The Case for Domain-Specialized Branch Predictors for Graph-Processing

Branch prediction is believed by many to be a solved problem, with state-of-the-art predictors achieving near-perfect prediction for many programs. In this article, we conduct a detailed simulation of graph-processing workloads in the GAPBS benchmark suite and show that branch mispredictions occur frequently and are still a large limitation on performance in key graph-processing applications. We provide a detailed analysis of which branches are mispredicting and show that a few key branches are the main source of performance degradation across the graph-processing benchmarks we looked at. We also propose a few ideas for future work to improve branch prediction accuracy on graph workloads.