To Share or Not To Share

Tuesday September 18, 2007
Hamerschlag Hall D-210
4:30 pm

This is a practice talk for VLDB 2007.

Ryan Johnson
Carnegie Mellon University

Intuitively, aggressive work sharing among concurrent queries in a database system should always improve performance by eliminating redundant computation or data accesses. We show that, contrary to common intuition, this is not always the case in practice, especially in the highly parallel world of chip multi-processors. As the number of cores in the system increases, a trade-off appears between exploiting work sharing opportunities and the available parallelism. To understand the trade-off, we develop an analytical approach that predicts the effect of work sharing in multi-core systems. Database engines can use the model to determine whether work sharing is beneficial and apply it only when appropriate, resulting in an average performance improvement of 20% and 2.5x, respectively, over never- and always-share policies.

Ryan Johnson is a PhD student working with the StagedDB project under Natassa Ailamaki. He received a M.S. ECE from Carnegie Mellon University and a B.S. ECE from Brigham Young University. His primary interests are architecture-aware computing and high performance database systems.