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Alexander Heinecke
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2020 – today
- 2024
- [c44]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: 950-963 - [i20]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 abs/2404.15204 (2024) - 2023
- [i19]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 abs/2304.12576 (2023) - [i18]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 abs/2310.10537 (2023) - 2022
- [j15]Rui Ma
, Evangelos Georganas, Alexander Heinecke, Sergey Gribok
FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems. IEEE Comput. Archit. Lett. 21(2): 49-52 (2022) - [j14]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:
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. Frontiers Appl. Math. Stat. 8: 826269 (2022) - [c43]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: 176-185 - [c42]Alexander Breuer, Alexander Heinecke:
Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. IPDPS 2022: 402-413 - [i17]Alexander Breuer, Alexander Heinecke:
Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. CoRR abs/2202.10313 (2022) - [i16]Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi:
FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems. CoRR abs/2204.10943 (2022) - [i15]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 abs/2209.05433 (2022) - 2021
- [j13]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): 11:1-11:27 (2021) - [c41]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:
Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. SC 2021: 14 - [c40]Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed
DistGNN: scalable distributed training for large-scale graph neural networks. SC 2021: 76 - [i14]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:
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads. CoRR abs/2104.05755 (2021) - [i13]Md. Vasimuddin, 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 abs/2104.06700 (2021) - [i12]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 abs/2104.08002 (2021) - 2020
- [j12]Bilel Hadri
Performance study of sustained petascale direct numerical simulation on Cray XC40 systems. Concurr. Comput. Pract. Exp. 32(20) (2020) - [c39]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: 222-233 - [c38]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: 43 - [i11]Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives. CoRR abs/2002.02145 (2020) - [i10]Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke:
Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures. CoRR abs/2005.04680 (2020) - [i9]Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul:
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives. CoRR abs/2006.02230 (2020)
2010 – 2019
- 2019
- [j11]Alexander Heinecke, Alexander Breuer, Yifeng Cui:
Tensor-optimized hardware accelerates fused discontinuous Galerkin simulations. Parallel Comput. 89 (2019) - [j10]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): 64-85 (2019) - [c37]Greg Henry, Ping Tak Peter Tang, Alexander Heinecke:
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. ARITH 2019: 69-76 - [c36]Matthew Sotoudeh
ISA mapper: a compute and hardware agnostic deep learning compiler. CF 2019: 164-173 - [c35]Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov
Training Google Neural Machine Translation on an Intel CPU Cluster. CLUSTER 2019: 1-10 - [c34]Alexander Breuer, Yifeng Cui, Alexander Heinecke:
Petaflop Seismic Simulations in the Public Cloud. ISC 2019: 167-185 - [i8]Greg Henry, Ping Tak Peter Tang, Alexander Heinecke:
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. CoRR abs/1904.06376 (2019) - [i7]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 abs/1905.12322 (2019) - [i6]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 abs/1906.06440 (2019) - [i5]Amelia Drew
Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F). CoRR abs/1911.01933 (2019) - 2018
- [c33]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 - [c32]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: 66:1-66:12 - [i4]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 abs/1802.00930 (2018) - [i3]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 abs/1808.05567 (2018) - [i2]Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight:
ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler. CoRR abs/1810.09958 (2018) - 2017
- [c31]Alexander Breuer, Alexander Heinecke, Yifeng Cui:
EDGE: Extreme Scale Fused Seismic Simulations with the Discontinuous Galerkin Method. ISC 2017: 41-60 - [c30]Josh Tobin, Alexander Breuer, Alexander Heinecke, Charles Yount, Yifeng Cui:
Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor. ISC 2017: 139-157 - 2016
- [j9]Alexander Heinecke, Roman Karlstetter, Dirk Pflüger
Data mining on vast data sets as a cluster system benchmark. Concurr. Comput. Pract. Exp. 28(7): 2145-2165 (2016) - [j8]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): 11-27 (2016) - [c29]Alexander Breuer, Alexander Heinecke, Michael Bader:
Petascale Local Time Stepping for the ADER-DG Finite Element Method. IPDPS 2016: 854-863 - [c28]Alexander Heinecke, Greg Henry, Maxwell Hutchinson, Hans Pabst:
LIBXSMM: accelerating small matrix multiplications by runtime code generation. SC 2016: 981-991 - [c27]Alexander Heinecke, Alexander Breuer, Michael Bader, Pradeep Dubey:
High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing). ISC 2016: 343-362 - [c26]Maxwell Hutchinson, Alexander Heinecke, Hans Pabst, Greg Henry, Matteo Parsani
