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E. Wimmer:
"Is Gossip-inspired reduction competitive in high performance computing?";
Talk: International Workshop on Parallel Numerics (PARNUM 2017), Waischenfeld, Germany; 2017-04-19 - 2017-04-21.

The utility of gossip-based reduction algorithms in a High Performance Computing (HPC) context is investigated. They are compared to state-of-the-art deterministic parallel reduction
algorithms in terms of fault tolerance and resilience against silent data corruption (SDC) as well as in terms of runtime performance and scalability. New gossip-based reduction algorithms are proposed which significantly improve the state-of-the-art in terms of resilience
against SDC. A new gossip-inspired reduction algorithm is proposed which promises a more competitive runtime performance for low accuracy in an HPC context than gossip-based algorithms. It is shown that for very large systems the new gossip-inspired reduction algorithm has the potential to outperform classical reduction algorithm for low accuracy problems.