On 20/03/14 04:03, Andy C wrote:
So, the following test puzzles me. Not because it takes virtually the
same time (I know that Fork/Join is not cheap and memory is probably
the biggest bottleneck here). But because I do not get why map (as
opposed to r/ma) uses all 8 cores on my MacBookPro. All of them seem
to be running according to Activity Monitor at more less the same level.
user=> (def l (into [] (range 60000000)))
#'user/l
user=> (time (def a (doall (map #(Math/sin (* % %)) l))))
"Elapsed time: 19986.18 msecs"
user=> (time (def a (doall (into [] (r/map #( Math/sin (* % %)) l)))))
"Elapsed time: 18980.583 msecs"
I would also expect this code to run on a single CPU at any one time,
however process/thread scheduling can make this thread run on different
cores at different times. Depending on the sampling method the activity
monitor may display another picture of what you would expect. On my
linux machine, the cpu history graph shows it's using mostly one cpu at
any one time, but it's not always the same cpu.
I think the JVM uses all cores by default, and there's no standard way
to specify thread affinity
<http://stackoverflow.com/questions/2238272/java-thread-affinity>.
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