE, (2009)SMURFF: a High-Performance Framework for Matrix Factorization., , and . AICAS, page 304-308. IEEE, (2019)Industry-scale application and evaluation of deep learning for drug target prediction., , , , , , , , , and 9 other author(s). J. Cheminformatics, 12 (1): 26 (2020)HyperLoom: A Platform for Defining and Executing Scientific Pipelines in Distributed Environments., , , , , , , and . PARMA-DITAM@HiPEAC, page 1-6. ACM, (2018)Coxeter Lattice Paths., , and . Challenges in Symbolic Computation Software, volume 06271 of Dagstuhl Seminar Proceedings, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany, (2006)ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics., , , , , , , , , and 2 other author(s). BNAIC/BENELEARN, volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)