activity
20172021
most citedScale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train

36 citations · 38 across the 3 of their papers we have counts for

collaborators

8 papers

cs.DC20212 cited

A Holistic Analysis of Datacenter Operations: Resource Usage, Energy, and Workload Characterization -- Extended Technical Report

Laurens Versluis, Mehmet Cetin, Caspar Greeven +5

Improving datacenter operations is vital for the digital society. We posit that doing so requires our community to shift, from operational aspects taken in isolation to holistic an…

astro-ph.IM2020

DeepGalaxy: Deducing the Properties of Galaxy Mergers from Images Using Deep Neural Networks

Maxwell X. Cai, Jeroen Bédorf, Vikram A. Saletore +4

Galaxy mergers, the dynamical process during which two galaxies collide, are among the most spectacular phenomena in the Universe. During this process, the two colliding galaxies a…

quant-ph2020

NetSquid, a NETwork Simulator for QUantum Information using Discrete events

Tim Coopmans, Robert Knegjens, Axel Dahlberg +13

In order to bring quantum networks into the real world, we would like to determine the requirements of quantum network protocols including the underlying quantum hardware. Because…

physics.ao-ph2020

Predicting atmospheric optical properties for radiative transfer computations using neural networks

Menno A. Veerman, Robert Pincus, Robin Stoffer +3

The radiative transfer equations are well-known, but radiation parametrizations in atmospheric models are computationally expensive. A promising tool for accelerating parametrizati…

cs.CE2020

Deep-learning enhancement of large scale numerical simulations

Caspar van Leeuwen, Damian Podareanu, Valeriu Codreanu +11

Traditional simulations on High-Performance Computing (HPC) systems typically involve modeling very large domains and/or very complex equations. HPC systems allow running large mod…

cs.LG2019

Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models

Derya Cavdar, Valeriu Codreanu, Can Karakus +11

Neural machine translation - using neural networks to translate human language - is an area of active research exploring new neuron types and network topologies with the goal of dr…