Tal Ben-Nun

Computer Science Postdoc
Member of the Scalable Parallel Computing Laboratory at ETH Zurich.
Former member of the Distributed Computing and the X-ray scattering labs at the Hebrew University of Jerusalem.
Former member of the Parallel Systems Lab at the Hebrew University of Jerusalem.


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Research
Data-Driven Programming Models

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Data movement minimization has become the most important factor in performance optimization. We make performance programming easier by rethinking existing paradigms, via new representations and workflows that expose optimization opportunities and utilize hardware efficiently.

Learnable Code Representations

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Machine learning on code can be challenging if it is treated as text. We create new intermediate representations of code that can be used for automatic comprehension and performance optimization.

Large-Scale Machine Learning

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Scaling machine learning to large clusters poses challenges, from I/O to optimizers. We tackle communication, neural network architectures, and reproducibility - from theory to practice.

Deep Learning for Scientific Computing

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Using deep neural networks and creating datasets to improve scientific computing applications. Examples include improving weather uncertainty quantification and deforestation prediction.

Software
  • DaCe - Data-Centric parallel programming framework for CPUs, GPUs, and FPGAs.
  • Deep500 - An HPC Deep Learning benchmark, competition, and meta-framework.
  • MAPS - Device-level GPU memory abstraction and code optimization library.
  • CUDNN Training - A CUDNN-based minimal deep learning training code sample using LeNet.
  • MGBench - Multi-GPU computing benchmark suite.
  • ceres-windows - Windows port of the ceres-solver nonlinear optimization library.
  • Klogger - A Linux Kernel Logging Framework.
  • X+ - Numerical Analysis Tool for Solution and Powder Scattering Structure Factor of Macromolecular Systems.
Selected Publications
(full list at Google Scholar)
Contact
Tal Ben-Nun
Room E 76, CAB Building
Department of Computer Science
Universit├Ątstrasse 6
8092 Z├╝rich
Switzerland

E-Mail Address: talbninf ethz ch