Tal Ben-Nun

According to our database, Tal Ben-Nun authored at least 74 papers between 2009 and 2024.

Collaborative distances:

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

2024

Arrow Matrix Decomposition: A Novel Approach for Communication-Efficient Sparse Matrix Multiplication.

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

Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2024

Low-Depth Spatial Tree Algorithms.

Yves Baumann, Tal Ben-Nun, Maciej Besta, Lukas Gianinazzi, Torsten Hoefler, Piotr Luczynski

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2024

2023

Arrow Matrix Decompositions.

Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Piotr Luczynski, Saleh Ashkboosh, Langwen Huang, Florian Scheidl, Chio Ge, Armon Carigiet, Maciej Besta, Tal Ben-Nun, Torsten Hoefler

Dataset, April, 2023

Performance on HPC Platforms Is Possible Without C++.

Anshu Dubey, Tal Ben-Nun, Bradford L. Chamberlain, Bronis R. de Supinski, Damian W. I. Rouson

Comput. Sci. Eng., 2023

ComPile: A Large IR Dataset from Production Sources.

Aiden Grossman, Ludger Paehler, Konstantinos Parasyris, Tal Ben-Nun, Jacob Hegna, William S. Moses, Jose Manuel Monsalve Diaz, Mircea Trofin, Johannes Doerfert

CoRR, 2023

Cached Operator Reordering: A Unified View for Fast GNN Training.

Julia Bazinska, Andrei Ivanov, Tal Ben-Nun, Nikoli Dryden, Maciej Besta, Siyuan Shen, Torsten Hoefler

CoRR, 2023

STen: Productive and Efficient Sparsity in PyTorch.

Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Saleh Ashkboos, Torsten Hoefler

CoRR, 2023

Performance Embeddings: A Similarity-based Approach to Automatic Performance Optimization.

Lukas Trümper, Tal Ben-Nun, Philipp Schaad, Alexandru Calotoiu, Torsten Hoefler

CoRR, 2023

A Theory of I/O-Efficient Sparse Neural Network Inference.

Niels Gleinig, Tal Ben-Nun, Torsten Hoefler

CoRR, 2023

FuzzyFlow: Leveraging Dataflow To Find and Squash Program Optimization Bugs.

Philipp Schaad, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Alexandros Nikolaos Ziogas, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2023

VENOM: A Vectorized N: M Format for Unleashing the Power of Sparse Tensor Cores.

Roberto L. Castro, Andrei Ivanov, Diego Andrade, Tal Ben-Nun, Basilio B. Fraguela, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2023

Performance Embeddings: A Similarity-Based Transfer Tuning Approach to Performance Optimization.

Lukas Trümper, Tal Ben-Nun, Philipp Schaad, Alexandru Calotoiu, Torsten Hoefler

Proceedings of the 37th International Conference on Supercomputing, 2023

Maximum Flows in Parametric Graph Templates.

Tal Ben-Nun, Lukas Gianinazzi, Torsten Hoefler, Yishai Oltchik

Proceedings of the Algorithms and Complexity - 13th International Conference, 2023

Bridging Control-Centric and Data-Centric Optimization.

Tal Ben-Nun, Berke Ates, Alexandru Calotoiu, Torsten Hoefler

Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization, 2023

2022

Python FPGA Programming with Data-Centric Multi-Level Design.

Johannes de Fine Licht, Tiziano De Matteis, Tal Ben-Nun, Andreas Kuster, Oliver Rausch, Manuel Burger, Carl-Johannes Johnsen, Torsten Hoefler

CoRR, 2022

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecast.

Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler

CoRR, 2022

Deinsum: Practically I/O Optimal Multilinear Algebra.

Alexandros Nikolaos Ziogas, Grzegorz Kwasniewski, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

CoRR, 2022

The spatial computer: A model for energy-efficient parallel computation.

Lukas Gianinazzi, Tal Ben-Nun, Saleh Ashkboos, Yves Baumann, Piotr Luczynski, Torsten Hoefler

CoRR, 2022

Deinsum: Practically I/O Optimal Multi-Linear Algebra.

Alexandros Nikolaos Ziogas, Grzegorz Kwasniewski, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Boosting Performance Optimization with Interactive Data Movement Visualization.

Philipp Schaad, Tal Ben-Nun, Torsten Hoefler

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Productive Performance Engineering for Weather and Climate Modeling with Python.

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

Proceedings of the SC22: International Conference for High Performance Computing, 2022

ENS-10: A Dataset For Post-Processing Ensemble Weather Forecasts.

Saleh Ashkboos, Langwen Huang, Nikoli Dryden, Tal Ben-Nun, Peter Dueben, Lukas Gianinazzi, Luca Kummer, Torsten Hoefler

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A data-centric optimization framework for machine learning.

Oliver Rausch, Tal Ben-Nun, Nikoli Dryden, Andrei Ivanov, Shigang Li, Torsten Hoefler

Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

Lifting C semantics for dataflow optimization.

