Using Value Prediction to Increase the Power of Speculative Execution Hardware

This paper presents an experimental and analytical study of value prediction and its impact on speculative execution in superscalar microprocessors. Value prediction is a new paradigm that suggests predicting outcome values of operations (at run-time) and using these predicted values to trigger the execution of true-data dependent operations speculatively. As a result, stalls to memory locations can be reduced and the amount of instruction-level parallelism can be extended beyond the limits of the program’s dataflow graph. This paper examines the characteristics of the value prediction concept from two perspectives: 1. the related phenomena that are reflected in the nature of computer programs, and 2. the significance of these phenomena to boosting instruction-level parallelism of super-scalar microprocessors that support speculative execution. In order to better understand these characteristics, our work combines both analytical and experimental studies.