On 03/11/2017 19:07, Makarius wrote:
On 03/11/17 19:26, Fabian Immler wrote:
I looked at it once more: profiling told me that IntInf.pow (in combination 
with Par_List.map) seems to be the culprit.

The following snippet shows similar behavior:
ML ‹
fun powers [] = []
  | powers (x::xs) = IntInf.pow (2, x mod 15)::powers xs;
Par_List.map (fn i => powers (i upto 100000 * i)) (0 upto 31)

polyml-5.6-1/x86_64-linux: 0:00:08 elapsed time, 0:00:35 cpu time, factor 4.02
polyml-test-e8d82343b692/x86_64-linux: 0:00:36 elapsed time, 0:03:26 cpu time, 
factor 5.70
polyml-5.6-1/x86_64-darwin:  0.570s elapsed time, 1.748s cpu time, 0.000s GC 
polyml-test-e8d82343b692/x86_64-darwin: 522.080s elapsed time, 568.676s cpu 
time, 42.602s GC time

I have discovered the same and have now pushed a workaround:

Somehow the IntInf.pow implementation in Poly/ML e8d82343b692 is a bit
wasteful, maybe during the bit vector operation instead of our
IntInf.divMod (_, 2) used here: see

I've had a look at this and pushed a change to IntInf.pow to Poly/ML master (c2a2961). It now uses Word.andb rather than IntInf.andb which avoids a call into the run-time system (RTS).

However, this code hadn't changed since 5.6 and when I tested it using List.map with 5.6 and 5.7.1 I didn't notice much difference; certainly not the massive differences you found with Par_List.map. The only thing I can think of is that there were so many calls into the RTS that there was some contention on a mutex and that was causing problems.

Anyway, try the new version and let me know the results.


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