Author: Christophe Theron
Date: 10:56:49 05/02/00
Go up one level in this thread
On May 02, 2000 at 09:58:44, Robert Hyatt wrote:
>On May 02, 2000 at 01:41:23, Christophe Theron wrote:
>
>>On May 02, 2000 at 00:15:44, Christophe Theron wrote:
>>
>>>On May 01, 2000 at 23:36:30, Robert Hyatt wrote:
>>>
>>>>On May 01, 2000 at 22:50:50, Christophe Theron wrote:
>>>>
>>>>>On May 01, 2000 at 21:59:05, Robert Hyatt wrote:
>>>>>
>>>>>>On May 01, 2000 at 20:39:13, Christophe Theron wrote:
>>>>>>
>>>>>>>On May 01, 2000 at 18:50:24, Robert Hyatt wrote:
>>>>>>>
>>>>>>>>On April 30, 2000 at 22:34:17, Christophe Theron wrote:
>>>>>>>>
>>>>>>>>>On April 30, 2000 at 18:42:57, Amir Ban wrote:
>>>>>>>>>
>>>>>>>>>>On April 30, 2000 at 16:39:04, Christophe Theron wrote:
>>>>>>>>>>
>>>>>>>>>>>On April 30, 2000 at 06:47:29, Amir Ban wrote:
>>>>>>>>>>>
>>>>>>>>>>>>On April 29, 2000 at 11:31:09, Eran wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>I am sorry if I said it. Okay I believe you that Junior6 has underpromotion code
>>>>>>>>>>>>>and that's wonderful. Maybe I will consider buying it. Does Junior6 consume
>>>>>>>>>>>>>hashtable memory as large as fritz does? Is having large hashtable memory
>>>>>>>>>>>>>important for Junior6? Is 40 MB hashtable enough for 40/120 games?
>>>>>>>>>>>>>
>>>>>>>>>>>>>Eran
>>>>>>>>>>>>
>>>>>>>>>>>>More memory for hash is good, but Junior is not very sensitive to it and you can
>>>>>>>>>>>>change memory size by order of magnitude without obvious effect on playing
>>>>>>>>>>>>strength.
>>>>>>>>>>>>
>>>>>>>>>>>>The comparison to Fritz is interesting and backward: I believe that Fritz 6
>>>>>>>>>>>>(new) consumes less memory than previous versions and the reason may be a
>>>>>>>>>>>>conversation I had with Frans about this in Paderborn, from which he may have
>>>>>>>>>>>>decided that he doesn't need so much memory.
>>>>>>>>>>>>
>>>>>>>>>>>>Amir
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>I must admit I don't understand what you say...
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Christophe
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>Then why don't you ask :)
>>>>>>>>>>
>>>>>>>>>>I understood from Frans that he's hashing quiescence nodes. I told him I don't,
>>>>>>>>>>and that I consider it a waste of time.
>>>>>>>>>>
>>>>>>>>>>Amir
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>I hash quies nodes. I tried both methods (hashing them and not hashing them) and
>>>>>>>>>found that hashing QSearch nodes was definitely better, but not by much. I did
>>>>>>>>>hours of experiments and drew a lot of curves with my spreadsheet in order to
>>>>>>>>>find this.
>>>>>>>>>
>>>>>>>>>It works better even if the hash table is highly saturated.
>>>>>>>>>
>>>>>>>>>That's how it works for me. I don't think that I have a better hashing/replacing
>>>>>>>>>strategy, actually it is rather simplistic. Maybe it's because I do more in
>>>>>>>>>QSearch than both of you do, although I cannot know for sure.
>>>>>>>>>
>>>>>>>>>Maybe I should check again... :)
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> Christophe
>>>>>>>>
>>>>>>>>
>>>>>>>>I used to hash q-search nodes. I found it reduced the size of the tree by about
>>>>>>>>10%.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>Yes, that's approximately what I measured.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>> I also found that by taking it out, I reduced the total search time by
>>>>>>>>15 %. A net gain of 5%.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>That's where I differ. Taking hash probe/updating out of QSearch results in a
>>>>>>>very marginal speed gain (in NPS) for me.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>> More importantly, I don't need nearly the hash memory
>>>>>>>>now since over half of the search is not hashed.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>I think there is no saving in memory. In QSearch, if the hash table slot is
>>>>>>>available, I use it and will maybe gain something, and if it's not available
>>>>>>>(because a more important information is stored) I end up not using the hash
>>>>>>>info in QSearch, as you do.
