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- W2055274745 abstract "The construction of distributed algorithms for matrix computations built on top of distributed data aggregation algorithms with randomized communication schedules is investigated. For this purpose, a new aggregation algorithm for summing or averaging distributed values, the push-flow algorithm, is developed, which achieves superior resilience properties with respect to node failures compared to existing aggregation methods. On a hypercube topology it asymptotically requires the same number of iterations as the optimal all-to-all reduction operation and it scales well with the number of nodes. Orthogonalization is studied as a prototypical matrix computation task. A new fault tolerant distributed orthogonalization method (rdmGS), which can produce accurate results even in the presence of node failures, is built on top of distributed data aggregation algorithms." @default.
- W2055274745 created "2016-06-24" @default.
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- W2055274745 date "2011-11-14" @default.
- W2055274745 modified "2023-09-25" @default.
- W2055274745 title "Robust distributed orthogonalization based on randomized aggregation" @default.
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- W2055274745 doi "https://doi.org/10.1145/2133173.2133177" @default.
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