23 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.DC2019★ 1 cited
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism
Nikoli Dryden, Naoya Maruyama, Tom Benson +3
Scaling CNN training is necessary to keep up with growing datasets and reduce training time. We also see an emerging need to handle datasets with very large samples, where memory r…
cs.OH2016★ 23 cited
Doing Moore with Less -- Leapfrogging Moore's Law with Inexactness for Supercomputing
Sven Leyffer, Stefan M. Wild, Mike Fagan +4
Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness, where the quality of the solution can be traded for energy savings, has b…
cs.CE2013★ 1 cited
Software Abstractions and Methodologies for HPC Simulation Codes on Future Architectures
A. Dubey, S. Brandt, R. Brower +9
Large, complex, multi-scale, multi-physics simulation codes, running on high performance com-puting (HPC) platforms, have become essential to advancing science and engineering. The…