Alexander Heinecke

According to our database, Alexander Heinecke authored at least 70 papers between 2007 and 2023.

Collaborative distances:

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

2023

Microscaling Data Formats for Deep Learning.

Bita Darvish Rouhani, Ritchie Zhao, Ankit More, Mathew Hall, Alireza Khodamoradi, Summer Deng, Dhruv Choudhary, Marius Cornea, Eric Dellinger, Kristof Denolf, Dusan Stosic, Venmugil Elango, Maximilian Golub, Alexander Heinecke, Phil James-Roxby, Dharmesh Jani, Gaurav Kolhe, Martin Langhammer, Ada Li, Levi Melnick, Maral Mesmakhosroshahi, Andres Rodriguez, Michael Schulte, Rasoul Shafipour, Lei Shao, Michael Y. Siu, Pradeep Dubey, Paulius Micikevicius, Maxim Naumov, Colin Verilli, Ralph Wittig, Doug Burger, Eric S. Chung

CoRR, 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

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

FP8 Formats for Deep Learning.

Paulius Micikevicius, Dusan Stosic, Neil Burgess, Marius Cornea, Pradeep Dubey, Richard Grisenthwaite, Sangwon Ha, Alexander Heinecke, Patrick Judd, John Kamalu, Naveen Mellempudi, Stuart F. Oberman, Mohammad Shoeybi, Michael Y. Siu, Hao Wu

CoRR, 2022

FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems.

Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi

CoRR, 2022

FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems.

Rui Ma, Evangelos Georganas, Alexander Heinecke, Sergey Gribok, Andrew Boutros, Eriko Nurvitadhi

IEEE Comput. Archit. Lett., 2022

Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data.

Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Next-Generation Local Time Stepping for the ADER-DG Finite Element Method.

Alexander Breuer, Alexander Heinecke

Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

2021

PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives.

Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Bharat Kaul, Gagandeep Goyal, Ramakrishna Upadrasta

ACM Trans. Archit. Code Optim., 2021

Efficient and Generic 1D Dilated Convolution Layer for Deep Learning.

Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

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

DistGNN: scalable distributed training for large-scale graph neural networks.

Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha

Proceedings of the International Conference for High Performance Computing, 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

2020

PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives.

Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul

CoRR, 2020

Performance study of sustained petascale direct numerical simulation on Cray XC40 systems.

Bilel Hadri, Matteo Parsani, Maxwell Hutchinson, Alexander Heinecke, Lisandro Dalcín, David E. Keyes

Concurr. Comput. Pract. Exp., 2020

Optimizing deep learning recommender systems training on CPU cluster architectures.

Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 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

Optimizing Deep Learning RNN Topologies on Intel Architecture.

Kunal Banerjee, Evangelos Georganas, Dhiraj D. Kalamkar, Barukh Ziv, Eden Segal, Cristina Anderson, Alexander Heinecke

Supercomput. Front. Innov., 2019

Tensor-optimized hardware accelerates fused discontinuous Galerkin simulations.

Alexander Heinecke, Alexander Breuer, Yifeng Cui

Parallel Comput., 2019

Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F).

Amelia Drew, Alexander Heinecke

CoRR, 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

A Study of BFLOAT16 for Deep Learning Training.

Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey

CoRR, 2019

Petaflop Seismic Simulations in the Public Cloud.

Alexander Breuer, Yifeng Cui, Alexander Heinecke

Proceedings of the High Performance Computing - 34th International Conference, 2019

Training Google Neural Machine Translation on an Intel CPU Cluster.

Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

ISA mapper: a compute and hardware agnostic deep learning compiler.

Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight

Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019

Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations.

Greg Henry, Ping Tak Peter Tang, Alexander Heinecke

Proceedings of the 26th IEEE Symposium on Computer Arithmetic, 2019

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

Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor.

Josh Tobin, Alexander Breuer, Alexander Heinecke, Charles Yount, Yifeng Cui

Proceedings of the High Performance Computing - 32nd International Conference, 2017

EDGE: Extreme Scale Fused Seismic Simulations with the Discontinuous Galerkin Method.

Alexander Breuer, Alexander Heinecke, Yifeng Cui

Proceedings of the High Performance Computing - 32nd International Conference, 2017

2016

Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors.

Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Md. Mostofa Ali Patwary, Vadim O. Pirogov, Pradeep Dubey, Xing Liu, Carlos Rosales, Cyril Mazauric, Christopher S. Daley

Int. J. High Perform. Comput. Appl., 2016

Data mining on vast data sets as a cluster system benchmark.

Alexander Heinecke, Roman Karlstetter, Dirk Pflüger, Hans-Joachim Bungartz

Concurr. Comput. Pract. Exp., 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

High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing).

Alexander Heinecke, Alexander Breuer, Michael Bader, Pradeep Dubey

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

Petascale Local Time Stepping for the ADER-DG Finite Element Method.

Alexander Breuer, Alexander Heinecke, Michael Bader

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

2015

Supercomputing for Molecular Dynamics Simulations - Handling Multi-Trillion Particles in Nanofluidics

Alexander Heinecke, Wolfgang Eckhardt, Martin Horsch, Hans-Joachim Bungartz

Springer Briefs in Computer Science, Springer, ISBN: 978-3-319-17148-7, 2015

Beacon: Deployment and Application of Intel Xeon Phi Coprocessorsfor Scientific Computing.

R. Glenn Brook, Alexander Heinecke, Anthony B. Costa, Paul Peltz Jr., Vincent C. Betro, Troy Baer, Michael Bader, Pradeep Dubey

Comput. Sci. Eng., 2015

Cache-oblivious matrix algorithms in the age of multicores and many cores.

Alexander Heinecke, Carsten Trinitis

Concurr. Comput. Pract. Exp., 2015

High-Order ADER-DG Minimizes Energy- and Time-to-Solution of SeisSol.

Alexander Breuer, Alexander Heinecke, Leonhard Rannabauer, Michael Bader

Proceedings of the High Performance Computing - 30th International Conference, 2015

Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors.

Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke

Proceedings of the International Conference for High Performance Computing, 2015

Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems.

Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

Optimized Force Calculation in Molecular Dynamics Simulations for the Intel Xeon Phi.

Nikola Tchipev, Amer Wafai, Colin W. Glass, Wolfgang Eckhardt, Alexander Heinecke, Hans-Joachim Bungartz, Philipp Neumann

Proceedings of the Euro-Par 2015: Parallel Processing Workshops, 2015

2014

Boosting Scientific Computing Applications through Leveraging Data Parallel Architectures.

Alexander Heinecke

PhD thesis, 2014

ls1 mardyn: The massively parallel molecular dynamics code for large systems.

Christoph Niethammer, Stefan Becker, Martin Bernreuther, Martin Buchholz, Wolfgang Eckhardt, Alexander Heinecke, Stephan Werth, Hans-Joachim Bungartz, Colin W. Glass, Hans Hasse, Jadran Vrabec, Martin Horsch

CoRR, 2014

Parallelizing a Black-Scholes solver based on finite elements and sparse grids.

Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter

Concurr. Comput. Pract. Exp., 2014

Sustained Petascale Performance of Seismic Simulations with SeisSol on SuperMUC.

Alexander Breuer, Alexander Heinecke, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel, Christian Pelties

Proceedings of the Supercomputing - 29th International Conference, 2014

Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices.

Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Xing Liu, Md. Mostofa Ali Patwary, Yutong Lu, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2014

Petascale High Order Dynamic Rupture Earthquake Simulations on Heterogeneous Supercomputers.

Alexander Heinecke, Alexander Breuer, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel, Christian Pelties, Arndt Bode, William Barth, Xiangke Liao, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Pradeep Dubey

Proceedings of the International Conference for High Performance Computing, 2014

Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters.

Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey

Proceedings of the 2014 IEEE 28th International Parallel and Distributed Processing Symposium, 2014

2013

Emerging Architectures Enable to Boost Massively Parallel Data Mining Using Adaptive Sparse Grids.

Alexander Heinecke, Dirk Pflüger

Int. J. Parallel Program., 2013

591 TFLOPS Multi-trillion Particles Simulation on SuperMUC.

Wolfgang Eckhardt, Alexander Heinecke, Reinhold Bader, Matthias Brehm, Nicolay Hammer, Herbert Huber, Hans-Georg Kleinhenz, Jadran Vrabec, Hans Hasse, Martin Horsch, Martin Bernreuther, Colin W. Glass, Christoph Niethammer, Arndt Bode, Hans-Joachim Bungartz

Proceedings of the Supercomputing - 28th International Supercomputing Conference, 2013

Many-core architectures boost the pricing of basket options on adaptive sparse grids.

