1 research outputs found
Optimization of hybrid parallel application execution in heterogeneous high performance computing systems considering execution time and power consumption
Many important computational problems require utilization of high performance
computing (HPC) systems that consist of multi-level structures combining higher
and higher numbers of devices with various characteristics. Utilizing full
power of such systems requires programming parallel applications that are
hybrid in two meanings: they can utilize parallelism on multiple levels at the
same time and combine together programming interfaces specific for various
types of computing devices.
The main goal of parallel processing is increasing the processing
performance, and therefore decreasing the application execution time. The
international HPC community is targeting development of "Exascale"
supercomputers (able to sustain floating point operations per second)
by the year 2020. One of the main obstacles to achieving this goal is power
consumption of the computing systems that exceeds the energy supply limits. New
programming models and algorithms that consider this criterion are one of the
key areas where significant progress is necessary in order to achieve the goal.
The goal of the dissertation is to extract a general model of hybrid parallel
application execution in heterogeneous HPC systems that is a synthesis of
existing specific approaches and developing an optimization methodology for
such execution aiming for minimization of the contradicting objectives of
application execution time and power consumption of the utilized computing
hardware. Both meanings of the application hybridity result in multiplicity of
execution parameters of nontrivial interdependences and influence on the
considered optimization criteria. Mapping of the application processes on
computing devices has also a significant impact on these criteria.Comment: 127 pages, 25 figures. PhD thesis, Gda\'nsk University of Technology
(2018