CRII: III: Buffer Management for Non-Volatile Memory

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Fifty years of research in database systems has focused on a canonical two-tier storage hierarchy with the volatile memory and durable storage technologies. A database system's buffer manager provides efficient access to data stored on storage by migrating it to volatile memory. The data migration policy employed by the buffer manager in existing systems is predicated on the assumptions that storage is orders of magnitude slower than volatile memory. But emerging non-volatile memory technologies are poised to upend these design assumptions. They provide fast accesses like volatile memory but with persistent writes like storage. The traditional approaches for buffer management are incompatible with this new hardware landscape. This project outlines a research agenda to study and develop novel buffer management techniques for non-volatile memory. The project will result in algorithms for shrinking the cost of large-scale in-memory data processing. The key lessons learned from this project will be integrated into the graduate-level course on database systems at Georgia Tech, educating students about the challenges and opportunities in non-volatile memory database systems.The technical aims of the project are divided into three interacting research thrusts. The first thrust develops a taxonomy of data migration policies for volatile and non-volatile memory technologies. What makes this different than earlier attempts is that the buffer manager will dynamically leverage all the data flow paths enabled by non-volatile memory to improve the database system's performance. The second thrust develops a machine-learning model for automatically tuning the data migration policy for an arbitrary workload and storage hierarchy. Due to the unique price, capacity, and performance characteristics of non-volatile memory, it will be challenging for database administrators to size the different levels of a multi-tier storage hierarchy. The third thrust develops a storage system recommender to help administrators identify the optimal hierarchy for their target workloads. These three research thrusts will be complemented by a comprehensive evaluation plan. This research effort will have a profound impact on the adoption of non-volatile memory technologies and will enable cost-effective, large-scaledata processing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.