Alexander Heinecke, Jacob Jepsen, Hans-Joachim Bungartz

Proceedings of WHPCF'13: 6th Workshop on High Performance Computational Finance, 2013

Accelerating SeisSol by Generating Vectorized Code for Sparse Matrix Operators.

Alexander Breuer, Alexander Heinecke, Michael Bader, Christian Pelties

Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Design and Implementation of the Linpack Benchmark for Single and Multi-node Systems Based on Intel® Xeon Phi Coprocessor.

Alexander Heinecke, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Alexander Kobotov, Roman Dubtsov, Greg Henry, Aniruddha G. Shet, George Chrysos, Pradeep Dubey

Proceedings of the 27th IEEE International Symposium on Parallel and Distributed Processing, 2013

Accelerators in scientific computing is it worth the effort?

Alexander Heinecke

Proceedings of the International Conference on High Performance Computing & Simulation, 2013

2012

Option pricing with a direct adaptive sparse grid approach.

Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter

J. Comput. Appl. Math., 2012

A highly parallel Black-Scholes solver based on adaptive sparse grids.

Alexander Heinecke, Stefanie Schraufstetter, Hans-Joachim Bungartz

Int. J. Comput. Math., 2012

From GPGPU to Many-Core: Nvidia Fermi and Intel Many Integrated Core Architecture.

Alexander Heinecke, Michael Klemm, Hans-Joachim Bungartz

Comput. Sci. Eng., 2012

Exploiting State-of-the-Art x86 Architectures in Scientific Computing.

Alexander Heinecke, Thomas Auckenthaler, Carsten Trinitis

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

HPCS 2012 panels: Panel I: Energy efficient systems in next generation high performance data and compute centers.

Laurent Lefèvre, Vicente Martin, Miguel A. Ordonez, Johnatan E. Pecero, Jean-Marc Pierson, Jesús Carretero, Pascal Bouvry, David R. C. Hill, Jesús Labarta, Reinhard Schneider, James C. Sexton, Mads Nygård, Gorka Esnal Lopez, Maria Mirto, Marco Passante, Giovanni Aloisio, Carsten Trinitis, Alexander Heinecke, Lamia Djoudi

Proceedings of the 2012 International Conference on High Performance Computing & Simulation, 2012

Sparse grid classifiers as base learners for AdaBoost.

Alexander Heinecke, Benjamin Peherstorfer, Dirk Pflüger, Zhongwen Song

Proceedings of the 2012 International Conference on High Performance Computing & Simulation, 2012

Solving High-Dimensional Problems on Processors with Integrated GPU.

Alexander Heinecke

Proceedings of the Facing the Multicore-Challenge, 2012

An efficient vectorization of linked-cell particle simulations.

Wolfgang Eckhardt, Alexander Heinecke

Proceedings of the Computing Frontiers Conference, CF'12, 2012

2011

Making TifaMMy fit for tomorrow: Towards future shared memory systems and beyond.

Alexander Heinecke, Carsten Trinitis

Proceedings of the 2011 International Conference on High Performance Computing & Simulation, 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

Extending a Highly Parallel Data Mining Algorithm to the Intel ® Many Integrated Core Architecture.

Alexander Heinecke, Michael Klemm, Dirk Pflüger, Arndt Bode, Hans-Joachim Bungartz

Proceedings of the Euro-Par 2011: Parallel Processing Workshops - CCPI, CGWS, HeteroPar, HiBB, HPCVirt, HPPC, HPSS, MDGS, ProPer, Resilience, UCHPC, VHPC, Bordeaux, France, August 29, 2011

Multi- and many-core data mining with adaptive sparse grids.

Alexander Heinecke, Dirk Pflüger

Proceedings of the 8th Conference on Computing Frontiers, 2011

2010

Porting existing cache-oblivious linear algebra HPC modules to larrabee architecture.

Alexander Heinecke, Carsten Trinitis, Josef Weidendorfer

Proceedings of the 7th Conference on Computing Frontiers, 2010

2007

Hardware-Oriented Implementation of Cache Oblivious Matrix Operations Based on Space-Filling Curves.

Michael Bader, Robert Franz, Stephan Günther, Alexander Heinecke

Proceedings of the Parallel Processing and Applied Mathematics, 2007