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Global Parallel Computation, Networks and Geometry

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We discuss implementations of distributed algorithms for a broad family of linear algebra problems which lead to perfect load balancing of data movement, storage and computation. The algorithms were likely first discovered by Karmarkar in the 1990’s leveraging finite projective geometries. From this approach, network topologies emerge which exhibit resilience, very low diameters and high cross sectional bandwidth. A few studies of these algorithms in software have shown significant speedup over current practice, subject to proper locality of ingest data. Silicon photonics may allow for effective implementation of the networks. While it has received little attention, this broad mixture of ideas appears to form a viable system architecture for parallel computing, but it also raises questions about implementation methodology and performance studies of parallel algorithms.

This talk is part of the Cavendish Astrophysics Seminars series.

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