Pre- and Post Selection of Compiler Optimizations by Program Execution

In this paper, we investigate the combined use of static techniques and dynamic feedback information to achieve a high level of optimization of both compiler eeciency and code performance. In previous work, we have introduced a new compiler approach, iterative compilation, to select the best tile sizes and unrolling factors. In this approach, many versions of programs are generated and their worth is determined by the actual execution time. We found that this approach can obtain a much higher level of optimization than conventional static techniques. To further achieve both compiler eeciency and high code performance, we have incorporated cache models in the iterative compilation system. We utilize feedback information in two ways: Post-Selection and Pre-Selection. Experimental results show that even a very simple cache model can achieve a high level of optimization with Post-Selection verifying the worth of transformed programs, especially when the number of program executions is limited. Pre-Selection is superior if more program executions are allowed.