Games Completed = 1000 of 1000 (Avg game length = 17.901 sec)
Settings = Gauntlet/0MB/6000ms+60ms/M 500cp for 2 moves, D 100 moves/EPD:C:\LittleBlitzer\2moves_v1.epd(32000)
Time = 4548 sec elapsed, 0 sec remaining
1. SF 256M 478.5/1000 172-215-613 (L: m=0 t=0 i=0 a=215) (D: r=425 i=55 f=6 s=9 a=118) (tpm=148.7 d=15.95 nps=1625641)
2. SF 4M 521.5/1000 215-172-613 (L: m=0 t=0 i=0 a=172) (D: r=425 i=55 f=6 s=9 a=118) (tpm=148.4 d=16.12 nps=1759164)
TC is 6''+0.06'', Hash needed is about 1-2M on average, I used SF with 4M Hash and 256M Hash. The NPS decrease is 8%, depth decrease of 0.17 plies, and 256M version is about 15 ELO points weaker.
hgm wrote:
IIRC in my measurements the search time only started to go up once the overload factor exeded 10.
That seems confirmed. In 1000 games each, about 60,000 positions per Stockfish with different Hash at 6''+0.06'' 1 core, I get the following depths and nps:
1. SF 1M tpm=148.0 d=16.14 nps=1951575 99%
2. SF 4M tpm=148.1 d=16.30 nps=1955569 80%
3. SF 16M tpm=149.3 d=16.36 nps=1946288 25%
4. SF 64M tpm=149.3 d=16.33 nps=1910916 7%
5. SF 256M tpm=149.5 d=16.25 nps=1817734 2%
6. SF 1024M tpm=149.4 d=16.14 nps=1718677 1%
The last column is approximate Hash usage per move out of available. 25% (16M Hash) seems the optimum here depth-wise. And indeed, a factor of 16 overload seems to not hurt almost at all (4M vs 64M).
Kohflote wrote:That is very interesting. Have you experiment the hash size for LTC such as 40 moves in 120 minutes or 180 minutes?
Thank you!
For this TC even on one core the optimum might be at 4GB, and that's the maximum Hash I can have on my PC. To go to much higher Hash to see what happens is impossible for me. Also, the testing time on many positions for reliability of the result would be huge.
hgm wrote:
IIRC in my measurements the search time only started to go up once the overload factor exeded 10.
That seems confirmed. In 1000 games each, about 60,000 positions per Stockfish with different Hash at 6''+0.06'' 1 core, I get the following depths and nps:
1. SF 1M tpm=148.0 d=16.14 nps=1951575 99%
2. SF 4M tpm=148.1 d=16.30 nps=1955569 80%
3. SF 16M tpm=149.3 d=16.36 nps=1946288 25%
4. SF 64M tpm=149.3 d=16.33 nps=1910916 7%
5. SF 256M tpm=149.5 d=16.25 nps=1817734 2%
6. SF 1024M tpm=149.4 d=16.14 nps=1718677 1%
The last column is approximate Hash usage per move out of available. 25% (16M Hash) seems the optimum here depth-wise. And indeed, a factor of 16 overload seems to not hurt almost at all (4M vs 64M).
I measured depth, nodes per second, and hash usage at 1.5 seconds per move from a set of positions (the 8238 positions from the sim tool; data extracted from Polyglot logs). I think the thinking time would equate to 1 to 1.2 seconds per move on your computer.
16 MB of hash seems to be best for this tpm and these positions on my computer. I was expecting a little more of a difference compared to your results.