Computer Chess Club Archives


Search

Terms

Messages

Subject: random access latency opteron versus k7

Author: Vincent Diepeveen

Date: 12:41:30 05/30/04

Go up one level in this thread


On May 29, 2004 at 11:30:27, Robert Hyatt wrote:

[snip]
>See above.  _no_ improvement.  Raw latency on opteron is 1/2 the raw latency on
>the K7 and Intel boxes.  But mapping adds 2 extra memory accesses on the opteron
>which does away with any actual advantage...
>
>
>
>>
>>Softwarebenches like linbench and such pumping sequential a few gigabytes
>>through the machine and then divide that by the search time. Then you have
>>bandwidth. 1/bandwidth = latency they claim.
>
>
>But that is the latency _you_ are quoting when you say opteron is 1/2 the
>latency of the K7.  In your worst-case it is _not 1/2.  It is the same.

Let's show you the tested facts K7 versus A64:
Opteron single cpu 2.5 cas versus k7 cas 2.5. Note the k7 has all memory banks
filled the opteron does *not* it just has a single dimm and is single channel
and not even dual channel. So actually the latency is better than shown here.
Quad opteron tested at 120 ns latency for a single cpu in fact when i tried a
while ago.

E:\dblat>dblat 300000000
Setting up a random access pattern, may take a while
Finished
Random access:  13.156 s, 131.560 ns/access
Testing same pattern again
Random access:  13.374 s, 133.740 ns/access
Setting up a different random access pattern, may take a while
Finished
Random access:  13.343 s, 133.430 ns/access
Testing same pattern again
Random access:  13.265 s, 132.650 ns/access
Sequential access offset     1:   0.250 s,   2.500 ns/access
Sequential access offset     2:   0.484 s,   4.840 ns/access
Sequential access offset     4:   0.875 s,   8.750 ns/access
Sequential access offset     8:   1.781 s,  17.810 ns/access
Sequential access offset    16:   3.375 s,  33.750 ns/access
Sequential access offset    32:   6.265 s,  62.650 ns/access
Sequential access offset    64:   6.516 s,  65.160 ns/access
Sequential access offset   128:   7.000 s,  70.000 ns/access
Sequential access offset   256:   7.938 s,  79.380 ns/access
Sequential access offset   512:   9.188 s,  91.880 ns/access
Sequential access offset  1024:   9.875 s,  98.750 ns/access

Now the dual k7. all banks filled. a-brand memory.
C:\tries>dblat 300000000
Setting up a random access pattern, may take a while
Finished
Random access:  36.266 s, 362.660 ns/access
Testing same pattern again
Random access:  36.406 s, 364.060 ns/access
Setting up a different random access pattern, may take a while
Finished
Random access:  36.250 s, 362.500 ns/access
Testing same pattern again
Random access:  36.484 s, 364.840 ns/access
Sequential access offset     1:   0.906 s,   9.060 ns/access
Sequential access offset     2:   1.766 s,  17.660 ns/access
Sequential access offset     4:   3.437 s,  34.370 ns/access
Sequential access offset     8:   6.891 s,  68.910 ns/access
Sequential access offset    16:  13.875 s, 138.750 ns/access
Sequential access offset    32:  19.093 s, 190.930 ns/access
Sequential access offset    64:  19.156 s, 191.560 ns/access
Sequential access offset   128:  19.328 s, 193.280 ns/access
Sequential access offset   256:  19.719 s, 197.190 ns/access
Sequential access offset   512:  20.437 s, 204.370 ns/access
Sequential access offset  1024:  21.860 s, 218.600 ns/access

So practical difference for computerchess :

363 / 132 = 2.75 times faster latency for the opteron

On die memory controller isn't that stupid nah?

>>I would prefer calling that 'streaming latency'. It's full name officially is
>>though 'cross bandwidth latency'.
>>
>>For chesssoftware that cross bandwidth latency is completely irrelevant.
>Not if you need to move blocks of data...

