Tal Ben-Nun - RankMe

116 papers A* 4A 26B 5C 4Misc 1Journal 69Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Unifying Framework to Enable Artificial Intelligence in High Performance Computing Workflows. CoRR Jens Domke, Mohamed Wahib, Anshu Dubey, Tal Ben-Nun, Erik W. Draeger
2025	J	`jnl`	A Unifying Framework to Enable Artificial Intelligence in High-Performance Computing Workflows. Comput. Sci. Eng. Jens Domke, Mohamed Wahib, Anshu Dubey, Tal Ben-Nun, Erik W. Draeger
2025	J	`jnl`	BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models. CoRR Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun, Peggy Li, James Diffenderfer, Busra Demirci, Obadiah Smolenski, Tim Hsu, Anna M. Hiszpanski, Kenneth Chiu, Bhavya Kailkhura, Brian Van Essen
2025	A	`conf`	C.A.T.S.: Memory and Control Flow Tracing for Whole-Program Performance Analysis. SC Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
2025	A	`conf`	Energy-Optimal and Low-Depth Algorithmic Primitives for Spatial Dataflow Architectures. IPDPS Lukas Gianinazzi, Tal Ben-Nun, Maciej Besta, Saleh Ashkboos, Yves Baumann, Piotr Luczynski, Torsten Hoefler
2025	—	`conf`	Extending RAJA Parallel Programming Abstractions with Just-In-Time Optimization. SC Workshops John Bowen, Konstantinos Parasyris, David Beckingsale, Tal Ben-Nun, Thomas Stitt, Giorgis Georgakoudis
2025	J	`jnl`	Inductive Loop Analysis for Practical HPC Application Optimization. CoRR Philipp Schaad, Tal Ben-Nun, Patrick Iff, Torsten Hoefler
2025	C	`conf`	Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions. ISC Keita Teranishi, Harshitha Menon, William F. Godoy, Prasanna Balaprakash, David Bau, Tal Ben-Nun, Abhinav Bhatele, Franz Franchetti, Michael E. Franusich, Todd Gamblin, Giorgis Georgakoudis, Tom Goldstein, Arjun Guha, Steven E. Hahn, Costin Iancu, Zheming Jin, Terry R. Jones, Tze Meng Low, Het Mankad, Narasinga Rao Miniskar, Mohammad Alaul Haque Monil, Daniel Nichols, Konstantinos Parasyris, Swaroop Pophale, Pedro Valero-Lara, Jeffrey S. Vetter, Samuel Williams, Aaron R. Young
2025	J	`jnl`	Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions. CoRR Keita Teranishi, Harshitha Menon, William F. Godoy, Prasanna Balaprakash, David Bau, Tal Ben-Nun, Abhinav Bhatele, Franz Franchetti, Michael E. Franusich, Todd Gamblin, Giorgis Georgakoudis, Tom Goldstein, Arjun Guha, Steven E. Hahn, Costin Iancu, Zheming Jin, Terry R. Jones, Tze Meng Low, Het Mankad, Narasinga Rao Miniskar, Mohammad Alaul Haque Monil, Daniel Nichols, Konstantinos Parasyris, Swaroop Pophale, Pedro Valero-Lara, Jeffrey S. Vetter, Samuel Williams, Aaron R. Young
2025	J	`jnl`	Modeling Code: Is Text All You Need? CoRR Daniel Nichols, Konstantinos Parasyris, Harshitha Menon, Brian R. Bartoldson, Giorgis Georgakoudis, Tal Ben-Nun, Abhinav Bhatele
2025	J	`jnl`	Productivity, Portability, Performance, and Reproducibility: Data-Centric Python. IEEE Trans. Parallel Distributed Syst. Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler
2025	J	`jnl`	SPADA: A Spatial Dataflow Architecture Programming Language. CoRR Lukas Gianinazzi, Tal Ben-Nun, Torsten Hoefler
2025	—	`conf`	Speculative Diffusion Decoding: Accelerating Language Generation through Diffusion. NAACL (Long Papers) Jacob K. Christopher, Brian R. Bartoldson, Tal Ben-Nun, Michael Cardei, Bhavya Kailkhura, Ferdinando Fioretto
2025	J	`jnl`	Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training. CoRR Brian R. Bartoldson, Siddarth Venkatraman, James Diffenderfer, Moksh Jain, Tal Ben-Nun, Seanie Lee, Minsu Kim, Johan S. Obando-Ceron, Yoshua Bengio, Bhavya Kailkhura
