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Research overview	Using Advanced MPI	Edited volumes

2019

ML4PS'19	[1] Peter Grönquist, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Luca Lavarini, Shigang Li, Torsten Hoefler:
		Predicting Weather Uncertainty with Deep Convnets In Machine Learning and the Physical Sciences Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS), presented in Vancouver, BC, Canada, Dec. 2019,

SC19	[2] Cedric Renggli, Dan Alistarh, Mehdi Aghagolzadeh, Torsten Hoefler:
		SparCML: High-Performance Sparse Communication for Machine Learning In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[3] Tiziano De Matteis, Johannes de Fine Licht, Jakub Beránek, Torsten Hoefler:
		Streaming Message Interface: High-Performance DistributedMemory Programming on Reconfigurable Hardware In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[4] Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler:
		Optimizing the Data Movement in Quantum Transport Simulations via Data-Centric Parallel Programming In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[5] Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler:
		A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, Gordon Bell Prize finalist

SC19	[6] Salvatore Di Girolamo, Konstantin Taranov, Andreas Kurth, Michael Schaffner, Timo Schneider, Jakub Beránek, Maciej Besta, Luca Benini, Duncan Roweth, Torsten Hoefler:
		Network-Accelerated Non-Contiguous Memory Transfers In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[7] Daniele De Sensi, Salvatore Di Girolamo, Torsten Hoefler:
		Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[8] Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler:
		Stateful Dataflow Multigraphs: A Data-Centric Model for Performance Portability on Heterogeneous Architectures In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344))

SC19	[9] Maciej Besta, Simon Weber, Lukas Gianinazzi, Robert Gerstenberger, Andrey Ivanov, Yishai Oltchik, Torsten Hoefler:
		Slim Graph: Practical Lossy Graph Compression for Approximate Graph Processing, Storage, and Analytics In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344)) Best Paper Finalist, Best Student Paper Finalist

SC19	[10] Grzegorz Kwasniewski and Marko Kabić and Maciej Besta and Joost VandeVondele and Raffaele Solcà and Torsten Hoefler:
		Red-Blue Pebbling Revisited: Near Optimal Parallel Matrix-Matrix Multiplication In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19), Nov. 2019, (acceptance rate: 22.7% (78/344)) Best Paper Finalist, Best Student Paper Finalist

PACT'19	[11] Tobias Gysi, Tobias Grosser, Torsten Hoefler:
		Absinthe: Learning an Analytical Performance Model to Fuse and Tile Stencil Codes in One Shot In Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques (PACT), presented in Seattle, WA, USA, IEEE, Sep. 2019,

ACM CSUR	[12] Tal Ben-Nun, Torsten Hoefler:
		Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Comput. Surv.. Vol 52, Nr. 4, pages 65:1--65:43, ACM, ISSN: 0360-0300, Aug. 2019,

IEEE TPDS	[13] Sergei Shudler, Yannick Berens, Alexandru Calotoiu, Torsten Hoefler, Alexandre Strube, Felix Wolf:
		Engineering Algorithms for Scalability through Continuous Validation of Performance Expectations IEEE Transactions on Parallel and Distributed Systems (TPDS). Vol 30, Nr. 8, IEEE, Jul. 2019,

arXiv	[14] Tiziano De Matteis and Johannes de Fine Licht and Torsten Hoefler:
		FBLAS: Streaming Linear Algebra on FPGA CoRR. Vol abs/1907.07929, Jul. 2019,

PASC'19	[15] Felix Thaler, Stefan Moosbrugger, Carlos Osuna, Mauro Bianco, Hannes Vogt, Anton Afanasyev, Lukas Mosimann, Oliver Fuhrer, Thomas Schulthess, Torsten Hoefler:
		Porting the COSMO Weather Model to Intel KNL presented in Zurich, Switzerland, ACM, Jun. 2019, Accepted at the ACM Platform for Advanced Scientific Computing Conference (PASC19)

DAC'19	[16] Niels Gleinig and Frances Ann Hubis and Torsten Hoefler:
		Embedding Functions Into Reversible Circuits: A Probabilistic Approach to the Number of Lines In Proceedings of the 56th Annual Design Automation Conference, presented in Las Vegas, NV, USA, ACM, ISBN: 978-1-4503-6725-7/19/06, Jun. 2019,

PLDI'19	[17] Tobias Gysi, Tobias Grosser, L. Brandner, Torsten Hoefler:
		A Fast Analytical Model of Fully Associative Caches In Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, presented in Phoenix, AZ, USA, pages 816--829, ACM, ISBN: 978-1-4503-6712-7, Jun. 2019,

ICS'19	[18] Paul R. Eller, Torsten Hoefler, William Gropp:
		Using Performance Models to Understand Scalable Krylov Solver Performance at Scale for Structured Grid Problems In Proceedings of the 2019 ACM International Conference on Supercomputing (ICS'19), presented in Phoenix, AZ, ACM, Jun. 2019,

IPDPS'19	[19] Salvatore Di Girolamo, P. Schmid, Thomas Schulthess, Torsten Hoefler:
		SimFS: A Simulation Data Virtualizing File System Interface In Proceedings of the 33st IEEE International Parallel & Distributed Processing Symposium (IPDPS'19), presented in Rio de Janeiro, Brazil, IEEE, May 2019,

IPDPS'19	[20] Tal Ben-Nun, Maciej Besta, S. Huber, Alexandros Nikolaos Ziogas, D. Peter, Torsten Hoefler:
		A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning IEEE, May 2019, Accepted at the 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS'19)

