Let me start by thanking William Stein for making this machine
available.  I would like to run a parallel polynomial multiplication
benchmark on sage.math, however right now 16 cores are in use so
performance degrades after 8 threads (the program does not handle
heavy multitasking well).  Here are the results I am getting:

> read "sdmp.mpl":
> f := sdmp(expand((1+x+y+z+t)^30),plex(x,y,z,t),pack=4):
> g := sdmp(expand((1+x+y+z+t)^30+1),plex(x,y,z,t),pack=4):
> for i from 1 to 24 do sdmp:-num_cpus(i): p := sdmp:-Multiply(f,g): end do:
time: 57.260 sec   alg: 57.150 sec   io: 0.110 sec   real: 57.190
sec   0.999x
time: 54.430 sec   alg: 54.300 sec   io: 0.130 sec   real: 27.236
sec   1.994x
time: 56.320 sec   alg: 56.200 sec   io: 0.120 sec   real: 18.788
sec   2.991x
time: 54.760 sec   alg: 54.660 sec   io: 0.100 sec   real: 13.721
sec   3.984x
time: 52.480 sec   alg: 52.360 sec   io: 0.120 sec   real: 10.539
sec   4.968x
time: 51.920 sec   alg: 51.810 sec   io: 0.110 sec   real: 8.713 sec
5.946x
time: 52.040 sec   alg: 51.930 sec   io: 0.110 sec   real: 7.533 sec
6.894x
time: 54.660 sec   alg: 54.550 sec   io: 0.110 sec   real: 7.117 sec
7.665x
time: 57.200 sec   alg: 57.080 sec   io: 0.120 sec   real: 6.573 sec
8.684x
time: 57.600 sec   alg: 57.480 sec   io: 0.120 sec   real: 6.024 sec
9.542x
time: 63.730 sec   alg: 63.610 sec   io: 0.120 sec   real: 6.907 sec
9.209x
time: 65.130 sec   alg: 65.010 sec   io: 0.120 sec   real: 6.720 sec
9.674x
time: 74.280 sec   alg: 74.160 sec   io: 0.120 sec   real: 7.944 sec
9.336x
time: 106.240 sec   alg: 106.110 sec   io: 0.130 sec   real: 10.251
sec   10.351x
time: 97.920 sec   alg: 97.790 sec   io: 0.130 sec   real: 10.064
sec   9.717x
Interrupted
>

Would it be possible to arrange a time when the machine is empty to
run this test ?  I would like to get a graph for a paper.  In return,
I am happy to share the binary with the sage community so you can do
experiments with parallel computer algebra.  You can find the binary
in /home/mmonagan/sdmp  start Maple and read in sdmp.mpl. Sorry no
source code (it has bugs anyway) but the paper should be very helpful
to anyone trying to implement something.

Roman Pearce
CECM/SFU
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