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Update README with DOI badge and paper reference
Added DOI badge for the MICRO 2024 paper and updated references.
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README.md

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<img alt="GitHub release" src="https://img.shields.io/github/v/release/dhschall/LLBP">
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</a>
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<a href="https://doi.org/10.5281/zenodo.13197409"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.13197409.svg" alt="Trace DOI"></a>
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<a href="https://doi.org/10.1109/MICRO61859.2024.00042"><img src="https://img.shields.io/badge/DOI-MICRO61859.2024.00042-blue" alt="Trace DOI"></a>
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<a href="https://github.com/dhschall/LLBP/actions/workflows/build-and-run.yml">
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<img alt="Build and test" src="https://github.com/dhschall/LLBP/actions/workflows/build-and-run.yml/badge.svg">
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</a>
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The Last-Level Branch Predictor (LLBP) is a microarchitectural approach that improves branch prediction accuracy through additional high-capacity storage backing the baseline TAGE predictor. The key insight is that LLBP breaks branch predictor state into multiple program contexts which can be thought of as a call chain. Each context comprises only a small number of patterns and can be prefetched ahead of time. This enables LLBP to store a large number of patterns in a high-capacity structure and prefetch only the patterns for the upcoming contexts into a small, fast structure to overcome the long access latency of the high-capacity structure (LLBP).
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LLBP is presented at [MICRO 2024](https://microarch.org/micro57/).
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LLBP is presented at [MICRO 2024](https://doi.org/10.1109/MICRO61859.2024.00042).
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This repository contains the source code of the branch predictor model used to evaluate LLBP's prediction accuracy. The code is based on the [CBP5 framework](http://www.jilp.org/cbp2016/), but was heavily modified and extended with various statistics to evaluate the performance of LLBP and the baseline TAGE predictor.
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@inproceedings{schall2024llbp,
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title={The Last-Level Branch Predictor},
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author={Schall, David and Sandberg, Andreas and Grot, Boris},
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booktitle={Proceedings of the 57th Annual IEEE/ACM International Symposium on Microarchitecture},
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year={2024}
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booktitle={2024 57th IEEE/ACM International Symposium on Microarchitecture (MICRO)},
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year={2024},
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pages={464-479},
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doi={10.1109/MICRO61859.2024.00042}
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}
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```
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David Schall - [GitHub](https://github.com/dhschall), [Website](https://dhschall.github.io/), [Mail](mailto:david.schall@tum.de)
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## Acknowledgements
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We thank all the anonymous reviewers of MICRO and the artifact evaluation team for their valuable feedback. Furthermore the members of the EASE-lab team at the University of Edinburgh as well as Arm Ltd. for their support and feedback.
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We thank all the anonymous reviewers of MICRO and the artifact evaluation team for their valuable feedback. Furthermore the members of the EASE-lab team at the University of Edinburgh as well as Arm Ltd. for their support and feedback.

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