Abstract
This study considers a heterogeneous computing
system and corresponding workload being investigated
by the Extreme Scale Systems Center (ESSC) at Oak
Ridge National Laboratory (ORNL). The ESSC is part of
a collaborative effort between the Department of Energy
(DOE) and the Department of Defense (DoD) to deliver
research, tools, software, and technologies that can be
integrated, deployed, and used in both DOE and DoD
environments. The heterogeneous system and workload described
here are representative of a prototypical computing
environment being studied as part of this collaboration.
Each task can exhibit a time-varying importance or utility
to the overall enterprise. In this system, an arriving task
has an associated priority and precedence. The priority is
used to describe the importance of a task, and precedence
is used to describe how soon the task must be executed.
These two metrics are combined to create a utility function
curve that indicates how valuable it is for the system
to complete a task at any given moment. This research
focuses on using time-utility functions to generate a metric
that can be used to compare the performance of different
resource schedulers in a heterogeneous computing system.
The contributions of this paper are: (a) a mathematical
model of a heterogeneous computing system where tasks
arrive dynamically and need to be assigned based on their
priority, precedence, utility characteristic class, and task
execution type, (b) the use of priority and precedence to
generate time-utility functions that describe the value a
task has at any given time, (c) the derivation of a metric
based on the total utility gained from completing tasks to
measure the performance of the computing environment,
and (d) a comparison of the performance of resource
allocation heuristics in this environment.