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2003
IEEE

Dynamic Data Dependence Tracking and its Application to Branch Prediction

11 years 5 days ago
Dynamic Data Dependence Tracking and its Application to Branch Prediction
To continue to improve processor performance, microarchitects seek to increase the effective instruction level parallelism (ILP) that can be exploited in applications. A fundamental limit to improving ILP is data dependences among instructions. If data dependence information is available at run-time, there are many uses to improve ILP. Prior published examples include decoupled branch execution architectures and critical instruction detection. In this paper, we describe an efficient hardware mechanism to dynamically track the data dependence chains of the instructions in the pipeline. This information is available on a cycle-by-cycle basis to the microengine for optimizing its performance. We then use this design in a new value-based branch prediction design using Available Register Value Information (ARVI). From the use of data dependence information, the ARVI branch predictor has better prediction accuracy over a comparably sized hybrid branch predictor. With ARVI used as the second...
Lei Chen, Steve Dropsho, David H. Albonesi
Added 01 Dec 2009
Updated 01 Dec 2009
Type Conference
Year 2003
Where HPCA
Authors Lei Chen, Steve Dropsho, David H. Albonesi
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