Abstract
Sparse grids are a popular approach for the numerical treatment of
high-dimensional problems. Where classical numerical discretization schemes
fail in more than three or four dimensions, sparse grids, in their different
flavors, are frequently the method of choice, be it spatially adaptive in the
hierarchical basis or via the dimensionally adaptive combination technique. The
third Workshop on Sparse Grids and Applications (SGA2014), which took place at
the University of Stuttgart from September 1 to 5 in 2014, demonstrated once
again the importance of this numerical discretization scheme. Organized by
Hans-Joachim Bungartz, Jochen Garcke, Michael Griebel, Markus Hegland, Dirk
Pflüger, and Clayton Webster, almost 60 participants from 8 different
countries have presented and discussed the current state of the art of sparse
grids and their applications. Thirty-eight talks covered their numerical
analysis as well as efficient data structures and new forms of adaptivity and a
range of applications from clustering and model order reduction to uncertainty
quantification settings and optimization. As a novelty, the topic
high-performance computing covered several talks, targeting exascale computing
and related tasks. Besides data structures and communication patterns with
excellent parallel scalability, fault tolerance was introduced to the SGA
series, the hierarchical approach providing novel approaches to the treatment
of hardware failures without checkpoint restart. This volume of LNCSE collects
selected contributions from attendees of the workshop
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