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 memory-efficient 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 bit-wise 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/ _______________________________________________ Judy-devel mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/judy-devel
