Pythia: A Customizable Hardware Prefetching Framework Using Online Reinforcement Learning

2 code implementations • 24 Sep 2021 • Rahul Bera, Konstantinos Kanellopoulos, Anant V. Nori, Taha Shahroodi, Sreenivas Subramoney, Onur Mutlu

In this paper, we make a case for designing a holistic prefetch algorithm that learns to prefetch using multiple different types of program context and system-level feedback information inherent to its design.

reinforcement-learning Reinforcement Learning (RL)

Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction

1 code implementation • 1 Sep 2022 • Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu

To this end, we propose a new technique called Hermes, whose key idea is to: 1) accurately predict which load requests might go off-chip, and 2) speculatively fetch the data required by the predicted off-chip loads directly from the main memory, while also concurrently accessing the cache hierarchy for such loads.

Sibyl: Adaptive and Extensible Data Placement in Hybrid Storage Systems Using Online Reinforcement Learning

1 code implementation • 15 May 2022 • Gagandeep Singh, Rakesh Nadig, Jisung Park, Rahul Bera, Nastaran Hajinazar, David Novo, Juan Gómez-Luna, Sander Stuijk, Henk Corporaal, Onur Mutlu

We introduce Sibyl, the first technique that uses reinforcement learning for data placement in hybrid storage systems.