Abstract. Optimized software development for symmetric multiprocessing systems,
especially the low-level ones, has always been hard in terms of achieving
sustainable operational level with reasonable effort and in acceptable time. Through
the process of personal electrical impedance mammograph software development
and debugging it was shown that major drawback of Harvard-type architecture,
implemented in modern AVR microprocessors, may be an issue in terms of precise
interrupt-driven synchronization between several elements of the multiprocessor
architecture because of the different length of commands and therefore often
unpredictable execution timing before finishing the very last command and
entering the particular interruption, that can be successfully mitigated in two
steps: initial configuration of the job that needs to be done with respect to
timing which should be followed by light sleep state and further
synchronization interruption that will be able to wake up the modules and
provide exact timing. It was also shown that during parallel usage of one UART
of the micro controller unit to serve two dependent units one may experience
frame errors unless UART reconfigured on demand. Utilization of any
python-based computational environments that support special kernels with
enhanced introspection and parallel computing clusters management with the help
of asynchronous status callbacks can significantly improve the development
process speeding up the debugging routine. It is shown in the example of
personal electrical impedance mammograph software development and debugging,
especially on the late stages of development when the level of abstraction gets
higher, particularly on the examples of experiment data results assessment on
multiple levels from raw data to reconstructed images.
Keywords: hardware and software system, multiprocessing system, synchronization
problem solving, debugging and development, python.
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