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Parallel Computing for Data Science
book

Parallel Computing for Data Science

by Norman Matloff
November 2015
Intermediate to advanced
328 pages
10h 12m
English
CRC Press
Content preview from Parallel Computing for Data Science
8.5. EXAMPLE: FINDING PRIMES 199
msgsize 2 workers 3 workers 4 workers
1000 59.487 58.175 47.248
5000 22.855 17.541 15.454
10000 19.230 14.734 12.522
15000 19.198 14.874 12.689
25000 22.516 18.057 15.591
50000 23.029 18.573 16.114
Table 8.1: Timings, Prime Number Finding
8.5.4 Latency, Bandwdith and Parallelism
Another salient aspect here is that msgsize matters. Recall Section 2.5,
especially Equation (2.1). Let’s see how they affect things here.
In our timings above, setting the msgsize parameter to the lower value,
1000, results in having more chunks, thus more times that we incur the net-
work latency. On the other hand, a value of 50000 yields less
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Publisher Resources

ISBN: 9781466587014