2025	J	`jnl`	VEIL: Reading Control Flow Graphs Like Code. CoRR Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
2024	B	`conf`	Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication. PPoPP Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Langwen Huang, Piotr Luczynski, Saleh Ashkboosh, Florian Scheidl, Armon Carigiet, Chio Ge, Nabil Abubaker, Maciej Besta, Tal Ben-Nun, Torsten Hoefler
2024	J	`jnl`	Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication. CoRR Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Langwen Huang, Piotr Luczynski, Saleh Ashkboos, Florian Scheidl, Armon Carigiet, Chio Ge, Nabil Abubaker, Maciej Besta, Tal Ben-Nun, Torsten Hoefler
2024	—	`conf`	Autonomous Execution for Multi-GPU Systems: Compiler Support. SC Workshops Javid Baydamirli, Tal Ben-Nun, Didem Unat
2024	J	`jnl`	ComPile: A Large IR Dataset from Production Sources. J. Data-centric Mach. Learn. Res. Aiden Grossman, Ludger Paehler, Konstantinos Parasyris, Tal Ben-Nun, Jacob Hegna, William S. Moses, Jose Manuel Monsalve Diaz, Mircea Trofin, Johannes Doerfert
2024	J	`jnl`	Lion Cub: Minimizing Communication Overhead in Distributed Lion. CoRR Satoki Ishikawa, Tal Ben-Nun, Brian Van Essen, Rio Yokota, Nikoli Dryden
2024	A	`conf`	Low-Depth Spatial Tree Algorithms. IPDPS Yves Baumann, Tal Ben-Nun, Maciej Besta, Lukas Gianinazzi, Torsten Hoefler, Piotr Luczynski
2024	J	`jnl`	Low-Depth Spatial Tree Algorithms. CoRR Yves Baumann, Tal Ben-Nun, Maciej Besta, Lukas Gianinazzi, Torsten Hoefler, Piotr Luczynski
2023	J	`jnl`	A Theory of I/O-Efficient Sparse Neural Network Inference. CoRR Niels Gleinig, Tal Ben-Nun, Torsten Hoefler
2023	A	`conf`	Bridging Control-Centric and Data-Centric Optimization. CGO Tal Ben-Nun, Berke Ates, Alexandru Calotoiu, Torsten Hoefler
2023	J	`jnl`	Bridging Control-Centric and Data-Centric Optimization. CoRR Tal Ben-Nun, Berke Ates, Alexandru Calotoiu, Torsten Hoefler
2023	J	`jnl`	Cached Operator Reordering: A Unified View for Fast GNN Training. CoRR Julia Bazinska, Andrei Ivanov, Tal Ben-Nun, Nikoli Dryden, Maciej Besta, Siyuan Shen, Torsten Hoefler
2023	J	`jnl`	ComPile: A Large IR Dataset from Production Sources. CoRR Aiden Grossman, Ludger Paehler, Konstantinos Parasyris, Tal Ben-Nun, Jacob Hegna, William S. Moses, Jose Manuel Monsalve Diaz, Mircea Trofin, Johannes Doerfert
2023	A	`conf`	FuzzyFlow: Leveraging Dataflow To Find and Squash Program Optimization Bugs. SC Philipp Schaad, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Alexandros Nikolaos Ziogas, Torsten Hoefler
2023	J	`jnl`	FuzzyFlow: Leveraging Dataflow To Find and Squash Program Optimization Bugs. CoRR Philipp Schaad, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Alexandros Nikolaos Ziogas, Torsten Hoefler
2023	C	`conf`	Maximum Flows in Parametric Graph Templates. CIAC Tal Ben-Nun, Lukas Gianinazzi, Torsten Hoefler, Yishai Oltchik
2023	J	`jnl`	Maximum Flows in Parametric Graph Templates. CoRR Tal Ben-Nun, Lukas Gianinazzi, Torsten Hoefler, Yishai Oltchik
2023	A	`conf`	Performance Embeddings: A Similarity-Based Transfer Tuning Approach to Performance Optimization. ICS Lukas Trümper, Tal Ben-Nun, Philipp Schaad, Alexandru Calotoiu, Torsten Hoefler
2023	J	`jnl`	Performance Embeddings: A Similarity-based Approach to Automatic Performance Optimization. CoRR Lukas Trümper, Tal Ben-Nun, Philipp Schaad, Alexandru Calotoiu, Torsten Hoefler
2023	J	`jnl`	Performance on HPC Platforms Is Possible Without C++. Comput. Sci. Eng. Anshu Dubey, Tal Ben-Nun, Bradford L. Chamberlain, Bronis R. de Supinski, Damian W. I. Rouson
