Conditional branches frequently exhibit similar behavior (bias, time-varying behavior, ...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch cl...

Conditional branch induced control hazards cause significant performance loss in modern out-of-order superscalar processors. Dynamic branch prediction techniques help alleviate the penalties associated with conditional branch instructions. However, branches still constitute one of the main hurdles towards achieving higher ILP. Dynamic branch prediction relies on the temporal locality of and spa...

Understanding and Improving Operating System Effects in Control Flow Prediction Abstract Many modern applications exercise the operating system kernel significantly, resulting in several implications including affecting the control flow transfer in the execution environment. This paper focuses on understanding the operating system effects on control flow transfer and prediction, and designing a...

This paper describes a new on-demand wakeup prediction policy for instruction cache leakage control that achieves better leakage savings than prior policies, and avoids the performance overheads of prior policies. The proposed policy reduces leakage energy by more than 92% with only less than 0.3% performance overhead on average, whereas prior policies were either prone to severe performance ov...

This paper describes a new on-demand wakeup prediction policy for instruction cache leakage control that achieves better leakage savings than prior policies, and avoids the performance overheads of prior policies. The proposed policy reduces leakage energy by more than 92% with only less than 0.3% performance overhead on average. The key to this new on-demand policy is to use branch prediction ...

Program control flow transfer (branch) prediction is considered to be a performance hurdle and a key design issue for current and future microprocessors. Branch prediction schemes with high prediction accuracy have been proposed to support longer processor pipelines with higher frequency clocks. In the previously published literature, the design and evaluation of branch predictors have been bas...

In this paper we present mechanisms that improve the accuracy and performance of history-based branch prediction. By studying the characteristics of the decision structures present in high-level languages, two mechanisms are proposed that reduce the number of wrong predictions made by a branch target buer (BTB). Execution-driven modeling is used to evaluate the improvement in branch prediction ...

Historically, Markovian predictors have been very successful in predicting branch outcomes. In this work we propose a hybrid scheme that employs two Prediction by Partial Matching (PPM) Markovian predictors, one that predicts based on local branch histories and one based on global branch histories. The two independent predictions are combined using a neural network. On the CBP-2 traces the prop...

Branch prediction, i.e., predicting the outcome of a conditional branch instruction, is essential to the performance of current and future microprocessors. We show how perceptrons can be used to improve the state of the art in branch prediction. We explore the unusual challenges this domain presents for neural systems, and we show why other neural methods, such as back-propagation, provide no a...