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A Hybrid Branch Prediction Scheme

机译:混合分支预测方案

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Providing accurate branch prediction is critical to exploit instruction level parallelism effectively. Some of the existing branch prediction methods are static: compilers use opcode information and profiling statistics to make predictions. Other branch prediction methods are dynamic: hardware uses execution history collected at run-time to make predictions. In this paper, we propose a hybrid branch prediction scheme that combines hardware and software techniques to improve the branch prediction accuracy. This hybrid scheme integrates an improved static branch prediction and a new dynamic branch predictor. The dynamic branch predictor consists of a "Switch-Counter" in addition to a two-level adaptive branch predictor. Using trace-driven simulation on SPEC95 benchmarks, the results indicate that this scheme provides an improvement over the existing branch prediction methods at similar hardware cost.
机译:提供精确的分支预测对于有效地利用指示水平并行性至关重要。一些现有分支预测方法是静态:编译器使用Opcode信息和分析统计数据来进行预测。其他分支预测方法是动态:硬件使用在运行时收集的执行历史记录来进行预测。在本文中,我们提出了一种混合分支预测方案,其结合了硬件和软件技术来提高分支预测精度。该混合方案集成了改进的静态分支预测和新的动态分支预测因子。除了双级自适应分支预测器之外,动态分支预测器还包括“交换机计数器”。在SPEM95基准上使用痕量仿真,结果表明该方案以类似的硬件成本提供了对现有分支预测方法的改进。

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