| Summary: | 博士 === 國立中正大學 === 資訊工程研究所 === 102 === The framework PoF is a performance-oriented framework which supports the modeldriven
development for multicore software. The framework contains four man components,
including the model parser, parallel code generator, monitor integrator and
the performance tuner. In the Thesis, the concepts of three main parallelism, i.e.,
task parallelism, data parallelism, and data flow parallelism, are described by SysML
activity diagram. The multicore software developers implement the three concept by
specifying the implementation or concept code and additional configuration information
in the specific components of activity diagram. The model parser parses the
implementation or concept code and the configuration information from the models,
and then passes to the parallel code generator to generate the corresponding skeleton
code and interface for each realization of parallelism, and put the specified user
code in the position where it should be. In order to tune the performance of multicore
software, the multicore monitoring system is designed and integrated into the
framework. Once the parallel code is generated, the monitor integrator inserts the
monitoring code in the parallel code, and the monitor system can access performance
data through the monitor code. The performance then evaluates the performance
data obtained from the monitor code, and tunes the configuration, such as the number
of threads, of the multicore software to achieve the optimal performance with
fewest computing resources, the processing cores of multicore architectures.
The main contributions of the Thesis include 1) the model-driven design of three
parallelism is proposed based on SysML activity diagram and the components of the multicore software models can be annotated into the corresponding parallel code, 2)
the multicore monitoring system is proposed and through the framework the monitoring
code is integrated in the generated parallel code, 3) the performance tuner
for general-purpose multicore applications is proposed and the experimental results
shows its excellent work than the other performance tuner.
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