Congratulations to our PhD student Rahul Bera and co-authors for their Best Paper Award at MICRO’22 for their work “Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction”!
What is Hermes?
The key idea behind Hermes is to: (1) accurately predict which load requests might go to off-chip, and (2) speculatively start fetching the data required by the predicted off-chip loads directly from the main memory in parallel to the cache accesses. Hermes proposes a lightweight, perceptron-based off-chip predictor that identifies off-chip load requests using multiple disparate program features. The predictor is implemented using only tables and simple arithmetic operations like increment and decrement.