Featherlight Reuse-Distance Measurement

Data locality has a profound impact on program performance. Reuse distance—the number of distinct memory locations accessed between two consecutive accesses to the same location—is the de facto, machine-independent metric of data locality in a program. Reuse distance measurement, typically, requires exhaustive instrumentation (code or binary) to log every memory access, which results in orders of magnitude runtime slowdown and memory bloat. Such high overheads impede reuse distance tools from adoption in long-running, production applications despite their usefulness. We develop RDX, a lightweight profiling tool for characterizing reuse distance in an execution; RDX typically incurs negligible time (5%) and memory (7%) overheads. RDX performs no instrumentation whatsoever but uniquely combines hardware performance counter sampling with hardware debug registers, both available in commodity CPU processors, to produce reuse-distance histograms. RDX typically has more than 90% accuracy compared to the ground truth. With the help of RDX, we are the first to characterize memory performance of long-running SPEC CPU2017 benchmarks. Keywords-Reuse distance; locality; hardware performance counters; debug registers; profiling.