Hello,
Patric Michaud made some observations regarding parrot GC changes. The
basic findings are that parrot 3.0 with MS2 GC has the same execution
time of rakudo spectest as current parrot with GMS GC, current MS2
throughput is worse compared to parrot 3.0. He was wondering if GMS is
then better GC than MS2.
I think I know what causes the performance differences. Improved
tri-colour MS2 GC has landed in parrot 3.0. It did not have adaptive
triggering that the old MS GC had - it kicked out every 1/8 of system
memory allocated (if my memory serves me correctly). It wasted a lot of
memory and had long pauses. For example, on my system compiling rakudo
used 700+ M.
In parrot 3.1 Nick Wellnhofer have ported GC adaptive triggering system
from MS to MS2 GC core. It compiled rakudo in 400-500M but somewhat
slower because it kicked more frequently. It also had improved on
interactive loads - there were no long pauses.
GMS also landed at the same time in master - it does not have adaptive
triggering - it kicks minor collection on every 1/100 of system memory
allocated. Older generation GC is started on 10 younger generation
collection. It has 8 generations. So it wastes a lot less memory - it
could compile rakudo in 256M of RAM and have further improved
interactive behavior. Parrot with GMS compiles Rakudo in the same time
as MS2 without adaptive triggering but in 1/2-1/3 of the memory.
So, though execution times of GMS and MS2 (without adaptive triggering)
are similar, their other characteristics are quite different - GMS
wastes a lot less memory, has better interactive behavior etc.
I have also ported adaptive triggering system to GMS but the
performance was the same as current GMS. It wasted a lot more memory
(comparable to MS2 with adaptive triggering). The current triggering
system relies on the size of the youngest generation, adaptive
triggering system of MS2 depends on the size of all allocated memory and
complicates the things. Current GMS has more uniform pauses than GMS
with adaptive triggering. These are the causes I have dropped this first
experiment for adaptive triggering of GMS GC.
GMS has some tunable parameters but every tuning is compromise. So it
will be best to pick some sane defaults (we are not far from them on my
account) and provide mechanism to change them with parrot options. My
preliminary experiments show that 3-4 generations in GMS are enough and
there also a lot other variables to tune - I have not done the extensive
test in order to change the current defaults.
--
Luben Karavelov
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