2023	J	`jnl`	STen: Productive and Efficient Sparsity in PyTorch. CoRR Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Saleh Ashkboos, Torsten Hoefler
2023	A	`conf`	VENOM: A Vectorized N: M Format for Unleashing the Power of Sparse Tensor Cores. SC Roberto L. Castro, Andrei Ivanov, Diego Andrade, Tal Ben-Nun, Basilio B. Fraguela, Torsten Hoefler
2023	J	`jnl`	VENOM: A Vectorized N: M Format for Unleashing the Power of Sparse Tensor Cores. CoRR Roberto L. Castro, Andrei Ivanov, Diego Andrade, Tal Ben-Nun, Basilio B. Fraguela, Torsten Hoefler
2022	A	`conf`	A data-centric optimization framework for machine learning. ICS Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler
2022	A	`conf`	Boosting Performance Optimization with Interactive Data Movement Visualization. SC Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
2022	J	`jnl`	Boosting Performance Optimization with Interactive Data Movement Visualization. CoRR Philipp Schaad, Tal Ben-Nun, Torsten Hoefler
2022	A	`conf`	Deinsum: Practically I/O Optimal Multi-Linear Algebra. SC Alexandros Nikolaos Ziogas, Grzegorz Kwasniewski, Tal Ben-Nun, Timo Schneider, Torsten Hoefler
2022	J	`jnl`	Deinsum: Practically I/O Optimal Multilinear Algebra. CoRR Alexandros Nikolaos Ziogas, Grzegorz Kwasniewski, Tal Ben-Nun, Timo Schneider, Torsten Hoefler
2022	J	`jnl`	ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast. CoRR Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler
2022	A*	`conf`	ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts. NeurIPS Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler
2022	A	`conf`	Lifting C semantics for dataflow optimization. ICS Alexandru Calotoiu, Tal Ben-Nun, Grzegorz Kwasniewski, Johannes de Fine Licht, Timo Schneider, Philipp Schaad, Torsten Hoefler
2022	A	`conf`	Productive Performance Engineering for Weather and Climate Modeling with Python. SC Tal Ben-Nun, Linus Groner, Florian Deconinck, Tobias Wicky, Eddie Davis, Johann Dahm, Oliver Elbert, Rhea George, Jeremy McGibbon, Lukas Trümper, Elynn Wu, Oliver Fuhrer, Thomas C. Schulthess, Torsten Hoefler
2022	J	`jnl`	Productive Performance Engineering for Weather and Climate Modeling with Python. CoRR Tal Ben-Nun, Linus Groner, Florian Deconinck, Tobias Wicky, Eddie Davis, Johann Dahm, Oliver Elbert, Rhea George, Jeremy McGibbon, Lukas Trümper, Elynn Wu, Oliver Fuhrer, Thomas C. Schulthess, Torsten Hoefler
2022	J	`jnl`	Python FPGA Programming with Data-Centric Multi-Level Design. CoRR Johannes de Fine Licht, Tiziano De Matteis, Tal Ben-Nun, Andreas Kuster, Oliver Rausch, Manuel Burger, Carl-Johannes Johnsen, Torsten Hoefler
2022	A	`conf`	Temporal Vectorization: A Compiler Approach to Automatic Multi-Pumping. ICCAD Carl-Johannes Johnsen, Tiziano De Matteis, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler
2022	J	`jnl`	Temporal Vectorization: A Compiler Approach to Automatic Multi-Pumping. CoRR Carl-Johannes Johnsen, Tiziano De Matteis, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler
2022	J	`jnl`	The spatial computer: A model for energy-efficient parallel computation. CoRR Lukas Gianinazzi, Tal Ben-Nun, Saleh Ashkboos, Yves Baumann, Piotr Luczynski, Torsten Hoefler
2021	J	`jnl`	A Data-Centric Optimization Framework for Machine Learning. CoRR Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler
2021	J	`jnl`	Breaking (Global) Barriers in Parallel Stochastic Optimization With Wait-Avoiding Group Averaging. IEEE Trans. Parallel Distributed Syst. Shigang Li, Tal Ben-Nun, Giorgi Nadiradze, Salvatore Di Girolamo, Nikoli Dryden, Dan Alistarh, Torsten Hoefler
