کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
524311 | 868596 | 2006 | 20 صفحه PDF | دانلود رایگان |
Conventional auto-tuning numerical software has the drawbacks of (1) fixed sampling points for the performance estimation; (2) inadequate adaptation to heterogeneous environments. To solve these drawbacks, we developed ABCLib_DRSSED, which is a parallel eigensolver with an auto-tuning facility. ABCLib_DRSSED has (1) functions based on the sampling points which are constructed with an end-user interface; (2) a load-balancer for the data to be distributed; (3) a new auto-tuning optimization timing called Before Execute-time Optimization (BEO).In our performance evaluation of the BEO, we obtained speedup factors from 10% to 90%, and 340% in the case of a failed estimation. In the evaluation of the load-balancer, the performance was 220% improved.
Journal: Parallel Computing - Volume 32, Issue 3, March 2006, Pages 231–250