[Computer-go] pachi2

[Aja]

Hi Petr and Jean-loup,

I think Erica might drop to 2d if using the same time setting of Pachi2 (over 20mins SD).
The semeai in the bottom-left of this game is very interesting: 
http://files.gokgs.com/games/2011/1/13/pachi2-BOThater36.sgf

I believe, we must solve this kind of long-semeai to make our programs reach high dan.

Aja
  ----- Original Message ----- 
  From: Jean-loup Gailly 
  To: computer-go at dvandva.org 
  Sent: Thursday, January 13, 2011 7:20 PM
  Subject: Re: [Computer-go] pachi2


  Here is some preliminary information on the distributed version of pachi.
  Petr (pasky) and I will publish all the details later, this is just to give
  you an idea of what we are doing. Pasky is the main author of pachi and
  wrote most of the single machine code. I wrote the distributed code and
  some other improvements.


  All the code, including the distributed code, is GPL and available at
  http://repo.or.cz/w/pachi.git/


  The distributed pachi uses simple tcp/ip sockets, not MPI. This makes it
  portable to many environments. A master process receives stats updates
  regularly from all the slaves and distributes the aggregated updates back
  to all slaves. The master-slave protocol is specific to pachi but it is
  rather simple. It is fault tolerant: if a slave dies, the master will send
  again the whole game to the new slave that will replace it. If the master
  dies, I ignore the current game and restart a new one when doing test
  runs. If the master dies when running for KGS, I kill the kgsGtp program
  and start a new one; KGS then sends again the partial game and we continue
  from there.


  I measured scalability both on a single machine and in distributed
  mode. All the details will be published, but here is a summary.  In single
  machine mode, doubling the number of cores gains roughly 100 elo or one
  stone. (I measured one stone to be approximately 100 elo).  This is true up
  to the number of cores I can test (20 per machine, other cores are reserved
  for the OS and other apps).


  In distributed mode doubling the number of machines initially gains
  approximately 50 elo (half a stone) up to 8 machines.  Above this we
  quickly hit a scalability limit and the best result so far is with 64
  machines; this is the configuration used for the KGS tournament (starting
  at round 4) and on KGS right now. 128 machines are currently much worse
  than 64.


  Preliminary analysis of the lost games shows that the current code
  has inherent scalability limits because the playouts are biased.
  When the playouts incorrectly judge the life status of a group,
  the results will be bad no matter how many cores and machines
  work on it. We are of course working on this to eliminate these
  scalability limits.


  Pachi has benefited enormously from ideas published on the computer-go
  mailing list and in many papers.  By making its source completely open we
  hope to encourage further progress in this area.


  Petr and Jean-loup




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