2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (2016)
Chicago, IL, USA
May 23, 2016 to May 27, 2016
This paper introduces a new heterogeneous streaminglibrary called hetero Streams (hStreams). We show how asimple FIFO streaming model can be applied to heterogeneoussystems that include manycore coprocessors and multicore CPUs. This model supports concurrency across nodes, among taskswithin a node, and between data transfers and computation. Wegive examples for different approaches, show how the implementation can be layered, analyze overheads among layers, and apply those models to parallelize applications using simple, intuitive interfaces. We compare the features and versatility of hStreams, OpenMP, CUDA Streams and OmpSs. We show how the use of hStreams makes it easier for scientists to identify tasks and easily expose concurrency among them, and how it enables tuning experts and runtime systems to tailor execution for differentheterogeneous targets. Practical application examples are takenfrom the field of numerical linear algebra, commercial structuralsimulation software, and a seismic processing application.
Libraries, Graphics processing units, Concurrent computing, Data transfer, Semantics, Tuners, Parallel processing
C. J. Newburn et al., "Heterogeneous Streaming," 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Chicago, IL, USA, 2016, pp. 611-620.