http://compsoc.dur.ac.uk/whitespace/index.php

If you have p bits of hash function available to you, and the top tier consumes q of them, then at one extreme q = 0, and you have all p bits available for use within the one bucket, cutting p up into k different hash functions yields the traditional Bloom filter.

In the other extreme you have q = p, and you have the efficacy of a bloom table/bit-hash with one hash function.

In the middle the false positive rate lies somewhere in between, but you only have to deal with data points within a single bucket to answer the query, so you can typically save a factor of k in paging or cache-thrashing costs.

http://algo2.iti.uni-karlsruhe.de/singler/publications/cacheefficientbloomfilters-wea2007.pdf

Although they concern themselves with clustering within a single cache line, the idea of clustering within a page follows similarly.

IIRC they take up like ~32% extra space to get the same precision, but they use VERY small buckets of the same size as a cache line. So that should give you an upper bound for space comparison that you can back into a false positive rate comparison.

Anyway, all jokes aside, I am surprised to find Bloom Filter usage very sparse within the general software industry (I am a consultant-of-one running my own company but have large clients in the Fortune 100, start-ups, etc).

The case you presented here for being able to efficiently serialize the filter has notable use in web-application farm environments where sessions and other state table information must be migrated between servers (depending on session management strategy employed). Indeed one challenge I am considering is somehow managing some Bloom Filter construct across a RAIN architecture without sacrificing the small memory footprint and performance advantages that Blooms provide.

Thanks again.

Unfortunately nothing I do these days makes for great screenshots. Maybe I should go back to voxels and stabbing line problems. ;)

I suppose you could Bloom a scene’s PVS or something, but its not all that useful for its primary purpose because then you wouldn’t be able to extract the member cells. Hrmm. That said, I guess it could be used for a quick, “is this model that overlaps these cells probably visible?” tester.

I almost referred to the hierarchical representation as a kind of Haar wavelet encoding, but I figured that would cause the last person in the audience to tune me out.

P.S. The alpaca on your page still refers to blabberize as ‘the technology of 2007′ ;)