Autotuning Algorithmic Choice for Input Sensitivity
Empirical autotuning is increasingly being used in many domains to achieve optimized performance in a variety of different execution environments. A daunting challenge faced by such autotuners is input sensitivity, where the best autotuned configuration may vary with different input sets. In this pa...
| Main Authors: | , , , , , |
|---|---|
| Other Authors: | |
| Published: |
2014
|
| Online Access: | http://hdl.handle.net/1721.1/88083 |