Alexander Heinecke

88 papers A 15C 11Misc 1Journal 40Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Space Filling Curves is All You Need: Communication-Avoiding Matrix Multiplication Made Simple. CoRR Evangelos Georganas, Alexander Heinecke, Pradeep Dubey
2026	J	`jnl`	Tensor Algebra Processing Primitives (TAPP): Towards a Standard for Tensor Operations. CoRR Jan Brandejs, Niklas Hörnblad, Edward F. Valeev, Alexander Heinecke, Jeff R. Hammond, Devin Matthews, Paolo Bientinesi
2025	—	`conf`	Einsum Trees: An Abstraction for Optimizing the Execution of Tensor Expressions. ASPLOS (2) Alexander Breuer, Mark Blacher, Max Engel, Joachim Giesen, Alexander Heinecke, Julien Klaus, Stefan Remke
2025	J	`jnl`	Library Liberation: Competitive Performance Matmul Through Compiler-composed Nanokernels. CoRR Arun Thangamani, Md Asghar Ahmad Shahid, Adam Siemieniuk, Rolf Morel, Renato Golin, Alexander Heinecke
2025	J	`jnl`	ML-SpecQD: Multi-Level Speculative Decoding with Quantized Drafts. CoRR Evangelos Georganas, Dhiraj D. Kalamkar, Alexander Kozlov, Alexander Heinecke
2025	J	`jnl`	Pushing the Envelope of LLM Inference on AI-PC. CoRR Evangelos Georganas, Dhiraj D. Kalamkar, Alexander Heinecke
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
2023	J	`jnl`	Microscaling Data Formats for Deep Learning. CoRR 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
2022	—	`conf`	Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data. IPDPS Workshops Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
2022	J	`jnl`	FP8 Formats for Deep Learning. CoRR 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
2022	J	`jnl`	FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems. IEEE Comput. Archit. Lett. Rui Ma, Evangelos Georganas, Alexander Heinecke, Sergey Gribok, Andrew Boutros, Eriko Nurvitadhi
2022	J	`jnl`	FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems. CoRR Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi
2022	A	`conf`	Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. IPDPS Alexander Breuer, Alexander Heinecke
2022	J	`jnl`	Next-Generation Local Time Stepping for the ADER-DG Finite Element Method. CoRR 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
2021	J	`jnl`	DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks. CoRR Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha
2021	A	`conf`	DistGNN: scalable distributed training for large-scale graph neural networks. SC Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha
2021	J	`jnl`	Efficient and Generic 1D Dilated Convolution Layer for Deep Learning. CoRR Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul
2021	J	`jnl`	PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives. ACM Trans. Archit. Code Optim. Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Bharat Kaul, Gagandeep Goyal, Ramakrishna Upadrasta
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
2020	J	`jnl`	Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures. CoRR Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
2020	A	`conf`	Optimizing deep learning recommender systems training on CPU cluster architectures. SC Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke
2020	J	`jnl`	Performance study of sustained petascale direct numerical simulation on Cray XC40 systems. Concurr. Comput. Pract. Exp. Bilel Hadri, Matteo Parsani, Maxwell Hutchinson, Alexander Heinecke, Lisandro Dalcín, David E. Keyes
2020	J	`jnl`	PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives. CoRR Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
2020	J	`jnl`	PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives. CoRR Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul
2019	J	`jnl`	A Study of BFLOAT16 for Deep Learning Training. CoRR 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
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
2019	—	`conf`	ISA mapper: a compute and hardware agnostic deep learning compiler. CF Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight
2019	C	`conf`	Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. ARITH Greg Henry, Ping Tak Peter Tang, Alexander Heinecke
2019	J	`jnl`	Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations. CoRR Greg Henry, Ping Tak Peter Tang, Alexander Heinecke
