CMU-SAFARI/Pythia-HDL

Implementation of Pythia: A Customizable Hardware Prefetching Framework Using Online Reinforcement Learning in Chisel HDL. To know more, please read the paper that appeared in MICRO 2021 by Bera et al. (https://arxiv.org/pdf/2109.12021.pdf).

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This project provides a hardware-realizable, lightweight data prefetcher that uses online reinforcement learning. It takes program context information from demand requests and outputs optimized prefetch decisions to improve memory access efficiency. Hardware architects and system designers can use this to integrate intelligent prefetching directly into their chip designs.

No commits in the last 6 months.

Use this if you are designing custom hardware and need an intelligent prefetching mechanism to reduce memory latency and improve system performance.

Not ideal if you are a software developer looking for a library to optimize application performance or if you need a pre-built hardware solution without custom integration.

hardware design processor architecture memory management chip design system-on-chip
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 13 / 25

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17

Forks

3

Language

Scala

License

MIT

Last pushed

Oct 09, 2021

Commits (30d)

0

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