Rename to insertion_sort so to avoid confusion
with std::sort, also move it to movepicker.cpp
and use the bit slower std::stable_sort in
search.cpp where it is used in not performance
critical paths.
No functional change.
Save the current active position in each Thread
instead of keeping a centralized array in struct
SplitPoint.
This allow to skip a memset() call at each split.
No functional change.
To return a pointer to the available
thread instead of a bool. This allows
to simplify the core loop in split().
No functional change.
Signed-off-by: Marco Costalba <mcostalba@gmail.com>
This function "returns" two values: bestValue and bestMove
Instead of returning one and passing as pointer the other
be consistent and pass as pointers both.
No functional change.
Currently a ttMove is reduced with ss->reduction = DEPTH_ZERO,
so it is actually not reduced (as it should be), but the
trick works just becuase it happens that ttMove is the first
to be tried and
reduction(depth, 1)
Always returns zero. So explicitly forbid reduction of ttMove
in the LMR condition. This is much clear and self-documented.
No functional change.
Handling of History and Gains is almost the same, with
the exception of the update logic, so unify both
classes under a single Stats struct.
No functional change.
Use a more traditional approach, along the same lines
of do_move().
It is true that we copy more in do_null_move(), but we
save the work in undo_null_move(). Speed test shows the
new code to be even a bit faster.
No functional change.
Fix again TimerThread::idle_loop() to prevent a
theoretical race with 'exit' flag in ~Thread().
Indeed in Thread d'tor we raise 'exit' and then
call notify() that is lock protected, so we
have to check again for 'exit' before going to
sleep in idle_loop().
Also same change in Thread::idle_loop() where we
now check for 'exit' before to go to sleep.
No functional change.
Signed-off-by: Marco Costalba <mcostalba@gmail.com>
Great code simplification: - instead do not futility
prune threat refutations. allows_move() is therefore removed.
4000 games at 50,000 nodes/move:
1085-989-1926 [51.2%] LOS=98.3%
4000 games in 10"+0.1"
756-751-2493 [50.1%] LOS=55.1%
EDIT: I have retested the patch of Lucas in a slightly different form
(without pruning in PvNode) and test mre or less confirms that
60 lines of code are totally unuseful:
After 6195 games at 15"+0.05"
1333 - 1325 - 3537 ELO 0
bench 5140990
Subclass MainThread and TimerThread and declare
idle_loop() virtual. This allow us to cleanly
remove a good bunch of hacks, relying on C++
polymorphism to do the job.
No functional change.
Rename it is_finished and use it only in main
thread to signal search is finished. This allows
us to simplify the complex SMP logic.
Ultra tricky patch: deep test is required under
wide conditions like pondering on and option
"Use Sleeping Threads" set to false.
No functional change.
Revert patch c581b7ea36
Seems a regression after testing from Gary:
ELO: 7.24 +- 99%: 17.03 95%: 12.93
LOS: 97.86%
Wins: 439 Losses: 381 Draws: 1962
And mine:
After 5410 games at 15"+0.05
Wins: 936 Losses: 1141 Draws: 3333 ELO -13
Moreover we know that there is a regression in the range
of patches which include the fromNull patch.
Probably this is not the only regression since 2.3.1 and
perhaps the idea under fromNull is good, but at the moment,
while in deep regression hunting, better to be on the safe
side and revert it entirely.
My guess on why this is a regression is that using the
negated evaluation of previous ply in case of null search
fails to take in account the king safety asymmetry between
the two colors. This is of course just a guess.
bench 5503830
Sometimes is faster, but not always and on very long mates
produces strange scores probably due to truncation of PV
artifacts.
So simply perform normal search also in case of UCI 'mate x'
command, with the only difference that when a mate in x is
found search returns immediately.
No functional change.
Following a user request I added the handling of UCI:
go mate x
Currently we just return from a PV node if x moves have been
done. Probably not the best approach. I have looked at Fruit/Toga
sources and there is even simpler: engine falls back on a fixed
depth search.
No functional change.
And return on using TT as backing store for position
evaluations.
Tests (even on single thread) show eval cache was a regression.
In multi thread result should be even worst because eval cache
is a per-thread struct, while TT is shared.
After 4957 games at 15"+0.05 (single thread)
eval cache vs master 969 - 1093 - 2895 -9 ELO
So previous reported result of +18 ELO was probably due to an
issue in the testing framework (a bug in cutechess-cli) that
has been fixed in the meanwhile.
bench: 5386711
In case of null search at low depths returns a fail low
due to a threat then, rather than return beta-1 (to cause
a re-search at full depth in the parent node), we set a flag
threatExtension = true (false by default) that will cause
moves that prevent the threat to be extended of one ply
in the following search.
Idea and patch is by Lucas Braesch.
Lucas also did the tests:
1500 games in 5"+0.05":
SF_threatExtension vs SF_20121222: 366 - 331 - 803 [51.2%] LOS=90.8%
3000 games in 10"+0.1":
SF_threatExtension vs SF_20121222: 610 - 559 - 1831 [50.8%] LOS=93.2%
Tests confirmed by Gary after 10570 games,
ELO: 2.79 +- 99%: 8.72 95%: 6.63
LOS: 94.08%
Wins: 1523 Losses: 1438 Draws: 7607
And finally by me at 15"+0.05, single thread, 3824 games
threatExtension vs master 768 - 692 - 2364 +7 ELO
bench 4918443
Test by Joona prooves the new feature don't value 70 added lines of code.
Grand totals after 10040 games (crashes: 0) for tt_both
master_9edc7 - 6a93488_6a934: 1756 - 1688 - 6596 ELO +2 (+- 2.7)
Confirmed by test of Gary:
After 8680 games:
ELO: 0.80 +- 99%: 9.62 95%: 7.31
LOS: 65.38%
Wins: 1288 Losses: 1268 Draws: 6130
Thanks a lot to both for testing it !!!
bench 5149248
This is more complex than what I'd like but I
was unable to split in small chunks.
Here we add 2 slots to TTEntry (valueUpper and depthUpper)
so that sizeof(TTEntry) returns to the original 16 bytes
and we can pack exactly 4 entries in a 64 bytes cache line.
Now we save an upper bound score alongside a lower (exact)
score. The idea is to increase TT cut-offs rates becuase
there is now an higher probability for a node to use TT info.
This patch is highly experimental and probably needs further
steps as is hinted by an unrealistic bench number:
bench: 2022385
In search(), after we evalute the position, in case there
isn't any TT entry we create one with just the evaluation
score.
This patches removes that code. The reason becuase the patch
deserves a single commit it is becuase introduces a (very small)
functional change due to the fact that the total number of
TT stores is less now and this slightly alters the TT hits
of our benchmark.
bench: 4983262
