Gpu Accelerated Parallel Branch Prediction For Multi/Many-Core Processor Simulation

Branch Prediction is a common function in nowadays microprocessors. Branch predictor is duplicated in each core of a multi/many-core processor and makes prediction for multiple concurrent running programs respectively. To evaluate the parallel branch prediction in a multi/many-core processor, existing schemes generally use a parallel simulator running on a CPU that does not have a real massive parallel running environment to support the simulation and thus has a bad simulating performance. In this paper, we use a real many-core platform, GPU, to perform a parallel simulation of branch prediction for the future general purpose multi/many-core processor design. We verify the correctness of the GPU based parallel branch predictor against the traditional CPU based branch predictor. Experiment result shows that the GPU based parallel simulation scheme obtains a two to ten times of speedup over the CPU platform when the issue rate ranging from one to four instructions per cycle, and it shows that the GPU based scheme is a promising way to improve the simulation speed for future multi/many-core processor research.