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| author | Michele Simionato <michele.simionato@gmail.com> | 2010-08-31 08:07:03 +0200 |
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| committer | Michele Simionato <michele.simionato@gmail.com> | 2010-08-31 08:07:03 +0200 |
| commit | 33143cb11d6fb33d1c056220790cd1ee8a652975 (patch) | |
| tree | b519e70d3c1d3467cf142aa2c1efe59a79d78701 | |
| parent | 3df27dd0d7b5dd75a7c14b7c316975d96a3eec99 (diff) | |
| download | micheles-33143cb11d6fb33d1c056220790cd1ee8a652975.tar.gz | |
Micro fix to the docs
| -rw-r--r-- | plac/doc/plac_adv.txt | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/plac/doc/plac_adv.txt b/plac/doc/plac_adv.txt index 554847e..c679220 100644 --- a/plac/doc/plac_adv.txt +++ b/plac/doc/plac_adv.txt @@ -1026,7 +1026,7 @@ Parallel computing with plac plac_ is certainly not intended as a tool for parallel computing, but still you can use it to launch a set of commands and to collect the -results, similarly to the MapReduce pattern recently popularized by +results, similarly to the MapReduce pattern popularized by Google. In order to give an example, I will consider the "Hello World" of parallel computing, i.e. the computation of pi with independent processes. There is a huge number of algorithms to @@ -1074,11 +1074,11 @@ equally busy they should finish more or less at the same time). Here are the results on my old Macbook with Ubuntu 10.04 and Python 2.6, for 10 million of iterations:: - $ python picalculator.py -mP 10000000 + $ python picalculator.py -mP 10000000 # two processes 3.141904 in 5.744545 seconds - $ python picalculator.py -mT 10000000 + $ python picalculator.py -mT 10000000 # two threads 3.141272 in 13.875645 seconds - $ python picalculator.py -mS 10000000 + $ python picalculator.py -mS 10000000 # sequential 3.141586 in 11.353841 seconds As you see using processes one gets a 2x speedup indeed, where the threaded |