Efficiency of High Order Spectral Element Methods on Petascale Architectures. ISC 2016: 449-466 - 2015
- [b2]Alexander Heinecke, Wolfgang Eckhardt, Martin Horsch, Hans-Joachim Bungartz:
Supercomputing for Molecular Dynamics Simulations - Handling Multi-Trillion Particles in Nanofluidics. Springer Briefs in Computer Science, Springer 2015, ISBN 978-3-319-17147-0, pp. 1-76 - [j7]Alexander Heinecke, Carsten Trinitis:
Cache-oblivious matrix algorithms in the age of multicores and many cores. Concurr. Comput. Pract. Exp. 27(9): 2215-2234 (2015) - [j6]R. Glenn Brook, Alexander Heinecke, Anthony B. Costa
Beacon: Deployment and Application of Intel Xeon Phi Coprocessorsfor Scientific Computing. Comput. Sci. Eng. 17(2): 65-72 (2015) - [c25]Nikola Tchipev, Amer Wafai, Colin W. Glass
Optimized Force Calculation in Molecular Dynamics Simulations for the Intel Xeon Phi. Euro-Par Workshops 2015: 774-785 - [c24]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: 723-732 - [c23]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: 23:1-23:12 - [c22]Alexander Breuer, Alexander Heinecke, Leonhard Rannabauer, Michael Bader:
High-Order ADER-DG Minimizes Energy- and Time-to-Solution of SeisSol. ISC 2015: 340-357 - 2014
- [b1]Alexander Heinecke:
Boosting Scientific Computing Applications through Leveraging Data Parallel Architectures. Technical University Munich, Verlag Dr. Hut 2014, ISBN 978-3-8439-1408-6, pp. 1-231 - [j5]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): 1640-1653 (2014) - [c21]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: 1083-1092 - [c20]Alexander Heinecke, Alexander Breuer, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel
Petascale High Order Dynamic Rupture Earthquake Simulations on Heterogeneous Supercomputers. SC 2014: 3-14 - [c19]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: 945-955 - [c18]Alexander Breuer, Alexander Heinecke, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel
Sustained Petascale Performance of Seismic Simulations with SeisSol on SuperMUC. ISC 2014: 1-18 - [i1]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 abs/1408.4599 (2014) - 2013
- [j4]Alexander Heinecke, Dirk Pflüger:
Emerging Architectures Enable to Boost Massively Parallel Data Mining Using Adaptive Sparse Grids. Int. J. Parallel Program. 41(3): 357-399 (2013) - [c17]Alexander Heinecke:
Accelerators in scientific computing is it worth the effort? HPCS 2013: 504 - [c16]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: 126-137 - [c15]Alexander Breuer, Alexander Heinecke, Michael Bader, Christian Pelties:
Accelerating SeisSol by Generating Vectorized Code for Sparse Matrix Operators. PARCO 2013: 347-356 - [c14]Alexander Heinecke, Jacob Jepsen, Hans-Joachim Bungartz:
Many-core architectures boost the pricing of basket options on adaptive sparse grids. WHPCF@SC 2013: 1:1-1:9 - [c13]Wolfgang Eckhardt, Alexander Heinecke, Reinhold Bader, Matthias Brehm, Nicolay Hammer, Herbert Huber, Hans-Georg Kleinhenz, Jadran Vrabec
591 TFLOPS Multi-trillion Particles Simulation on SuperMUC. ISC 2013: 1-12 - [e1]Hubertus Franke, Alexander Heinecke, Krishna V. Palem, Eli Upfal:
Computing Frontiers Conference, CF'13, Ischia, Italy, May 14 - 16, 2013. ACM 2013, ISBN 978-1-4503-2053-5 [contents] - 2012
- [j3]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): 78-83 (2012) - [j2]Alexander Heinecke, Stefanie Schraufstetter, Hans-Joachim Bungartz:
A highly parallel Black-Scholes solver based on adaptive sparse grids. Int. J. Comput. Math. 89(9): 1212-1238 (2012) - [j1]Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter:
Option pricing with a direct adaptive sparse grid approach. J. Comput. Appl. Math. 236(15): 3741-3750 (2012) - [c12]Wolfgang Eckhardt, Alexander Heinecke:
An efficient vectorization of linked-cell particle simulations. Conf. Computing Frontiers 2012: 241-244 - [c11]Alexander Heinecke:
Solving High-Dimensional Problems on Processors with Integrated GPU. Facing the Multicore-Challenge 2012: 121-122 - [c10]Alexander Heinecke, Benjamin Peherstorfer, Dirk Pflüger, Zhongwen Song:
Sparse grid classifiers as base learners for AdaBoost. HPCS 2012: 161-166 - [c9]Laurent Lefèvre, Vicente Martin, Miguel A. Ordonez, Johnatan E. Pecero, Jean-Marc Pierson
HPCS 2012 panels: Panel I: Energy efficient systems in next generation high performance data and compute centers. HPCS 2012 - [c8]Alexander Heinecke, Thomas Auckenthaler, Carsten Trinitis:
Exploiting State-of-the-Art x86 Architectures in Scientific Computing. ISPDC 2012: 47-54 - 2011
- [c7]Alexander Heinecke, Dirk Pflüger:
Multi- and many-core data mining with adaptive sparse grids. Conf. Computing Frontiers 2011: 29 - [c6]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: 375-384 - [c5]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: 36-47 - [c4]Alexander Heinecke, Carsten Trinitis:
Making TifaMMy fit for tomorrow: Towards future shared memory systems and beyond. HPCS 2011: 517-524 - 2010
- [c3]Alexander Heinecke, Carsten Trinitis, Josef Weidendorfer:
Porting existing cache-oblivious linear algebra HPC modules to larrabee architecture. Conf. Computing Frontiers 2010: 91-92 - [c2]Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter:
Parallelizing a Black-Scholes solver based on finite elements and sparse grids. IPDPS Workshops 2010: 1-8
2000 – 2009
- 2007
- [c1]Michael Bader, Robert Franz, Stephan Günther, Alexander Heinecke:
Hardware-Oriented Implementation of Cache Oblivious Matrix Operations Based on Space-Filling Curves. PPAM 2007: 628-638
Coauthor Index
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