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📁 Design and building parallel program
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<B> Next:</B> <A NAME=tex2html3438 HREF="node121.html" tppabs="http://www.dit.hcmut.edu.vn/books/system/par_anl/node121.html"> Exercises</A>
<B>Up:</B> <A NAME=tex2html3436 HREF="node116.html" tppabs="http://www.dit.hcmut.edu.vn/books/system/par_anl/node116.html">10 Random Numbers</A>
<B> Previous:</B> <A NAME=tex2html3430 HREF="node119.html" tppabs="http://www.dit.hcmut.edu.vn/books/system/par_anl/node119.html">10.3 Distributed Random Generators</A>
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<H1><A NAME=SECTION04240000000000000000>10.4 Summary</A></H1>
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In this chapter, we have shown how one commonly used sequential random
number generator, the linear congruential method, can be adapted for
parallel execution.  This example shows how parallel computation can
introduce new issues even in apparently simple problems.  In the case
of random numbers, these issues include reproducibility, scalability,
the preservation of randomness, and the greater number of random
values consumed when executing on many processors.
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<B> Next:</B> <A NAME=tex2html3438 HREF="node121.html" tppabs="http://www.dit.hcmut.edu.vn/books/system/par_anl/node121.html"> Exercises</A>
<B>Up:</B> <A NAME=tex2html3436 HREF="node116.html" tppabs="http://www.dit.hcmut.edu.vn/books/system/par_anl/node116.html">10 Random Numbers</A>
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