امروز پنج شنبه , 01 شهریور 1403
شنبه تا پنج شنبه - 9 صبح الی 20 عصر
دانلود مقاله Parallel astronomical data processing with Python: Recipes for multicore machines 2013
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دانلود مقاله
Parallel astronomical data processing with Python: Recipes for multicore machines 2013
نویسندگان :
Navtej Singh, Lisa-Marie Browne, Ray Butler
فرمت: pdf
a b s t r a c t
High performance computing has been used in various fields of astrophysical research. But most of it
is implemented on massively parallel systems (supercomputers) or graphical processing unit clusters.
With the advent of multicore processors in the last decade, many serial software codes have been reimplemented
in parallel mode to utilize the full potential of these processors. In this paper, we propose
parallel processing recipes for multicore machines for astronomical data processing. The target audience
is astronomers who use Python as their preferred scripting language and who may be using PyRAF/IRAF
for data processing. Three problems of varied complexity were benchmarked on three different types
of multicore processors to demonstrate the benefits, in terms of execution time, of parallelizing data
processing tasks. The native multiprocessing module available in Python makes it a relatively trivial task
to implement the parallel code.Wehave also compared the three multiprocessing approaches—Pool/Map,
Process/Queue and Parallel Python. Our test codes are freely available and can be downloaded from our
website
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