Morrigan: A Composite Instruction TLB Prefetcher

Abstract summary

Morrigan targets the instruction-translation misses caused by large server code footprints. It combines Markov-chain predictors with sequential prediction and locality within page tables. A frequency-sensitive replacement scheme preserves useful prediction history while adapting to changing execution phases. The resulting prefetcher aims to avoid demand page walks and reduce front-end stalls.

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@misc{morriganacompositeinstructiontlbprefetcher,
  title = {Morrigan: A Composite Instruction TLB Prefetcher},
  author = {Georgios Vavouliotis and Lluc Alvarez and Boris Grot and Daniel Jiménez and Marc Casas},
  year = {2021},
  note = {MICRO},
  url = {https://doi.org/10.1145/3466752.3480049}
}

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