ANN: Dogelog Runtime, Prolog to the Moon (2021)
Mostowski Collapse
bursejan at gmail.com
Wed Sep 15 17:29:36 EDT 2021
Thank you for the suggestion. The test harness
is invoked as follows. So it does already do time/1,
thats also how I did the comparison Standard Python
and GraalVM Python, a file dogelog.py:
import sys
# sys.path.append("<path>\jekrun_bench\core\harness2\libpy")
sys.path.append("/mnt/c/<path>/jekrun_bench/core/harness2/libpy")
from index import init, consult
init()
consult(":- ['suite2.p']. "
":- time(suite). "
":- nl. "
":- time(suite). ")
Here you see a GraalVM cold and warm run.The warm run is faster.
If you do a warm warm run, it even gets more faster, because of
JIT-ing, Just-in-Time machine compilation,
via the GraalVM Truffles framework:
$ export PATH=<path>/graalvm-ce-java8-21.2.0/bin:$PATH
$ cd /mnt/c/<path>/jekrun_bench/core/harness2
$ graalpython /mnt/c/<path>/jekrun_bench/core/harness2/dogelog.py
nrev % Wall 6175 ms, gc 212 ms, 154473 lips
crypt % Wall 9327 ms, gc 63 ms, 112838 lips
deriv % Wall 4101 ms, gc 90 ms, 321890 lips
poly % Wall 3594 ms, gc 415 ms, 216299 lips
sortq % Wall 3427 ms, gc 67 ms, 290070 lips
tictac % Wall 2770 ms, gc 51 ms, 136580 lips
queens % Wall 3287 ms, gc 64 ms, 325617 lips
query % Wall 1432 ms, gc 77 ms, 382969 lips
mtak % Wall 2532 ms, gc 95 ms, 533881 lips
perfect % Wall 3980 ms, gc 76 ms, 290382 lips
% Wall 40745 ms, gc 1212 ms, 235751 lips
nrev % Wall 4508 ms, gc 112 ms, 211595 lips
crypt % Wall 6063 ms, gc 61 ms, 173584 lips
deriv % Wall 3150 ms, gc 42 ms, 419070 lips
poly % Wall 3549 ms, gc 432 ms, 219042 lips
sortq % Wall 3196 ms, gc 63 ms, 311036 lips
tictac % Wall 2670 ms, gc 52 ms, 141695 lips
queens % Wall 3087 ms, gc 60 ms, 346713 lips
query % Wall 1434 ms, gc 25 ms, 382435 lips
mtak % Wall 2596 ms, gc 90 ms, 520719 lips
perfect % Wall 3521 ms, gc 43 ms, 328236 lips
% Wall 33810 ms, gc 980 ms, 284108 lips
DFS schrieb am Mittwoch, 15. September 2021 um 23:15:07 UTC+2:
> On 9/15/2021 12:23 PM, Mostowski Collapse wrote:
> > I really wonder why my Python implementation
> > is a factor 40 slower than my JavaScript implementation.
> > Structurally its the same code.
> >
> > You can check yourself:
> >
> > Python Version:
> > https://github.com/jburse/dogelog-moon/blob/main/devel/runtimepy/machine.py
> >
> > JavaScript Version:
> > https://github.com/jburse/dogelog-moon/blob/main/devel/runtime/machine.js
> >
> > Its the same while, if-then-else, etc.. its the same
> > classes Variable, Compound etc.. Maybe I could speed
> > it up by some details. For example to create an array
> > of length n, I use in Python:
> >
> > temp = [NotImplemented] * code[pos]
> > pos += 1
> >
> > Whereas in JavaScript I use, also
> > in exec_build2():
> >
> > temp = new Array(code[pos++]);
> >
> > So I hear Guido doesn't like ++. So in Python I use +=
> > and a separate statement as a workaround. But otherwise,
> > what about the creation of an array,
> >
> > is the the idiom [_] * _ slow? I am assuming its
> > compiled away. Or does it really first create an
> > array of size 1 and then enlarge it?
> I'm sure you know you can put in timing statements to find bottlenecks.
>
> import time
> startTime = time.perf_counter()
> [code block]
> print("%.2f" % (time.perf_counter() - startTime))
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