That would make a funny chessprogram moving blocks of a few megabyte memory for
each node :)

>
>
>
>
>>
>>>>>>
>>>>>>>The IID principle can also apply to some additional situations:
>>>>>>
>>>>>>>1) You have a hash move, but it's at depth-2 rather than depth-1. You can do
>>>>>>>another IID layer in this case.
>>>>>>
>>>>>>In that case hashmoves works better of course.
>>>>>>
>>>>>>>2) Your fail-high hash move (for some engines the only possible kind of hash
>>>>>>>move) fails low. Here you can do IID to get an alternative move.
>>>>>>
>>>>>>This is highly unlikely as your IID is at depth-i where i > 0.
>>>>>>
>>>>>>So most likely that hashmove is already from a position j >= depth - i, which
>>>>>>makes IID a complete waste of your time.
>>>>>
>>>>>I meant an IID where the move that already failed low is thrown out. You want
>>>>>the second-best move at the reduced depth.
>>>>
>>>>Use double nullmove. works better than IID and the first move you already get
>>>>the best move :)
>>>
>>>The depth reduction is too high. More experiments are needed - but it would be
>>>quite a coincidence if the best IID depth reduction just happened to be exactly
>>>twice the best null move depth reduction.
>>>>
>>>>>Usually, you will waste a few nodes this way of course. The idea is to avoid-the
>>>>>worst case scenario - of doing a full search through a bunch of other moves,
>>>>>before finding the fail-high move.
>>>>
>>>>You can add 1000 conditions, but if something doesn't work in general, it won't
>>>>work with 1000 conditions either. It just is harder to test in a way that
>>>>objective and statistical significant conclusions are possible to statistical
>>>>significant conclude whether it works or doesn't.
>>>>
>>>
>>>In Rybka, IID works. Further, I haven't found any conditions which make it work
>>>better, although I didn't try anything really fancy - just some comparisons
>>>between current eval and the bound. Anyway, I read your reply to Tord, and will
>>>keep retesting as the engine evolves.
>>
>>I didn't find a single condition under which it works for DIEP. It's just a
>>waste of system time IMHO.
>
>Too bad.  It works for me too.  Used very selectively.
>
>
>
>>
>>>>>>
>>>>>>>And - as Tord mentioned - an IID search can be turned into the final
>>>>>>>reduced-depth search, based on its result.
>>>>>>>Vas
>>>>>>
>>>>>>Depth reducing the current search?
>>>>>>
>>>>>>Sounds like a rather bad idea to me.
>>>>>
>>>>>Well that's the million dollar question, isn't it?
>>>>
>>>>Seems there is 2 camps.
>>>>
>>>>I'm currently in the camp that i tried both worlds and concluded that depth
>>>>reducing with nullmove is already enough.
>>>>
>>>>I can imagine last few plies some types of forward pruning somehow work. So far
>>>>i could not prove that last though.
>>>>
>>>>I have a hard time believing that forward pruning in the entire tree is going to
>>>>beat the nullmove pruning.
>>>>
>>>>We both are titled chessplayers, and i see simply that the few mistakes todays
>>>>engines make, usually it is a dubious move caused by bugs in the forward
>>>>pruning.
>>>>
>>>>Shredder is clearest example.
>>>
>>>Yes Shredder has some blind spots, but it can also search really deep,
>>>especially when it's attacking. It's always nice to search deeper in the
>>>critical lines. Anyway - I'm still checking out both camps.
>>
>>Well it's not so hard to add 7 plies to your search depth because your
>>'selective search' might see 7 more (which in fact it does in diep).
>>
>>I prefer a 14 ply search depth with just nullmove above 18 with the chance that
>>all your search lines are depth reduced and last few plies you supernullmove and
>>in qsearch you lazy evaluate :)
>>
>>With forward pruning at every ply like shredder seems to do you only see faster
>>what it sees anyway. What your eval doesn't see, search won't find either
>>because you nonstop shorten such lines more than my '14 ply search depth' is
>>doing.
>>
>>>The key is to think of the future - because it will soon be here. I really don't
>>>care which search misses more tactics on some 32 bit 1 GHz machine ...
>>>Vas
>>
>>Last time Shredder ran on a 1 Ghz machine at a world champs was in world champs
>>London 2000, so those days are long gone.
>>
>>>>
>>>>>Vas



This page took 0 seconds to execute

Last modified: Thu, 15 Apr 21 08:11:13 -0700

Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.