کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
524238 | 868576 | 2007 | 11 صفحه PDF | دانلود رایگان |
We explore the applicability of the quadtree encoding method to the run-time MPI collective algorithm selection problem. Measured algorithm performance data was used to construct quadtrees with different properties. The quality and performance of generated decision functions and in-memory decision systems were evaluated. Experimental data shows that in some cases, a decision function based on a quadtree structure with a mean depth of three, incurs on average as little as a 5% performance penalty. In all cases, experimental data can be fully represented with a quadtree containing a maximum of six levels. Our results indicate that quadtrees may be a feasible choice for both processing of the performance data and automatic decision function generation.
Journal: Parallel Computing - Volume 33, Issue 9, September 2007, Pages 613–623