Strategies for optimal operating point selection in timing speculative processors

Performance of timing speculative processors relies on strategies for accurate prediction of optimal operating points. In this paper, we develop an efficient process-variation-aware simulation framework and use it to evaluate a range of such timing speculation strategies. Our experiments on a timing speculative processor running applications from the MiBench benchmark suite show that, in a typical case, while a perfect timing speculation strategy can improve throughput by up to 143% over a guardbanded design, the most commonly used approach in the literature achieves only a 21.8% of the potential gains. By improving the speculation accuracy, the new strategies we propose in this paper can realize up to 35.6% of the potential gains, a throughput improvement of 50.9% over a guardbanded design.