Application-aware snoop filtering for low-power cache coherence in embedded multiprocessors

Authors:
Xiangrong Zhou;Chenjie Yu;Alokika Dash;Peter Petrov
Affiliations:
University of Maryland, College Park, MD;University of Maryland, College Park, MD;University of Maryland, College Park, MD;University of Maryland, College Park, MD
Venue:
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Year:
2008

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Abstract

Maintaining local caches coherently in shared-memory multiprocessors results in significant power consumption. The customization methodology we propose exploits the fact that in embedded systems, important knowledge is available to the system designers regarding memory sharing between tasks. We demonstrate how the snoop-induced cache probings can be significantly reduced by identifying and exploiting in a deterministic way the shared memory regions between the processors. Snoop activity is enabled only for the accesses referring to known shared regions. The hardware support is not only cost efficient, but also software programmable, which allows for reprogrammability and customization across different tasks and applications.