Authors:
Kazuki Tsuzuku
and
Toshio Endo
Affiliation:
Tokyo Institute of Technology, Japan
Keyword(s):
GPGPU, Power Capping, DVFS, Power Model, Performance Model.
Related
Ontology
Subjects/Areas/Topics:
Energy and Economy
;
Energy Monitoring
;
Energy Profiling and Measurement
;
Energy-Aware Systems and Technologies
;
Optimization Techniques for Efficient Energy Consumption
Abstract:
Recent high performance computing (HPC) systems and supercomputers are built under strict power budgets
and the limitation will be even severer. Thus power control is becoming more important, especially on the
systems with accelerators such as GPUs, whose power consumption changes largely according to the characteristics
of application programs. In this paper, we propose an efficient power capping technique for compute
nodes with accelerators that supports dynamic voltage frequency scaling (DVFS). We adopt a hybrid approach
that consists of a static method and a dynamic method. By using a static method based on our power and performance
model, we obtain optimal frequencies of GPUs and CPUs for the given application. Additionally,
while the application is running, we adjust GPU frequency dynamically based on real-time power consumption.
Through the performance evaluation on a compute node with a NVIDIA GPU, we demonstrate that our
hybrid method successfully control the power
consumption under a given power constraint better than simple
methods, without aggravating energy-to-solution.
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