Branch History Matching: Branch Predictor Warmup for Sampled Simulation

摘要

Computer architects and designers rely heavily on simulation. The downside of simulation is that it is very time-consuming — simulating an industry-standard benchmark on today's fastest machines and simulators takes several weeks. A practical solution to the simulation problem is sampling. Sampled simulation selects a number of sampling units out of a complete program execution and only simulates those sampling units in detail. An important problem with sampling however is the microarchitecture state at the beginning of each sampling unit. Large hardware structures such as caches and branch predictors suffer most from unknown hardware state. Although a great body of work exists on cache state warmup, very little work has been done on branch predictor warmup. This paper proposes Branch History Matching (BHM) for accurate branch predictor warmup during sampled simulation. The idea is to build a distribution for each sampling unit of how far one needs to go in the pre-sampling unit in order to find the same static branch with a similar global and local history as the branch instance appearing in the sampling unit. Those distributions are then used to determine where to start the warmup phase for each sampling unit for a given total warmup length budget. Using SPEC CPU2000 integer benchmarks, we show that BHM is substantially more efficient than fixed-length warmup in terms of warmup length for the same accuracy. Or reverse, BHM is substantially more accurate than fixed-length warmup for the same warmup budget.