Alexander Heinecke

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 46

Top Venues

CoRR

ISC

IPDPS

Technical University Munich (PHD)

Education History

Technical University Munich

PHD

Publications

Renato Golin, Lorenzo Chelini, Adam Siemieniuk, Kavitha Madhu, Niranjan Hasabnis, Hans Pabst, Evangelos Georganas, Alexander Heinecke
Towards a high-performance AI compiler with upstream MLIR. CoRR (2024)
Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Abhisek Kundu, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke
Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures. IPDPS (2024)
Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke
Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures. CoRR (2023)
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
Microscaling Data Formats for Deep Learning. CoRR (2023)
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
FP8 Formats for Deep Learning. CoRR (2022)
Rui Ma, Evangelos Georganas, Alexander Heinecke, Sergey Gribok, Andrew Boutros, Eriko Nurvitadhi
FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems. IEEE Comput. Archit. Lett. 21 (2) (2022)
Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data. IPDPS Workshops (2022)
Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi
FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems. CoRR (2022)
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, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Brian Retford, Barukh Ziv, Alexander Heinecke
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. Frontiers Appl. Math. Stat. 8 (2022)
Alexander Breuer, Alexander Heinecke
Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. IPDPS (2022)
Alexander Breuer, Alexander Heinecke
Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. CoRR (2022)
Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
Efficient and Generic 1D Dilated Convolution Layer for Deep Learning. CoRR (2021)
Vasimuddin Md, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha
DistGNN: scalable distributed training for large-scale graph neural networks. SC (2021)
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Bharat Kaul, Gagandeep Goyal, Ramakrishna Upadrasta
PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives. ACM Trans. Archit. Code Optim. 18 (1) (2021)
Vasimuddin Md, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks. CoRR (2021)
Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads. CoRR (2021)
Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Vasimuddin Md, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke
Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. SC (2021)
Bilel Hadri, Matteo Parsani, Maxwell Hutchinson, Alexander Heinecke, Lisandro Dalcín, David E. Keyes
Performance study of sustained petascale direct numerical simulation on Cray XC40 systems. Concurr. Comput. Pract. Exp. 32 (20) (2020)
Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures. CoRR (2020)
Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
Optimizing deep learning recommender systems training on CPU cluster architectures. SC (2020)
Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
Harnessing Deep Learning via a Single Building Block. IPDPS (2020)
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives. CoRR (2020)
Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives. CoRR (2020)
Kunal Banerjee, Evangelos Georganas, Dhiraj D. Kalamkar, Barukh Ziv, Eden Segal, Cristina Anderson, Alexander Heinecke
Optimizing Deep Learning RNN Topologies on Intel Architecture. Supercomput. Front. Innov. 6 (3) (2019)
Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
High-Performance Deep Learning via a Single Building Block. CoRR (2019)
Greg Henry, Ping Tak Peter Tang, Alexander Heinecke
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. ARITH (2019)
Amelia Drew, Alexander Heinecke
Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F). CoRR (2019)
Alexander Heinecke, Alexander Breuer, Yifeng Cui
Tensor-optimized hardware accelerates fused discontinuous Galerkin simulations. Parallel Comput. 89 (2019)
Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight
ISA mapper: a compute and hardware agnostic deep learning compiler. CF (2019)
Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke
Training Google Neural Machine Translation on an Intel CPU Cluster. CLUSTER (2019)
Alexander Breuer, Yifeng Cui, Alexander Heinecke
Petaflop Seismic Simulations in the Public Cloud. ISC (2019)
Greg Henry, Ping Tak Peter Tang, Alexander Heinecke
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. CoRR (2019)
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
A Study of BFLOAT16 for Deep Learning Training. CoRR (2019)
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
Mixed Precision Training of Convolutional Neural Networks using Integer Operations. ICLR (Poster) (2018)
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
Mixed Precision Training of Convolutional Neural Networks using Integer Operations. CoRR (2018)
Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke
Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures. CoRR (2018)
Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight
ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler. CoRR (2018)
Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke
Anatomy of high-performance deep learning convolutions on SIMD architectures. SC (2018)
Alexander Breuer, Alexander Heinecke, Yifeng Cui
EDGE: Extreme Scale Fused Seismic Simulations with the Discontinuous Galerkin Method. ISC (2017)
Josh Tobin, Alexander Breuer, Alexander Heinecke, Charles Yount, Yifeng Cui
Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor. ISC (2017)
Alexander Heinecke, Alexander Breuer, Michael Bader, Pradeep Dubey
High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing). ISC (2016)
Alexander Breuer, Alexander Heinecke, Michael Bader
Petascale Local Time Stepping for the ADER-DG Finite Element Method. IPDPS (2016)
Alexander Heinecke, Greg Henry, Maxwell Hutchinson, Hans Pabst
LIBXSMM: accelerating small matrix multiplications by runtime code generation. SC (2016)