Alexandru Calotoiu, Tal Ben-Nun, Grzegorz Kwasniewski, Johannes de Fine Licht, Timo Schneider, Philipp Schaad, Torsten Hoefler

Proceedings of the ICS '22: 2022 International Conference on Supercomputing, Virtual Event, June 28, 2022

Temporal Vectorization: A Compiler Approach to Automatic Multi-Pumping.

Carl-Johannes Johnsen, Tiziano De Matteis, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

2021

Breaking (Global) Barriers in Parallel Stochastic Optimization With Wait-Avoiding Group Averaging.

Shigang Li, Tal Ben-Nun, Giorgi Nadiradze, Salvatore Di Girolamo, Nikoli Dryden, Dan Alistarh, Torsten Hoefler

IEEE Trans. Parallel Distributed Syst., 2021

Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks.

Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, Alexandra Peste

J. Mach. Learn. Res., 2021

Learning Combinatorial Node Labeling Algorithms.

Lukas Gianinazzi, Maximilian Fries, Nikoli Dryden, Tal Ben-Nun, Maciej Besta, Torsten Hoefler

CoRR, 2021

Pebbles, Graphs, and a Pinch of Combinatorics: Towards Tight I/O Lower Bounds for Statically Analyzable Programs.

Grzegorz Kwasniewski, Tal Ben-Nun, Lukas Gianinazzi, Alexandru Calotoiu, Timo Schneider, Alexandros Nikolaos Ziogas, Maciej Besta, Torsten Hoefler

Proceedings of the SPAA '21: 33rd ACM Symposium on Parallelism in Algorithms and Architectures, 2021

Productivity, portability, performance: data-centric Python.

Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2021

On the parallel I/O optimality of linear algebra kernels: near-optimal matrix factorizations.

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

Proceedings of the International Conference for High Performance Computing, 2021

Clairvoyant prefetching for distributed machine learning I/O.

Nikoli Dryden, Roman Böhringer, Tal Ben-Nun, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2021

On the parallel I/O optimality of linear algebra kernels: near-optimal LU factorization.

Grzegorz Kwasniewski, Tal Ben-Nun, Alexandros Nikolaos Ziogas, Timo Schneider, Maciej Besta, Torsten Hoefler

Proceedings of the PPoPP '21: 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2021

Data Movement Is All You Need: A Case Study on Optimizing Transformers.

Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun, Shigang Li, Torsten Hoefler

Proceedings of the Fourth Conference on Machine Learning and Systems, 2021

NPBench: a benchmarking suite for high-performance NumPy.

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

Proceedings of the ICS '21: 2021 International Conference on Supercomputing, 2021

ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations.

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle, Hugh Leather

Proceedings of the 38th International Conference on Machine Learning, 2021

StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems.

Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun, Dominic Hofer, Torsten Hoefler

Proceedings of the IEEE/ACM International Symposium on Code Generation and Optimization, 2021

2020

Substream-Centric Maximum Matchings on FPGA.

Maciej Besta, Marc Fischer, Tal Ben-Nun, Dimitri Stanojevic, Johannes de Fine Licht, Torsten Hoefler

ACM Trans. Reconfigurable Technol. Syst., 2020

Groute: Asynchronous Multi-GPU Programming Model with Applications to Large-scale Graph Processing.

Tal Ben-Nun, Michael Sutton, Sreepathi Pai, Keshav Pingali

ACM Trans. Parallel Comput., 2020

Deep Data Flow Analysis.

Chris Cummins, Hugh Leather, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael F. P. O'Boyle

CoRR, 2020

Parametric Graph Templates: Properties and Algorithms.

Tal Ben-Nun, Lukas Gianinazzi, Torsten Hoefler, Yishai Oltchik

CoRR, 2020

Deep Learning for Post-Processing Ensemble Weather Forecasts.

Peter Grönquist, Chengyuan Yao, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Shigang Li, Torsten Hoefler

CoRR, 2020

Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging.

Shigang Li, Tal Ben-Nun, Dan Alistarh, Salvatore Di Girolamo, Nikoli Dryden, Torsten Hoefler

CoRR, 2020

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis.

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Hugh Leather

CoRR, 2020

Workflows are the New Applications: Challenges in Performance, Portability, and Productivity.

Tal Ben-Nun, Todd Gamblin, Daisy S. Hollman, Hari Krishnan, Chris J. Newburn

Proceedings of the IEEE/ACM International Workshop on Performance, 2020

Taming unbalanced training workloads in deep learning with partial collective operations.

Shigang Li, Tal Ben-Nun, Salvatore Di Girolamo, Dan Alistarh, Torsten Hoefler

Proceedings of the PPoPP '20: 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020

Augment Your Batch: Improving Generalization Through Instance Repetition.

Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Demystifying Parallel and Distributed Deep Learning: An In-depth Concurrency Analysis.

Tal Ben-Nun, Torsten Hoefler

ACM Comput. Surv., 2019

A Data-Centric Approach to Extreme-Scale Ab initio Dissipative Quantum Transport Simulations.