2021	J	`jnl`	Clairvoyant Prefetching for Distributed Machine Learning I/O. CoRR Roman Böhringer, Nikoli Dryden, Tal Ben-Nun, Torsten Hoefler
2021	A	`conf`	Clairvoyant prefetching for distributed machine learning I/O. SC Nikoli Dryden, Roman Böhringer, Tal Ben-Nun, Torsten Hoefler
2021	—	`conf`	Data Movement Is All You Need: A Case Study on Optimizing Transformers. MLSys Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler
2021	J	`jnl`	Learning Combinatorial Node Labeling Algorithms. CoRR Lukas Gianinazzi, Maximilian Fries, Nikoli Dryden, Tal Ben-Nun, Maciej Besta, Torsten Hoefler
2021	J	`jnl`	Lifting C Semantics for Dataflow Optimization. CoRR Alexandru Calotoiu, Tal Ben-Nun, Grzegorz Kwasniewski, Johannes de Fine Licht, Timo Schneider, Philipp Schaad, Torsten Hoefler
2021	A	`conf`	NPBench: a benchmarking suite for high-performance NumPy. ICS Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler
2021	J	`jnl`	On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal Matrix Factorizations. CoRR Grzegorz Kwasniewski, Marko Kabic, Tal Ben-Nun, Alexandros Nikolaos Ziogas, Jens Eirik Saethre, André Gaillard, Timo Schneider, Maciej Besta, Anton Kozhevnikov, Joost VandeVondele, Torsten Hoefler
2021	B	`conf`	On the parallel I/O optimality of linear algebra kernels: near-optimal LU factorization. PPoPP Grzegorz Kwasniewski, Tal Ben-Nun, Alexandros Nikolaos Ziogas, Timo Schneider, Maciej Besta, Torsten Hoefler
2021	A	`conf`	On the parallel I/O optimality of linear algebra kernels: near-optimal matrix factorizations. SC Grzegorz Kwasniewski, Marko Kabic, Tal Ben-Nun, Alexandros Nikolaos Ziogas, Jens Eirik Saethre, André Gaillard, Timo Schneider, Maciej Besta, Anton Kozhevnikov, Joost VandeVondele, Torsten Hoefler
2021	B	`conf`	Pebbles, Graphs, and a Pinch of Combinatorics: Towards Tight I/O Lower Bounds for Statically Analyzable Programs. SPAA Grzegorz Kwasniewski, Tal Ben-Nun, Lukas Gianinazzi, Alexandru Calotoiu, Timo Schneider, Alexandros Nikolaos Ziogas, Maciej Besta, Torsten Hoefler
2021	J	`jnl`	Pebbles, Graphs, and a Pinch of Combinatorics: Towards Tight I/O Lower Bounds for Statically Analyzable Programs. CoRR Grzegorz Kwasniewski, Tal Ben-Nun, Lukas Gianinazzi, Alexandru Calotoiu, Timo Schneider, Alexandros Nikolaos Ziogas, Maciej Besta, Torsten Hoefler
2021	A*	`conf`	ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations. ICML Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle, Hugh Leather
2021	J	`jnl`	Productivity, Portability, Performance: Data-Centric Python. CoRR Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler
2021	A	`conf`	Productivity, portability, performance: data-centric Python. SC Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler
2021	J	`jnl`	Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks. CoRR Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste
2021	J	`jnl`	Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks. J. Mach. Learn. Res. Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste
2021	A	`conf`	StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems. CGO Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun, Dominic Hofer, Torsten Hoefler
2020	A*	`conf`	Augment Your Batch: Improving Generalization Through Instance Repetition. CVPR Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry
2020	J	`jnl`	Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging. CoRR Shigang Li, Tal Ben-Nun, Dan Alistarh, Salvatore Di Girolamo, Nikoli Dryden, Torsten Hoefler
2020	J	`jnl`	Data Movement Is All You Need: A Case Study on Optimizing Transformers. CoRR Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler
