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Rahul Bera committed Oct 12, 2022
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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.

Hermes was presented at MICRO 2022
Hermes was presented at MICRO 2022.

> _Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu, "Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction", In Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 2022_
> _Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu, "[Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction](https://arxiv.org/pdf/2209.00188.pdf)", In Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 2022_
## About The Framework

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