2019	J	`jnl`	Optimizing Deep Learning RNN Topologies on Intel Architecture. Supercomput. Front. Innov. Kunal Banerjee, Evangelos Georganas, Dhiraj D. Kalamkar, Barukh Ziv, Eden Segal, Cristina Anderson, Alexander Heinecke
2019	C	`conf`	Petaflop Seismic Simulations in the Public Cloud. ISC Alexander Breuer, Yifeng Cui, Alexander Heinecke
2019	J	`jnl`	Tensor-optimized hardware accelerates fused discontinuous Galerkin simulations. Parallel Comput. Alexander Heinecke, Alexander Breuer, Yifeng Cui
2019	C	`conf`	Training Google Neural Machine Translation on an Intel CPU Cluster. CLUSTER Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke
2019	J	`jnl`	Training Neural Machine Translation (NMT) Models using Tensor Train Decomposition on TensorFlow (T3F). CoRR Amelia Drew, 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	J	`jnl`	ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler. CoRR Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight
2018	—	`conf`	Mixed Precision Training of Convolutional Neural Networks using Integer Operations. ICLR (Poster) 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
2018	J	`jnl`	Mixed Precision Training of Convolutional Neural Networks using Integer Operations. CoRR 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
2017	C	`conf`	Accelerating Seismic Simulations Using the Intel Xeon Phi Knights Landing Processor. ISC Josh Tobin, Alexander Breuer, Alexander Heinecke, Charles Yount, Yifeng Cui
2017	C	`conf`	EDGE: Extreme Scale Fused Seismic Simulations with the Discontinuous Galerkin Method. ISC Alexander Breuer, Alexander Heinecke, Yifeng Cui
2016	J	`jnl`	Data mining on vast data sets as a cluster system benchmark. Concurr. Comput. Pract. Exp. Alexander Heinecke, Roman Karlstetter, Dirk Pflüger, Hans-Joachim Bungartz
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	C	`conf`	High Order Seismic Simulations on the Intel Xeon Phi Processor (Knights Landing). ISC Alexander Heinecke, Alexander Breuer, Michael Bader, Pradeep Dubey
2016	A	`conf`	LIBXSMM: accelerating small matrix multiplications by runtime code generation. SC Alexander Heinecke, Greg Henry, Maxwell Hutchinson, Hans Pabst
2016	J	`jnl`	Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors. Int. J. High Perform. Comput. Appl. 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
2016	A	`conf`	Petascale Local Time Stepping for the ADER-DG Finite Element Method. IPDPS Alexander Breuer, Alexander Heinecke, Michael Bader
2015	J	`jnl`	Beacon: Deployment and Application of Intel Xeon Phi Coprocessorsfor Scientific Computing. Comput. Sci. Eng. R. Glenn Brook, Alexander Heinecke, Anthony B. Costa, Paul Peltz Jr., Vincent C. Betro, Troy Baer, Michael Bader, Pradeep Dubey
2015	J	`jnl`	Cache-oblivious matrix algorithms in the age of multicores and many cores. Concurr. Comput. Pract. Exp. Alexander Heinecke, Carsten Trinitis
2015	A	`conf`	Exploring Shared-Memory Optimizations for an Unstructured Mesh CFD Application on Modern Parallel Systems. IPDPS Dheevatsa Mudigere, Srinivas Sridharan, Anand M. Deshpande, Jongsoo Park, Alexander Heinecke, Mikhail Smelyanskiy, Bharat Kaul, Pradeep Dubey, Dinesh K. Kaushik, David E. Keyes
2015	A	`conf`	Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. SC Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke
2015	C	`conf`	High-Order ADER-DG Minimizes Energy- and Time-to-Solution of SeisSol. ISC Alexander Breuer, Alexander Heinecke, Leonhard Rannabauer, Michael Bader
2015	—	`conf`	Optimized Force Calculation in Molecular Dynamics Simulations for the Intel Xeon Phi. Euro-Par Workshops Nikola Tchipev, Amer Wafai, Colin W. Glass, Wolfgang Eckhardt, Alexander Heinecke, Hans-Joachim Bungartz, Philipp Neumann
2015	—	`book`	Supercomputing for Molecular Dynamics Simulations - Handling Multi-Trillion Particles in Nanofluidics Alexander Heinecke, Wolfgang Eckhardt, Martin Horsch, Hans-Joachim Bungartz
2014	—	`—`	Boosting Scientific Computing Applications through Leveraging Data Parallel Architectures. Alexander Heinecke
2014	A	`conf`	Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices. SC Jongsoo Park, Mikhail Smelyanskiy, Karthikeyan Vaidyanathan, Alexander Heinecke, Dhiraj D. Kalamkar, Xing Liu, Md. Mostofa Ali Patwary, Yutong Lu, Pradeep Dubey
2014	A	`conf`	Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters. IPDPS Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha G. Shet, Bharat Kaul, Bálint Joó, Pradeep Dubey
