Scheduling Multiple Data Visualization Query Workloads on a Shared
Memory Machine
Scheduling Multiple Data Visualization Query Workloads on a Shared
Memory Machine
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Date
2001-10-10
Authors
Andrade, Henrique
Kurc, Tahsin
Sussman, Alan
Saltz, Joel
Advisor
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DRUM DOI
Abstract
Query scheduling plays an important role when systems are faced with
limited resources and high workloads. It becomes even more relevant
for servers applying multiple query optimization techniques to batches of
queries, in which portions of datasets as well as intermediate results
are maintained in memory to speed up query evaluation. In this work,
we present a dynamic query scheduling model based on a
priority queue implementation using a directed graph and a strategy for ranking
queries. We examine the relative performance of four ranking strategies and compare them against a first-in first-out (FIFO) scheduling
strategy. We describe experimental results on a shared-memory machine
using two different versions of an application, called the Virtual
Microscope, for browsing digitized microscopy images.
(Also cross-referenced UMIACS-TR-2001-68)