A new technique of embedding multigrain parallel HPRC in OR1200 a soft-core processor
SEPADS'12/EDUCATION'12 Proceedings of the 11th WSEAS international conference on Software Engineering, Parallel and Distributed Systems, and proceedings of the 9th WSEAS international conference on Engineering Education
Multi-core and many-core shared-memory parallel raycasting volume rendering optimization and tuning
International Journal of High Performance Computing Applications
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With the computing industry trending toward multi- and many-core processors, we study how a standard visualization algorithm, raycasting volume rendering, can benefit from a hybrid parallelism approach. Hybrid parallelism provides the best of both worlds: using distributed-memory parallelism across a large numbers of nodes increases available FLOPs and memory, while exploiting shared-memory parallelism among the cores within each node ensures that each node performs its portion of the larger calculation as efficiently as possible. We demonstrate results from weak and strong scaling studies, at levels of concurrency ranging up to 216,000, and with data sets as large as 12.2 trillion cells. The greatest benefit from hybrid parallelism lies in the communication portion of the algorithm, the dominant cost at higher levels of concurrency. We show that reducing the number of participants with a hybrid approach significantly improves performance.