An Experimental Evaluation of Smart Disk
Architectures Using DSS Commercial Workloads
Gokhan Memik, Mahmut T. Kandemir and Alok Choudhary
Abstract
Smart disk systems with large storage capacities and growing
computational power are becoming increasingly attractive. The idea is
to perform parallel and filtering-type of data intensive computations
on disks, close to data, thereby offloading the host processor and
increasing the aggregate system power. In this paper, we evaluate in
detail the performance of a host-based architecture and a smart disk
system using queries from Decision Support System (DSS) databases. We
show how to optimize the execution of the whole query being
implemented by bundling frequently occurring patterns together and
posting the bundle to the smart disks in a single invocation that
reduces unnecessary communication between host and smart disks. Using
an accurate simulator that can simulate the host-based as well as
smart-disk system, we illustrate that the smart disk architecture
brings substantial benefits in terms of overall query execution
times. In particular, in our base configuration, we are able to
achieve improvements over the traditional architecture by as much as
83.5% using representative queries from the TPC-D benchmark suite.