Andreas G. Nowatzyk
Microsoft
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Publication
Featured researches published by Andreas G. Nowatzyk.
Journal of Parallel and Distributed Computing | 2013
Daniel Delling; Andrew V. Goldberg; Andreas G. Nowatzyk; Renato F. Werneck
Abstract We present a novel algorithm to solve the non-negative single-source shortest path problem on road networks and graphs with low highway dimension. After a quick preprocessing phase, we can compute all distances from a given source in the graph with essentially a linear sweep over all vertices. Because this sweep is independent of the source, we are able to reorder vertices in advance to exploit locality. Moreover, our algorithm takes advantage of features of modern CPU architectures, such as SSE and multiple cores. Compared to Dijkstra’s algorithm, our method needs fewer operations, has better locality, and is better able to exploit parallelism at multi-core and instruction levels. We gain additional speedup when implementing our algorithm on a GPU, where it is up to three orders of magnitude faster than Dijkstra’s algorithm on a high-end CPU. This makes applications based on all-pairs shortest-paths practical for continental-sized road networks. Several algorithms, such as computing the graph diameter, arc flags, or exact reaches, can be greatly accelerated by our method.
international parallel and distributed processing symposium | 2011
Daniel Delling; Andrew V. Goldberg; Andreas G. Nowatzyk; Renato F. Werneck
We present a novel algorithm to solve the nonnegative single-source shortest path problem on road networks and other graphs with low highway dimension. After a quick preprocessing phase, we can compute all distances from a given source in the graph with essentially a linear sweep over all vertices. Because this sweep is independent of the source, we are able to reorder vertices in advance to exploit locality. Moreover, our algorithm takes advantage of features of modern CPU architectures, such as SSE and multi-core. Compared to Dijkstras algorithm, our method needs fewer operations, has better locality, and is better able to exploit parallelism at multi-core and instruction levels. We gain additional speedup when implementing our algorithm on a GPU, where our algorithm is up to three orders of magnitude faster than Dijkstras algorithm on a high-end CPU. This makes applications based on all-pairs shortest-paths practical for continental-sized road networks. Several algorithms, such as computing the graph diameter, exact arc flags, or centrality measures (exact reaches or betweenness), can be greatly accelerated by our method.
Archive | 2012
Rod G. Fleck; Andreas G. Nowatzyk; John G. Bennett
Archive | 2012
Rod G. Fleck; David D. Bohn; Andreas G. Nowatzyk
Archive | 2012
Sasa Junuzovic; Kori Inkpen Quinn; Anoop Gupta; Aaron Hoff; Gina Venolia; Andreas G. Nowatzyk; Hrvoje Benko; Gavin Jancke; John C. Tang
Archive | 2011
Andreas G. Nowatzyk; Rod G. Fleck
Archive | 2012
Andreas G. Nowatzyk; Rod G. Fleck
Archive | 2012
Rod G. Fleck; Andreas G. Nowatzyk; David D. Bohn
Archive | 2011
Daniel Delling; Andrew V. Goldberg; Andreas G. Nowatzyk; Renato F. Werneck
Archive | 2012
Andreas G. Nowatzyk; David Rasmussen