2014	J	`jnl`	Parallelizing a Black-Scholes solver based on finite elements and sparse grids. Concurr. Comput. Pract. Exp. Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
2014	A	`conf`	Petascale High Order Dynamic Rupture Earthquake Simulations on Heterogeneous Supercomputers. SC 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
2014	C	`conf`	Sustained Petascale Performance of Seismic Simulations with SeisSol on SuperMUC. ISC Alexander Breuer, Alexander Heinecke, Sebastian Rettenberger, Michael Bader, Alice-Agnes Gabriel, Christian Pelties
2014	J	`jnl`	ls1 mardyn: The massively parallel molecular dynamics code for large systems. CoRR 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
2013	C	`conf`	591 TFLOPS Multi-trillion Particles Simulation on SuperMUC. ISC 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
2013	—	`conf`	Accelerating SeisSol by Generating Vectorized Code for Sparse Matrix Operators. PARCO Alexander Breuer, Alexander Heinecke, Michael Bader, Christian Pelties
2013	—	`conf`	Accelerators in scientific computing is it worth the effort? HPCS Alexander Heinecke
2013	—	`ed.`	Computing Frontiers Conference, CF'13, Ischia, Italy, May 14 - 16, 2013 Conf. Computing Frontiers Hubertus Franke, Alexander Heinecke, Krishna V. Palem, Eli Upfal
2013	A	`conf`	Design and Implementation of the Linpack Benchmark for Single and Multi-node Systems Based on Intel® Xeon Phi Coprocessor. IPDPS Alexander Heinecke, Karthikeyan Vaidyanathan, Mikhail Smelyanskiy, Alexander Kobotov, Roman Dubtsov, Greg Henry, Aniruddha G. Shet, George Chrysos, Pradeep Dubey
2013	J	`jnl`	Emerging Architectures Enable to Boost Massively Parallel Data Mining Using Adaptive Sparse Grids. Int. J. Parallel Program. Alexander Heinecke, Dirk Pflüger
2013	—	`conf`	Many-core architectures boost the pricing of basket options on adaptive sparse grids. WHPCF@SC Alexander Heinecke, Jacob Jepsen, Hans-Joachim Bungartz
2012	J	`jnl`	A highly parallel Black-Scholes solver based on adaptive sparse grids. Int. J. Comput. Math. Alexander Heinecke, Stefanie Schraufstetter, Hans-Joachim Bungartz
2012	—	`conf`	An efficient vectorization of linked-cell particle simulations. Conf. Computing Frontiers Wolfgang Eckhardt, Alexander Heinecke
2012	C	`conf`	Exploiting State-of-the-Art x86 Architectures in Scientific Computing. ISPDC Alexander Heinecke, Thomas Auckenthaler, Carsten Trinitis
2012	J	`jnl`	From GPGPU to Many-Core: Nvidia Fermi and Intel Many Integrated Core Architecture. Comput. Sci. Eng. Alexander Heinecke, Michael Klemm, Hans-Joachim Bungartz
2012	—	`conf`	HPCS 2012 panels: Panel I: Energy efficient systems in next generation high performance data and compute centers. HPCS 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
2012	J	`jnl`	Option pricing with a direct adaptive sparse grid approach. J. Comput. Appl. Math. Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
2012	—	`conf`	Solving High-Dimensional Problems on Processors with Integrated GPU. Facing the Multicore-Challenge Alexander Heinecke
2012	—	`conf`	Sparse grid classifiers as base learners for AdaBoost. HPCS Alexander Heinecke, Benjamin Peherstorfer, Dirk Pflüger, Zhongwen Song
2011	—	`conf`	Extending a Highly Parallel Data Mining Algorithm to the Intel ® Many Integrated Core Architecture. Euro-Par Workshops (2) Alexander Heinecke, Michael Klemm, Dirk Pflüger, Arndt Bode, Hans-Joachim Bungartz
2011	—	`conf`	Making TifaMMy fit for tomorrow: Towards future shared memory systems and beyond. HPCS Alexander Heinecke, Carsten Trinitis
2011	—	`conf`	Multi- and many-core data mining with adaptive sparse grids. Conf. Computing Frontiers Alexander Heinecke, Dirk Pflüger
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`	Parallelizing a Black-Scholes solver based on finite elements and sparse grids. IPDPS Workshops Hans-Joachim Bungartz, Alexander Heinecke, Dirk Pflüger, Stefanie Schraufstetter
2010	—	`conf`	Porting existing cache-oblivious linear algebra HPC modules to larrabee architecture. Conf. Computing Frontiers Alexander Heinecke, Carsten Trinitis, Josef Weidendorfer
2007	Misc	`conf`	Hardware-Oriented Implementation of Cache Oblivious Matrix Operations Based on Space-Filling Curves. PPAM Michael Bader, Robert Franz, Stephan Günther, Alexander Heinecke