From: Doug Baskins <dougbaskins@ya...>  20080517 15:21:24

Hi Simen: First, if I understand your email, I think you could solve the problem a little differently. Do J1N() on both arrays at the same time and advance the one that returns the lessor Index. All the data you need can be extracted when the J1N's return different Indexes. This will only require only one access on each data element in both arrays. For arrays of very large populations, J1N's are very fast because typically most of the data is in the cache from the last access (J1N). Second, I do not understand your statement: > However, it seems to scale not so well when the largest indicex present grows. If in your example that the number "20" were changed to 1234567890, I think the performance would be about the same because Judy1 does not store 0's (missing Indexes) in the array. I can answer more of your questions if you like. I am surprised that Judy1 is used for this "small" of problem. I am use to thinking in 100's of million of Indexes. Judy1 will store any combination of Indexes, in any order up to the 4 billion max while using less than 1GB of RAM. Doug Doug Baskins <dougbaskins@...>  Original Message  From: Simen Kvaal <simen.kvaal@...> To: judydevel@... Sent: Friday, May 16, 2008 9:59:17 PM Subject: Judy1 Hi! I came across Judy1 yesterday and have incorporated it into my code, and it works wonderfully. My code heavily relies on a fast and memoryefficient way to represent a sparse pattern of bits  hence, Judy1! To be more specific, my code repeatedly compares two variable patterns (Judy1 arrays) A and B, both containing a constant number of set bits, to find differing bit positions. For example, if A = (1, 4, 5, 10, 15) B = (1, 5, 6, 10, 20) Then i need the output d(A,B) = (4, 15), d(B,A) = (6, 20) and also j(A,B) = (2, 5) and j(B,A) = (3,5), where j(A,B) are the number in the sequence of the differing bits in A compared to B. What would be the most efficient way to do this? Would it depend on the density of the array? Typically, I have ~1000 indices and ~5 bits set. My present code traverses first A (using J1F and J1N on A) and using J1T on B for each result. The result is then stored. Then, it repeats the process on B. This is fast; about as fast as using bitwise manipulations on unsigned integers, which was my old representation of the patterns. However, it seems to scale not so well when the largest indicex present grows. Thanks in advance for any advice! Regards, Simen Kvaal.   Simen Kvaal  Ph.D student in Physics/Applied Maths  Centre of Mathematics for Applications, University of Oslo web: http://folk.uio.no/simenkva/ office: +47 22857708  This SF.net email is sponsored by: Microsoft Defy all challenges. Microsoft(R) Visual Studio 2008. http://clk.atdmt.com/MRT/go/vse0120000070mrt/direct/01/ _______________________________________________ Judydevel mailing list Judydevel@... https://lists.sourceforge.net/lists/listinfo/judydevel 