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
Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors. Int. J. High Perform. Comput. Appl. 30 (1) (2016)
Alexander Heinecke, Roman Karlstetter, Dirk Pflüger, Hans-Joachim Bungartz
Data mining on vast data sets as a cluster system benchmark. Concurr. Comput. Pract. Exp. 28 (7) (2016)
Maxwell Hutchinson, Alexander Heinecke, Hans Pabst, Greg Henry, Matteo Parsani, David E. Keyes
Efficiency of High Order Spectral Element Methods on Petascale Architectures. ISC (2016)
Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke
Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. SC (2015)
Nikola Tchipev, Amer Wafai, Colin W. Glass, Wolfgang Eckhardt, Alexander Heinecke, Hans-Joachim Bungartz, Philipp Neumann
Optimized Force Calculation in Molecular Dynamics Simulations for the Intel Xeon Phi. Euro-Par Workshops (2015)
Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes
Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. IPDPS (2015)
Alexander Breuer, Alexander Heinecke, Leonhard Rannabauer, Michael Bader
High-Order ADER-DG Minimizes Energy- and Time-to-Solution of SeisSol. ISC (2015)
R. Glenn Brook, Alexander Heinecke, Anthony B. Costa, Paul Peltz Jr., Vincent C. Betro, Troy Baer, Michael Bader, Pradeep Dubey
Beacon: Deployment and Application of Intel Xeon Phi Coprocessorsfor Scientific Computing. Comput. Sci. Eng. 17 (2) (2015)
Alexander Heinecke, Carsten Trinitis
Cache-oblivious matrix algorithms in the age of multicores and many cores. Concurr. Comput. Pract. Exp. 27 (9) (2015)
Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey
Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters. IPDPS (2014)
Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Xing Liu, Md. Mostofa Ali Patwary, Yutong Lu, Pradeep Dubey
Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices. SC (2014)
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
ls1 mardyn: The massively parallel molecular dynamics code for large systems. CoRR (2014)
Alexander Breuer, Alexander Heinecke, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel, Christian Pelties
Sustained Petascale Performance of Seismic Simulations with SeisSol on SuperMUC. ISC (2014)
Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
Parallelizing a Black-Scholes solver based on finite elements and sparse grids. Concurr. Comput. Pract. Exp. 26 (9) (2014)
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
Petascale High Order Dynamic Rupture Earthquake Simulations on Heterogeneous Supercomputers. SC (2014)
Alexander Heinecke, Dirk Pflüger
Emerging Architectures Enable to Boost Massively Parallel Data Mining Using Adaptive Sparse Grids. Int. J. Parallel Program. 41 (3) (2013)
Alexander Breuer, Alexander Heinecke, Michael Bader, Christian Pelties
Accelerating SeisSol by Generating Vectorized Code for Sparse Matrix Operators. PARCO (2013)
Alexander Heinecke
Accelerators in scientific computing is it worth the effort? HPCS (2013)
Alexander Heinecke, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Alexander Kobotov, Roman Dubtsov, Greg Henry, Aniruddha G. Shet, George Chrysos, Pradeep Dubey
Design and Implementation of the Linpack Benchmark for Single and Multi-node Systems Based on Intel® Xeon Phi Coprocessor. IPDPS (2013)
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
591 TFLOPS Multi-trillion Particles Simulation on SuperMUC. ISC (2013)
Alexander Heinecke, Jacob Jepsen, Hans-Joachim Bungartz
Many-core architectures boost the pricing of basket options on adaptive sparse grids. WHPCF@SC (2013)
Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
Option pricing with a direct adaptive sparse grid approach. J. Comput. Appl. Math. 236 (15) (2012)
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
HPCS 2012 panels: Panel I: Energy efficient systems in next generation high performance data and compute centers. HPCS (2012)
Alexander Heinecke, Michael Klemm, Hans-Joachim Bungartz
From GPGPU to Many-Core: Nvidia Fermi and Intel Many Integrated Core Architecture. Comput. Sci. Eng. 14 (2) (2012)
Wolfgang Eckhardt, Alexander Heinecke
An efficient vectorization of linked-cell particle simulations. Conf. Computing Frontiers (2012)
Alexander Heinecke, Stefanie Schraufstetter, Hans-Joachim Bungartz
A highly parallel Black-Scholes solver based on adaptive sparse grids. Int. J. Comput. Math. 89 (9) (2012)
Alexander Heinecke
Solving High-Dimensional Problems on Processors with Integrated GPU. Facing the Multicore-Challenge (2012)
Alexander Heinecke, Benjamin Peherstorfer, Dirk Pflüger, Zhongwen Song
Sparse grid classifiers as base learners for AdaBoost. HPCS (2012)
Alexander Heinecke, Thomas Auckenthaler, Carsten Trinitis
Exploiting State-of-the-Art x86 Architectures in Scientific Computing. ISPDC (2012)
Alexander Heinecke, Dirk Pflüger
Multi- and many-core data mining with adaptive sparse grids. Conf. Computing Frontiers (2011)
Alexander Heinecke, Carsten Trinitis
Making TifaMMy fit for tomorrow: Towards future shared memory systems and beyond. HPCS (2011)
Alexander Heinecke, Michael Klemm, Dirk Pflüger, Arndt Bode, Hans-Joachim Bungartz
Extending a Highly Parallel Data Mining Algorithm to the Intel ® Many Integrated Core Architecture. Euro-Par Workshops (2) (2011)
Alexander Heinecke, Michael Klemm, Hans Pabst, Dirk Pflüger
Towards High-Performance Implementations of a Custom HPC Kernel Using ® Array Building Blocks. Facing the Multicore-Challenge (2011)
Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
Parallelizing a Black-Scholes solver based on finite elements and sparse grids. IPDPS Workshops (2010)
Alexander Heinecke, Carsten Trinitis, Josef Weidendorfer
Porting existing cache-oblivious linear algebra HPC modules to larrabee architecture. Conf. Computing Frontiers (2010)
Michael Bader, Robert Franz, Stephan Günther, Alexander Heinecke
Hardware-Oriented Implementation of Cache Oblivious Matrix Operations Based on Space-Filling Curves. PPAM (2007)

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Publication Activity (10 Years)

Top Topics

Top Venues

Alexander Heinecke