The effects of context switching on branch predictor performance

Abstract

This paper shows that context switching is not a significant factor to be considered when performing general branch prediction studies. Branch prediction allows for speculative execution by increasing available instruction level parallelism (ILP) and hiding the time required to resolve branch conditions. Accurate simulation of branch prediction is important because branch prediction strongly influences the behavior of processor structures. For this study, a timesharing framework was developed by modifying SimpleScalar's branch predictor simulator. A thorough characterization of the effects of branch predictor configuration, branch predictor area, and time slice length is provided. As further verification, branch predictor performance with and without flushing the predictor structures is compared. Experiments show that operating system context switches have little effect on branch prediction rate when using time slices representative of today's operating systems. Our findings show that this results from the fact that time slices are much larger than the training time required by the branch predictor structures. For all predictor configurations tested, the predictors train in under 128K instructions with or without flushing the branch predictor structures.