91 citations · 146 across the 7 of their papers we have counts for
7 papers
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…
Reduced Precision Strategies for Deep Learning: A High Energy Physics Generative Adversarial Network Use Case
Florian Rehm, Sofia Vallecorsa, Vikram Saletore +5
Deep learning is finding its way into high energy physics by replacing traditional Monte Carlo simulations. However, deep learning still requires an excessive amount of computation…
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…
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…
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…
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train
Valeriu Codreanu, Damian Podareanu, Vikram Saletore
For the past 5 years, the ILSVRC competition and the ImageNet dataset have attracted a lot of interest from the Computer Vision community, allowing for state-of-the-art accuracy to…