2020	J	`jnl`	Deep Data Flow Analysis. CoRR Chris Cummins, Hugh Leather, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle
2020	J	`jnl`	Deep Learning for Post-Processing Ensemble Weather Forecasts. CoRR Peter Grönquist, Chengyuan Yao, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Shigang Li, Torsten Hoefler
2020	J	`jnl`	Groute: Asynchronous Multi-GPU Programming Model with Applications to Large-scale Graph Processing. ACM Trans. Parallel Comput. Tal Ben-Nun, Michael Sutton, Sreepathi Pai, Keshav Pingali
2020	J	`jnl`	On the Parallel I/O Optimality of Linear Algebra Kernels: Near-Optimal LU Factorization. CoRR Grzegorz Kwasniewski, Tal Ben-Nun, Alexandros Nikolaos Ziogas, Timo Schneider, Maciej Besta, Torsten Hoefler
2020	J	`jnl`	Parametric Graph Templates: Properties and Algorithms. CoRR Tal Ben-Nun, Lukas Gianinazzi, Torsten Hoefler, Yishai Oltchik
2020	J	`jnl`	ProGraML: Graph-based Deep Learning for Program Optimization and Analysis. CoRR Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Hugh Leather
2020	J	`jnl`	StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems. CoRR Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun, Dominic Hofer, Torsten Hoefler
2020	J	`jnl`	Substream-Centric Maximum Matchings on FPGA. CoRR Maciej Besta, Marc Fischer, Tal Ben-Nun, Dimitri Stanojevic, Johannes de Fine Licht, Torsten Hoefler
2020	J	`jnl`	Substream-Centric Maximum Matchings on FPGA. ACM Trans. Reconfigurable Technol. Syst. Maciej Besta, Marc Fischer, Tal Ben-Nun, Dimitri Stanojevic, Johannes de Fine Licht, Torsten Hoefler
2020	B	`conf`	Taming unbalanced training workloads in deep learning with partial collective operations. PPoPP Shigang Li, Tal Ben-Nun, Salvatore Di Girolamo, Dan Alistarh, Torsten Hoefler
2020	—	`conf`	Workflows are the New Applications: Challenges in Performance, Portability, and Productivity. P3HPC@SC Tal Ben-Nun, Todd Gamblin, Daisy S. Hollman, Hari Krishnan, Chris J. Newburn
2019	J	`jnl`	A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations. CoRR Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler
2019	A	`conf`	A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning. IPDPS Tal Ben-Nun, Maciej Besta, Simon Huber, Alexandros Nikolaos Ziogas, Daniel Peter, Torsten Hoefler
2019	J	`jnl`	A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning. CoRR Tal Ben-Nun, Maciej Besta, Simon Huber, Alexandros Nikolaos Ziogas, Daniel Peter, Torsten Hoefler
2019	A	`conf`	A data-centric approach to extreme-scale SC Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler
2019	J	`jnl`	Augment your batch: better training with larger batches. CoRR Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry
2019	J	`jnl`	Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis. ACM Comput. Surv. Tal Ben-Nun, Torsten Hoefler
2019	J	`jnl`	Graph Processing on FPGAs: Taxonomy, Survey, Challenges. CoRR Maciej Besta, Dimitri Stanojevic, Johannes de Fine Licht, Tal Ben-Nun, Torsten Hoefler
2019	J	`jnl`	Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency. CoRR Elad Hoffer, Berry Weinstein, Itay Hubara, Tal Ben-Nun, Torsten Hoefler, Daniel Soudry
2019	J	`jnl`	Optimizing the Data Movement in Quantum Transport Simulations via Data-Centric Parallel Programming. CoRR Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler
2019	A	`conf`	Optimizing the data movement in quantum transport simulations via data-centric parallel programming. SC Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler
2019	J	`jnl`	Predicting Weather Uncertainty with Deep Convnets. CoRR Peter Grönquist, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Luca Lavarini, Shigang Li, Torsten Hoefler
