Related Documents
Optimizing Communication Scheduling using Dataflow Semantics. Adrian Soviani, Jaswinder Pal Singh. International Conference on Parallel Processing (ICPP'09). PDF, slides
Presents how coarse grain dataflow semantics (CGD) can describe data and task parallelism at high level. Writing efficient codes is easier compared to message passing: communication and synchronization are added automatically and optimized for specific architectures; design space exploration and many high level optimizations require only redefining data distributions. The CGD implementation currently supports MPI, SHMEM, and pthreads, while benchmark results on SGI Altix 4700 show a 27% improvement for NPB FT, and a 41% improvement for the stencil micro-kernel.
A Hybrid SPMD - Coarse Grain Dataflow Parallel Programming Model. Adrian Soviani. preFPO defence, May 17th 2010. PDF
Discovering Performance Bottlenecks in Large Scale Parallel Applications. Presentation related to MOM4 project at Geofluid Dynamics Lab, Princeton. PDF