20 citations · 27 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 7 cited
Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)
Daniel Coquelin, Charlotte Debus, Markus Götz +4
With increasing data and model complexities, the time required to train neural networks has become prohibitively large. To address the exponential rise in training time, users are…
cs.DC2020★ 20 cited
HeAT -- a Distributed and GPU-accelerated Tensor Framework for Data Analytics
Markus Götz, Daniel Coquelin, Charlotte Debus +9
To cope with the rapid growth in available data, the efficiency of data analysis and machine learning libraries has recently received increased attention. Although great advancemen…