2019	J	`jnl`	Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs. CoRR Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler
2019	A	`conf`	Stateful dataflow multigraphs: a data-centric model for performance portability on heterogeneous architectures. SC Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler
2019	A	`conf`	Substream-Centric Maximum Matchings on FPGA. FPGA Maciej Besta, Marc Fischer, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler
2019	J	`jnl`	Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations. CoRR Shigang Li, Tal Ben-Nun, Salvatore Di Girolamo, Dan Alistarh, Torsten Hoefler
2018	C	`conf`	Accelerating Deep Learning Frameworks with Micro-Batches. CLUSTER Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
2018	J	`jnl`	Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis. CoRR Tal Ben-Nun, Torsten Hoefler
2018	A*	`conf`	Neural Code Comprehension: A Learnable Representation of Code Semantics. NeurIPS Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler
2018	J	`jnl`	Neural Code Comprehension: A Learnable Representation of Code Semantics. CoRR Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler
2018	A	`conf`	Optimizing Parallel Graph Connectivity Computation via Subgraph Sampling. IPDPS Michael Sutton, Tal Ben-Nun, Amnon Barak
2018	J	`jnl`	μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching. CoRR Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka
2017	C	`conf`	Big data causing big (TLB) problems: taming random memory accesses on the GPU. DaMoN Tomas Karnagel, Tal Ben-Nun, Matthias Werner, Dirk Habich, Wolfgang Lehner
2017	B	`conf`	Groute: An Asynchronous Multi-GPU Programming Model for Irregular Computations. PPoPP Tal Ben-Nun, Michael Sutton, Sreepathi Pai, Keshav Pingali
2016	J	`jnl`	Adaptive Work-Efficient Connected Components on the GPU. CoRR Michael Sutton, Tal Ben-Nun, Amnon Barak, Sreepathi Pai, Keshav Pingali
2016	—	`ch.`	FFMK: A Fast and Fault-Tolerant Microkernel-Based System for Exascale Computing. Software for Exascale Computing Carsten Weinhold, Adam Lackorzynski, Jan Bierbaum, Martin Küttler, Maksym Planeta, Hermann Härtig, Amnon Shiloh, Ely Levy, Tal Ben-Nun, Amnon Barak, Thomas Steinke, Thorsten Schütt, Jan Fajerski, Alexander Reinefeld, Matthias Lieber, Wolfgang E. Nagel
2016	—	`—`	Memory-Oriented Programming : A Data-Centric Programming Model for Systems with Multiple Parallel Accelerators (שער נוסף בעברית: תכנות מונחה זיכרון : מודל תכנות עבור מערכות מרובות מאיצים מקביליים.). Tal Ben-Nun
2016	J	`jnl`	Reciprocal Grids: A Hierarchical Algorithm for Computing Solution X-ray Scattering Curves from Supramolecular Complexes at High Resolution. J. Chem. Inf. Model. Avi Ginsburg, Tal Ben-Nun, Roi Asor, Asaf Shemesh, Israel Ringel, Uri Raviv
2016	J	`jnl`	Spline-based parallel nonlinear optimization of function sequences. J. Parallel Distributed Comput. Tal Ben-Nun, Amnon Barak, Uri Raviv
2015	A	`conf`	Memory access patterns: the missing piece of the multi-GPU puzzle. SC Tal Ben-Nun, Ely Levy, Amnon Barak, Eri Rubin
2014	J	`jnl`	MAPS: Optimizing Massively Parallel Applications Using Device-Level Memory Abstraction. ACM Trans. Archit. Code Optim. Eri Rubin, Ely Levy, Amnon Barak, Tal Ben-Nun
2010	Misc	`conf`	Design and implementation of a generic resource sharing virtual time dispatcher. SYSTOR Tal Ben-Nun, Yoav Etsion, Dror G. Feitelson
2009	A	`conf`	A global scheduling framework for virtualization environments. IPDPS Yoav Etsion, Tal Ben-Nun, Dror G. Feitelson