>>>>>>>
>>>>>>>Not hashing in QSearch means you are not taking advantage of all the memory you
>>>>>>>have to help you to decrease the size of your tree. It does not mean that you
>>>>>>>will need less memory.
>>>>>>>
>>>>>>>You do not take advantage of a resource you have, as your result of a 10%
>>>>>>>smaller tree when using HT in QSearch shows.
>>>>>>>
>>>>>>>Of course, the increased NPS in your case justifies your choice.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>>My next task is to save some time by getting rid of the hashing/unhashing code
>>>>>>>>in the q-search as well, since it isn't used...
>>>>>>>
>>>>>>>
>>>>>>>Yes, I thought of this possible speed gain. But then you have to write a special
>>>>>>>version of make/unmake that you will use exclusively in QSearch, and design
>>>>>>>another system to check for repetitions for example (as I assume that you use
>>>>>>>the hash key to detect repetitions).
>>>>>>>
>>>>>>
>>>>>>
>>>>>>Not possible in my q-search. I don't do checks. Only captures. As a result,
>>>>>>I don't do repetition checks at all since they can't possibly happen.
>>>>>
>>>>>
>>>>>
>>>>>I understand. So obviously you'll earn some extra % of speed by taking out the
>>>>>hashing code.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>>>This is maybe worth the effort for you, because you just generate captures in
>>>>>>>QSearch (that means no repetition can happen in QSearch). But my QSearch does
>>>>>>>more than that, so for me it's a real problem. My QSearch catches a lot of draws
>>>>>>>by repetition.
>>>>>>
>>>>>>I did this is CB. I am not sure it is the right thing to do, as several good
>>>>>>programs are using a restricted (or non-existant) capture search. Ferret is
>>>>>>one example, Junior is another. The benefit right now is that I use all the
>>>>>>extra time to extend in the basic search, where I generally encounter fewer
>>>>>>errors than in the q-search.
>>>>>
>>>>>
>>>>>
>>>>>The benefit of the kind of QSearch I do is not big. I do it mainly because I
>>>>>find it more elegant.
>>>>>
>>>>>If it was worse than doing a simplistic QSearch, I would not do it. But as it is
>>>>>not worse, I tend to use the most "elegant" approach (which is a matter of taste
>>>>>in this case).
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>>>You also need to keep the hashing of pawn structures anyway, so all hashing will
>>>>>>>not be taken out of the QSearch make/unmake.
>>>>>>
>>>>>>
>>>>>>right... although that is (in my code) a 32 bit hash, rather than a 64 bit
>>>>>>one.
>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>But I understand that not hashing in QSearch can be a good decision for some
>>>>>>>programs.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> Christophe
>>>>>>
>>>>>>
>>>>>>Bruce and I flipped and flopped on this one. I started off hashing, while I
>>>>>>don't think he did. Then I took it out but he added it. It is very close
>>>>>>to 'equal' in my code. And if it is equal, I prefer not doing it as it doesn't
>>>>>>stress memory nearly as much, and lets me do long searches without needing huge
>>>>>>hash tables...
>>>>>
>>>>>
>>>>>
>>>>>I understand the "stress memory" point.
>>>>>
>>>>>But I don't buy the "need less hash tables" argument. This is just not true.
>>>>>
>>>>>The hash table slots you fill during QSearch will never compete with the slots
>>>>>you fill during the "normal" search (I do not know how you call it).
>>>>>
>>>>>If you use the standard replacing scheme which uses the depth of computed
>>>>>subtree as the priority factor of a given slot, then it's obvious that a node
>>>>>computed in QSearch will never replace a node computed during the normal search,
>>>>>nor prevent a node computed in the normal search to replace it.
