Reconsidering Complex Branch Predictors

نویسنده

  • Daniel A. Jiménez
چکیده

To sustain instruction throughput rates in more aggressively clocked microarchitectures, microarchitects have incorporated larger and more complex branch predictors into their designs, taking advantage of the increasing numbers of transistors available on a chip. Unfortunately, because of penalties associated with their implementations, the extra accuracy provided by many branch predictors does not produce a proportionate increase in performance. Specifically, we show that the techniques used to hide the latency of a large and complex branch predictor do not scale well and will be unable to sustain IPC for deeper pipelines. We investigate a different way to build large branch predictors. We propose an alternative predictor design that completely hides predictor latency so that accuracy and hardware budget are the only factors that affect the efficiency of the predictor. Our simple design allows the predictor to be pipelined efficiently by avoiding difficulties introduced by complex predictors. Because this predictor eliminates the penalties associated with complex predictors, overall performance exceeds that of even the most accurate known branch predictors in the literature at large hardware budgets. We conclude that as chip densities increase in the next several years, the accuracy of complex branch predictors must be weighed against the performance benefits of simple branch predictors.

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تاریخ انتشار 2003