A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering

Abstract summary

The Two Level Perceptron design coordinates predictions about off-chip memory accesses with filtering of first-level cache prefetches. Its first predictor uses virtual-address features and selectively delays uncertain decisions; the second uses the resulting prediction alongside physical-address information to reject unhelpful prefetches. Experiments across single-core and multicore workloads examine how this coordination reduces memory traffic while improving performance.

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@misc{atwolevelneuralapproachcombiningoffchippredictionwithadaptiveprefetchfiltering,
  title = {A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering},
  author = {Alexandre Valentin Jamet and Georgios Vavouliotis and Daniel A. Jiménez and Lluc Alvarez and Marc Casas},
  year = {2024},
  note = {HPCA},
  url = {https://doi.org/10.1109/hpca57654.2024.00046}
}

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