This paper studies the overall system power variations of two multi-core architectures, an 8-core Intel and a 32-core AMD workstation, while using these machines to execute a wide variety of sequential and multi-threaded benchmarks using varying compiler optimization settings and runtime configurations. Our extensive experimental study provides insights for answering two questions: 1) what degrees of impact can application level optimizations have on reducing the overall system power consumption of modern CMP architectures; and 2) what strategies can compilers and application developers adopt to achieve a balanced performance and power efficiency for applications from a variety of science and embedded systems domains.
Modern microprocessors have many microarchitectural features. Quantifying the performance impact of one feature such as dynamic branch prediction can be difficult. On one hand, a timing simulator can predict the difference in performance given two different implementations of the technique, but simulators can be quite inaccurate. On the other hand, real systems are very accurate representations of themselves, but often cannot be modified to study the impact of a new technique.We demonstrate how to develop a performance model for branch prediction using real systems based on object code reordering. By observing the behavior of the benchmarks over a range of branch prediction accuracies, we can estimate the impact of a new branch predictor by simulating only the predictor and not the rest of the microarchitecture.We also use the reordered object code to validate a reverseengineered model for the Intel Core 2 branch predictor. We simulate several branch predictors using Pin and measure which hypothetical branch predictor has the highest correlation with the real one.This study in object code reorder points to way to future work on estimating the impact of other structures such as the instruction cache, the second-level cache, instruction decoders, indirect branch prediction, etc.
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