A Customizable Auto-Tuning Scenario with User-Defined Code Transformations

At present, most of real-world HPC applications are being developed without considering any auto-tuning techniques; those applications are not "gauto-tunable" for several reasons. One reason is that making a code auto-tunable often results in messing up the code and degrading the readability and/or maintainability. In our previous work, we have employed a code transformation framework, Xevolver, for making a code auto-tunable without messing it up. However, there is no standardized way to express the collaboration between code transformation and auto-tuning. In this paper, therefore, we design a standard tuning scenario and some directives to customize the scenario for individual applications. Our case studies show that the scenario can be reusable among different applications and different auto-tuning techniques by only partially customizing it. As a result, in terms of the number of code lines, the proposed approach requires much less programming effort for achieving auto-tuning.