>>>>>
>>>>>By not sending QSearch nodes into the hash table, you are NOT allowing more
>>>>>space for the other nodes. You are just wasting memory space. I understand that
>>>>>the time saved in the process can justify it, but it's wrong to think that you
>>>>>are saving a single byte of memory.
>>>>>
>>>>>
>>>>>
>>>>> Christophe
>>>>
>>>>
>>>>
>>>>This is a well-known bug. If you use totally depth-prefered replacement, you
>>>>run into a big problem, in that the table (in a deep search) gets filled with
>>>>'deep positions' and the positions near the tips don't get stored.
>>>
>>>
>>>
>>>I guess that now you know which replacement strategy I'm using! :)
>>>
>>>
>>>
>>>
>>>> Yet they
>>>>are _critical_. My approach is the one used by Ken Thompson, that of using
>>>>two tables, one depth-prefered, one always-store.
>>>
>>>
>>>
>>>OK, so in this case you are right, storing QSearch nodes does reduce the space
>>>for the other nodes, in the "always replace" table at least.
>>>
>>>
>>>
>>>
>>>>Probably the best way to compare two programs is to do the following: Pick a
>>>>position, and search (using the same hardware) for 300 seconds, while varying
>>>>the hash table for both from something very small, to something very big. For
>>>>each program, you will find a point where the improvement slope drops sharply
>>>>and levels off. We need to test a q-search prober vs a non-q-search prober.
>>>>
>>>>I can run the test for Crafty if you want... and can run from something tiny
>>>>up to 384M max...
>>>
>>>
>>>
>>>I can do the same, but I'll not be able to use more than 16Mb of RAM, as my
>>>computer has only 32Mb.
>>>
>>>I have already done this kind of experiment and plotted the curves with a
>>>spreadsheet. Actually I have done the experiment with 2 versions of my own
>>>program: one using HT during QSearch, the other one not using HT during QSearch.
>>>The programs are otherwise totally identical.
>>>
>>>The experiment was not done on only one position, but on 40 positions. The
>>>positions were taken from 2 actual games (20 positions of the first game, 20
>>>positions of the other game) played by an old version of Chess Tiger against
>>>Rebel Decade, one with white the other one with black. The positions are
>>>consecutive ones, and range from early middlegame to early endgame.
>>>
>>>The positions have all been searched to a fixed depth of 8 plies. The size of
>>>the hash table ranged from 32Kb to 8Mb. I have checked that the point where the
>>>slope of efficiency drops exists in this range of hash table sizes.
>>>
>>>The curves are interesting and show that, for my program, using the HT during
>>>QSearch is always better, and surprisingly is much more interesting when... the
>>>HT begins to be saturated!!
>>
>>
>>
>>Oops... Sorry, I'm tired.
>>
>>The above is complete bullshit. The curve of course shows the opposite: using HT
>>during QSearch is better when the HT is not saturated.
>>
>>Which is not surprising.
>>
>>
>> Christophe
>>
>>
>>
>>
>>>If you are interested, I can send you the small Excel4 file (or export it to
>>>text file).
>>>
>>>I would be interested in the curve that could be drawn from the experiment you
>>>are describing.
>>>
>>>
>>> Christophe
>
>
>
>I will run this test. I did it a couple of years ago and posted in r.g.c.c
>in response to a request by "Komputer Korner".
>
>The thing I worry about is this: for a hash table of size N, there is obviously
>a specific number of nodes that will fit in it at that size. Suppose you fill
>it by depth=12. What happens when you go to depth=20? The last 8 plies can't
>get in, as their depth is too low. And you will see the search die. And die
>badly, performance-wise.
Yes.
> That is the purpose of the 'always-store' part. I
>have 1/3 of my table holding deep search results. And 2/3 of the table is
>always store so it holds the "local search" results.
2/3 sounds big... Why did you chose that amount?
Christophe
>It is those way-deep searches that make this a problem... IE overnight, or
>at todays hardware speeds, even 10 minutes. I can easily hit 1M nps on my
>xeon. Using 384M of hash, I get about 24M hash entries. I can overrun that
>so fast it would be a joke. Even not hashing q-search sees this fill up in
>searches of < 1 minute...
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