PPoPP'19	[21] Martin Kuettler, Maksym Planeta, Jan Bierbaum, Carsten Weinhold, Hermann Haertig, Amnon Barak, Torsten Hoefler:
		Corrected Trees for Reliable Group Communication Feb. 2019, Accepted at The ACM Conference Principles and Practice of Parallel Programming 2019 (PPoPP'19) (acceptance rate: 19% (29/152))

FPGA'19	[22] Maciej Besta, Marc Fischer, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler:
		Substream-Centric Maximum Matchings on FPGA Feb. 2019, In Proceedings of the 27th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (acceptance rate: 23%) Best Paper Finalist (4/30)

arXiv	[23] Maciej Besta, Dimitri Stanojevic, Johannes de Fine Licht, Tal Ben-Nun, Torsten Hoefler:
		Graph Processing on FPGAs: Taxonomy, Survey, Challenges CoRR. Vol abs/1903.06697, Feb. 2019,

CiSE	[24] Thomas Schulthess, P. Bauer, Oliver Fuhrer, Torsten Hoefler, C. Schaer, N. Wedi:
		Reflecting on the goal and baseline for exascale computing: a roadmap based on weather and climate simulations Computing in Science and Engineering (CiSE). Vol 21, Nr. 1, IEEE Computer Society, ISSN: 1521-9615, Jan. 2019,

MLHPC	[25] Torsten Hoefler:
		HPC for ML and ML for HPC - Scalability, Communication, and Programming (Presentation) presented in Denver, CO, USA, Nov. 2019, Keynote talk at the International Machine Learning in High-Performance Computing (MLHPC'19 in conjunction with ACM/IEEE Supercomputing, SC19)

PARCO	[26] Torsten Hoefler:
		Data-Centric Parallel Programming (Presentation) presented in Prague, Czech Republic, Sep. 2019, Keynote talk at the The 18th International Parallel Computing conference (ParCo'19)

PPAM	[27] Torsten Hoefler:
		High-Performance Communication in Machine Learning (Presentation) presented in Bialystok, Poland, Sep. 2019, Keynote talk at the 13th International Conference on Parallel Processing and Applied Mathematics (PPAM'19)

ISC'19	[28] Torsten Hoefler, Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier and Johannes de Fine Licht:
		Data-Centric Parallel Programming (Presentation) presented in Frankfurt, Germany, Jun. 2019, invited talk at the International Conference on Supercomputing (ISC'19)

GG500	[29] Torsten Hoefler:
		The Green Graph500 List (June 2019) (Presentation) presented in Frankfurt, Germany, Jun. 2019, Presented at the Green Graph 500 BoF at the International Conference on Supercomputing (ISC'19)

ISC'19 ML	[30] Torsten Hoefler, Tal Ben-Nun:
		Optimizing and Benchmarking Large-Scale Deep Learning (Presentation) presented in Frankfurt, Germany, Jun. 2019, Invited talk at the Machine Learning day at the International Conference on Supercomputing (ISC'19)

NRE'19	[31] Torsten Hoefler:
		Performance Reproducibility in HPC and Deep Learning (Presentation) presented in Frankfurt, Germany, Jun. 2019, Keynote talk at the Numerical Reproducibility at Exascale Workshop (NRE2019), ISC’19

AsHES	[32] Torsten Hoefler:
		Performance Portability with Data-Centric Parallel Programming (Presentation) presented in Rio de Janeiro, Brasil, May 2019, Keynote talk at the The Ninth International Workshop on Accelerators and Hybrid Exascale Systems (AsHES) (delayed online)

HPCAC	[33] Torsten Hoefler:
		RDMA, Scalable MPI-3 RMA, and Next-Generation Post-RDMA Interconnects (Presentation) Apr. 2019, Best talk award winner at Swiss HPC Advisory Council Conference 2019

EMiT	[34] Torsten Hoefler:
		High-Performance Communication for Machine Learning (Presentation) presented in Huddersfield, UK, Apr. 2019, Keynote talk at the 5th Conference on Emerging Technologies – EMiT2019

SCFE'19	[35] Torsten Hoefler:
		Extreme-Scale Graphs (Presentation) presented in Warsaw, Poland, Mar. 2019, Invited talk at Supercomputing Frontiers Europe 2019

AHPC'19	[36] Torsten Hoefler:
		High-Performance Communication in Machine Learning (Presentation) presented in Grundlsee, Austria, Feb. 2019, Keynote at the Austrian HPC meeting 2019

ICL	[37] Torsten Hoefler:
		High-Performance Communication in Machine Learning (Presentation) presented in Knowville, TN, Feb. 2019,

RWTH Aachen	[38] Torsten Hoefler:
		High-Performance Communication for Machine Learning (Presentation) presented in Aachen, Germany, Jan. 2019,

RWTH Aachen	[39] Torsten Hoefler:
		MPI Remote Memory Access Programming and Scientific Benchmarking of Parallel Codes (Presentation) presented in Aachen, Germany, Jan. 2019,

TU Darmstadt	[40] Torsten Hoefler:
		An HPC Systems Guy’s View of Quantum Computing (Presentation) presented in Darstadt, Germany, Jan. 2019,

H2RC'19	[41] Johannes de Fine Licht, Torsten Hoefler:
		hlslib: Software Engineering for Hardware Design In Fifth International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC'19), presented in Denver, CO, United States, IEEE, Nov. 2019,

MB3	[42] Alexandr Nigay, Timo Schneider, Torsten Hoefler:
		TinyMPI tasking prototype Feb. 2019,