Hans Pabst

22 papers A 5C 3Journal 10Unranked 4
YearRankTypeTitle / Venue / Authors
2024 A conf
Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures.
IPDPS
Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Abhisek Kundu, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke
2024 J jnl
Towards a high-performance AI compiler with upstream MLIR.
CoRR
Renato Golin, Lorenzo Chelini, Adam Siemieniuk, Kavitha Madhu, Niranjan Hasabnis, Hans Pabst, Evangelos Georganas, Alexander Heinecke
2023 J jnl
Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures.
CoRR
Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke
2022 J jnl
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads.
Frontiers Appl. Math. Stat.
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
2022 J jnl
Towards electronic structure-based
Parallel Comput.
Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl
2021 J jnl
Enabling Electronic Structure-Based Ab-Initio Molecular Dynamics Simulations with Hundreds of Millions of Atoms.
CoRR
Robert Schade, Tobias Kenter, Hossam Elgabarty, Michael Lass, Ole Schütt, Alfio Lazzaro, Hans Pabst, Stephan Mohr, Jürg Hutter, Thomas D. Kühne, Christian Plessl
2021 C conf
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case.
ICPRAM
Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker
2021 J jnl
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case.
CoRR
Florian Rehm, Sofia Vallecorsa, Vikram A. Saletore, Hans Pabst, Adel Chaibi, Valeriu Codreanu, Kerstin Borras, Dirk Krücker
2021 J jnl
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads.
CoRR
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
2021 A conf
Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads.
SC
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
2020 A conf
Harnessing Deep Learning via a Single Building Block.
IPDPS
Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
2019 J jnl
High-Performance Deep Learning via a Single Building Block.
CoRR
Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
2018 J jnl
Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures.
CoRR
Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke
2018 A conf
Anatomy of high-performance deep learning convolutions on SIMD architectures.
SC
Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke
2018 — conf
Distributed Training of Generative Adversarial Networks for Fast Detector Simulation.
ISC Workshops
Sofia Vallecorsa, Federico Carminati, Gulrukh Khattak, Damian Podareanu, Valeriu Codreanu, Vikram A. Saletore, Hans Pabst
2017 — conf
Porting of the DBCSR Library for Sparse Matrix-Matrix Multiplications to Intel Xeon Phi Systems.
PARCO
Iain Bethune, Andreas Glöss, Jürg Hutter, Alfio Lazzaro, Hans Pabst, Fiona Reid
2017 J jnl
Porting of the DBCSR library for Sparse Matrix-Matrix Multiplications to Intel Xeon Phi systems.
CoRR
Iain Bethune, Andreas Glöss, Jürg Hutter, Alfio Lazzaro, Hans Pabst, Fiona Reid
2016 C conf
Efficiency of High Order Spectral Element Methods on Petascale Architectures.
ISC
Maxwell Hutchinson, Alexander Heinecke, Hans Pabst, Greg Henry, Matteo Parsani, David E. Keyes
2016 A conf
LIBXSMM: accelerating small matrix multiplications by runtime code generation.
SC
Alexander Heinecke, Greg Henry, Maxwell Hutchinson, Hans Pabst
2012 C conf
Performance of a Structure-Detecting SpMV Using the CSR Matrix Representation.
ISPDC
Hans Pabst, Bev Bachmayer, Michael Klemm
2011 — conf
Towards High-Performance Implementations of a Custom HPC Kernel Using ® Array Building Blocks.
Facing the Multicore-Challenge
Alexander Heinecke, Michael Klemm, Hans Pabst, Dirk Pflüger
2010 — conf
Multigrid optical flow for deformable medical volume registration.
SIGGRAPH Talks
Ariel Bernal, Ashok Thirumurthi, Hans Pabst, Tyler Nowicki, Michael McCool