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler

CoRR, 2019

Predicting Weather Uncertainty with Deep Convnets.

Peter Grönquist, Tal Ben-Nun, Nikoli Dryden, Peter Dueben, Luca Lavarini, Shigang Li, Torsten Hoefler

CoRR, 2019

Mix & Match: training convnets with mixed image sizes for improved accuracy, speed and scale resiliency.

Elad Hoffer, Berry Weinstein, Itay Hubara, Tal Ben-Nun, Torsten Hoefler, Daniel Soudry

CoRR, 2019

Graph Processing on FPGAs: Taxonomy, Survey, Challenges.

Maciej Besta, Dimitri Stanojevic, Johannes de Fine Licht, Tal Ben-Nun, Torsten Hoefler

CoRR, 2019

Stateful Dataflow Multigraphs: A Data-Centric Model for High-Performance Parallel Programs.

Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler

CoRR, 2019

Augment your batch: better training with larger batches.

Elad Hoffer, Tal Ben-Nun, Itay Hubara, Niv Giladi, Torsten Hoefler, Daniel Soudry

CoRR, 2019

Optimizing the data movement in quantum transport simulations via data-centric parallel programming.

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2019

A data-centric approach to extreme-scale <i>ab initio</i> dissipative quantum transport simulations.

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Guillermo Indalecio Fernández, Timo Schneider, Mathieu Luisier, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2019

Stateful dataflow multigraphs: a data-centric model for performance portability on heterogeneous architectures.

Tal Ben-Nun, Johannes de Fine Licht, Alexandros Nikolaos Ziogas, Timo Schneider, Torsten Hoefler

Proceedings of the International Conference for High Performance Computing, 2019

A Modular Benchmarking Infrastructure for High-Performance and Reproducible Deep Learning.

Tal Ben-Nun, Maciej Besta, Simon Huber, Alexandros Nikolaos Ziogas, Daniel Peter, Torsten Hoefler

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

Substream-Centric Maximum Matchings on FPGA.

Maciej Besta, Marc Fischer, Tal Ben-Nun, Johannes de Fine Licht, Torsten Hoefler

Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

2018

μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching.

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

CoRR, 2018

Neural Code Comprehension: A Learnable Representation of Code Semantics.

Tal Ben-Nun, Alice Shoshana Jakobovits, Torsten Hoefler

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Optimizing Parallel Graph Connectivity Computation via Subgraph Sampling.

Michael Sutton, Tal Ben-Nun, Amnon Barak

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Accelerating Deep Learning Frameworks with Micro-Batches.

Yosuke Oyama, Tal Ben-Nun, Torsten Hoefler, Satoshi Matsuoka

Proceedings of the IEEE International Conference on Cluster Computing, 2018

2017

Groute: An Asynchronous Multi-GPU Programming Model for Irregular Computations.

Tal Ben-Nun, Michael Sutton, Sreepathi Pai, Keshav Pingali

Proceedings of the 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2017

Big data causing big (TLB) problems: taming random memory accesses on the GPU.

Tomas Karnagel, Tal Ben-Nun, Matthias Werner, Dirk Habich, Wolfgang Lehner

Proceedings of the 13th International Workshop on Data Management on New Hardware, 2017

2016

FFMK: A Fast and Fault-Tolerant Microkernel-Based System 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

Proceedings of the Software for Exascale Computing - SPPEXA 2013-2015, 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

PhD thesis, 2016

Spline-based parallel nonlinear optimization of function sequences.

Tal Ben-Nun, Amnon Barak, Uri Raviv

J. Parallel Distributed Comput., 2016

Reciprocal Grids: A Hierarchical Algorithm for Computing Solution X-ray Scattering Curves from Supramolecular Complexes at High Resolution.

Avi Ginsburg, Tal Ben-Nun, Roi Asor, Asaf Shemesh, Israel Ringel, Uri Raviv

J. Chem. Inf. Model., 2016

Adaptive Work-Efficient Connected Components on the GPU.

Michael Sutton, Tal Ben-Nun, Amnon Barak, Sreepathi Pai, Keshav Pingali

CoRR, 2016

2015

Memory access patterns: the missing piece of the multi-GPU puzzle.

Tal Ben-Nun, Ely Levy, Amnon Barak, Eri Rubin

Proceedings of the International Conference for High Performance Computing, 2015

2014

MAPS: Optimizing Massively Parallel Applications Using Device-Level Memory Abstraction.

Eri Rubin, Ely Levy, Amnon Barak, Tal Ben-Nun

ACM Trans. Archit. Code Optim., 2014

2010

Design and implementation of a generic resource sharing virtual time dispatcher.

Tal Ben-Nun, Yoav Etsion, Dror G. Feitelson

Proceedings of of SYSTOR 2010: The 3rd Annual Haifa Experimental Systems Conference, 2010

2009

A global scheduling framework for virtualization environments.

Yoav Etsion, Tal Ben-Nun, Dror G. Feitelson

Proceedings of the 23rd IEEE International Symposium on Parallel and Distributed Processing, 2009