Abstract:Profile data is valuable for identifying program hotspots and guiding optimizations. Traditional software profiling techniques incur significant overhead and are not suitable for DBT (Dynamic Binary Translation) systems. Hardware can support profile collection through either counters or timer interrupts that permit collection of statistical samples via software. Most hardware-support profiling systems can only achieve either high profile accuracy or low overhead. In this paper, we propose a novel profile appro… Show more
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