[Computer-go] Has Anyone Heard of Multi-Hashing?

steve uurtamo uurtamo at gmail.com
Wed Jul 17 09:08:51 PDT 2013

You can likely think about this in the context of bloom filters.


On Wed, Jul 17, 2013 at 8:54 AM, Brandon Cieslak <bcieslak at lclark.edu>wrote:

> *
> Hello Computer Go mailing list,
> We were wondering if anyone has ever seen or heard of a method of storing
> patterns similar to the one we are currently trying to implement and test.
> Here is our method:
> We are using multiple hash tables to store win rates for large patterns.
> Each table uses a different Zobrist hash function. The tables are “sloppy”
> in that, when two patterns inevitably hash to the same location, we simply
> combine the information.
> When we store a win or a loss for a pattern (encountered in a recorded
> game or a playout), we store it in each table. When looking for the win
> rate of a pattern, we look in each of the tables and get the average of
> those results.
> The advantage of this approach (over one big table) is that, if there are
> n tables, each lookup averages n copies of the “signal” but only 1 copy of
> each collision. Preliminary experiments suggest that this is a better use
> of memory than one large table.
> (We also plan to store patterns at several different scales this way, but
> that’s another story.)
> The only reference we found to this approach has been a single section of
> Narayanasamy et al., “Catching Accurate Profiles in Hardware” (
> http://cseweb.ucsd.edu/~calder/papers/HPCA-03-Multihash.pdf, Section 6 is
> most relevant). They call this approach Multi-Hashing.
> Thank you in advance,
> The Orego Team*
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