Hans Pabst

According to our database, Hans Pabst authored at least 18 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures.

Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke

CoRR, 2023

2022

Towards electronic structure-based <i>ab-initio</i> molecular dynamics simulations with hundreds of millions of atoms.

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl

Parallel Comput., 2022

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Deepti Aggarwal, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Brian Retford, Barukh Ziv, Alexander Heinecke

Frontiers Appl. Math. Stat., 2022

2021

Enabling Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.

Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl

CoRR, 2021

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

CoRR, 2021

Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 2021

Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case.

Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker

Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

2020

Harnessing Deep Learning via a Single Building Block.

Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

2019

High-Performance Deep Learning via a Single Building Block.

Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

CoRR, 2019

2018

Machine Learning in High Energy Physics Community White Paper.

Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir V. Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark S. Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Chatham Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata

CoRR, 2018

Distributed Training of Generative Adversarial Networks for Fast Detector Simulation.

Sofia Vallecorsa, Federico Carminati, Gulrukh Khattak, Damian Podareanu, Valeriu Codreanu, Vikram A. Saletore, Hans Pabst

Proceedings of the High Performance Computing, 2018

Anatomy of high-performance deep learning convolutions on SIMD architectures.

Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 2018

2017

Porting of the DBCSR Library for Sparse Matrix-Matrix Multiplications to Intel Xeon Phi Systems.

Iain Bethune, Andreas Glöss, Jürg Hutter, Alfio Lazzaro, Hans Pabst, Fiona Reid

Proceedings of the Parallel Computing is Everywhere, 2017

2016

Efficiency of High Order Spectral Element Methods on Petascale Architectures.

Maxwell Hutchinson, Alexander Heinecke, Hans Pabst, Greg Henry, Matteo Parsani, David E. Keyes

Proceedings of the High Performance Computing - 31st International Conference, 2016

LIBXSMM: accelerating small matrix multiplications by runtime code generation.

Alexander Heinecke, Greg Henry, Maxwell Hutchinson, Hans Pabst

Proceedings of the International Conference for High Performance Computing, 2016

2012

Performance of a Structure-Detecting SpMV Using the CSR Matrix Representation.

Hans Pabst, Bev Bachmayer, Michael Klemm

Proceedings of the 11th International Symposium on Parallel and Distributed Computing, 2012

2011

Towards High-Performance Implementations of a Custom HPC Kernel Using ® Array Building Blocks.

Alexander Heinecke, Michael Klemm, Hans Pabst, Dirk Pflüger

Proceedings of the Facing the Multicore - Challenge II, 2011

2010

Multigrid optical flow for deformable medical volume registration.

Ariel Bernal, Ashok Thirumurthi, Hans Pabst, Tyler Nowicki, Michael McCool

Proceedings of the International Conference on Computer Graphics and Interactive Techniques, 2010