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- Lorenz Hübschle-Schneider, Peter Sanders
- 2016 IEEE International Parallel and Distributed…
- 2016

We present scalable parallel algorithms with sublinear per-processor communication volume and low latency for several fundamental problems related to finding the most relevant elements in a set, for various notions of relevance: We begin with the classical selection problem with unsorted input. We present generalizations with sorted inputs, dynamic content… (More)

We study the problem of computing routes for electric vehicles (EVs) in road networks. Since their battery capacity is limited, and consumed energy per distance increases with velocity, driving the fastest route is often not desirable and may even be infeasible. On the other hand, the energy-optimal route may be too conservative in that it contains… (More)

We revisit tree compression with top trees (Bille et al. [3]), and present several improvements to the compressor and its analysis. By significantly reducing the amount of information stored and guiding the compression step using a RePair-inspired heuristic, we obtain a fast compressor achieving good compression ratios, addressing an open problem posed by… (More)

We consider the problem of sampling n numbers from the range {1, . . . , N} without replacement on modern architectures. The main result is a simple divide-and-conquer scheme that makes sequential algorithms more cache efficient and leads to a parallel algorithm running in expected time O(n/p+ log p) on p processors. The amount of communication between the… (More)

In the area of route planning for battery-electric vehicles, previous works have focused on finding routes that are optimal regarding energy consumption and/or travel time, only considering a fixed speed level for each road segment, and thus ignoring the staggering energy consumption savings potential attainable through variation of driving speed. While… (More)

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