Area-Aware Optimizations for Resource Constrained Branch Predictors Exploited in Embedded Processors

Modern embedded processors (e.g., Intel´s XScale) use small and simple branch predictors to improve performance. Such predictors impose little area and power overhead but may offer low accuracy. As a result, branch misprediction rate could be high. Such mispredictions result in longer program runtime and wasted activity. To address this inefficiency, we introduce two optimization techniques: first, we introduce an adaptive and low-complexity branch prediction technique. Our branch predictor removes up to a maximum of 50% of the branch mispredictions of a bimodal predictor. This results in improving performance by up to 16%. Second, we present front-end gating techniques and reduce wasted activity up to a maximum of 32%