Research focus
About the research
Can mathematical locality measures predict and minimize data movement across cache hierarchies to improve program performance and energy efficiency?
Read the full research overview
The research develops formal locality theory and reuse-distance models to quantify data movement and working-set behavior across memory levels. The group designs compiler and runtime techniques, including cache hints and programmable caches, that translate locality metrics into code and cache-control optimizations. Researchers analyze data movement complexity and develop tools for benchmarking and modeling CPU/GPU cache behavior to guide optimizations. Work also addresses parallel-memory allocation and locality-aware runtime systems to reduce contention and improve scalable performance.
Selected publications
Publication highlights haven’t been added. Explore the official research profile ↗
People & alumni
Team details haven’t been added. See the lab’s website for its current members.
Alumni details haven’t been added. Check the lab’s official website.
Sources & listing information
Find Research Labs maintains this page using public sources. The faculty member, lab, and university have not claimed or approved this listing. Listing a lab does not indicate endorsement, partnership, or a recruiting opportunity.
Request a correction or removal ↗ · About directory listings