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Dense Matrix Computation on a Heterogenous Architecture: A Block Synchronous Approach

We present a strategy for efficient use of all components of a heterogenous compute node of a typical current generation cluster. Such nodes often comprise multiple sockets with a multicore processor per socket and one or more accelerators, possibly from different generations and/or types. Our strategy differs from schedulers such as Quark or SuperMatrix in that it does not rely on a Directed Acyclic Graph, but rather uses a bulk-synchronous model. Also, it uses dynamic task division rather than aggregation to deal with the heterogeneous components of a node. Practical experiments show the merits of our approach.