I'm working on a Julia implementation of a Treap, a data structure that maintains a sorted collection of elements and allows insertion, deletion, and random access in O(log n) time (http://en.wikipedia.org/wiki/Treap).
So far I've implemented the basic functions, but performance is far slower than I'd like and I am having trouble understanding why. Here's the gist: https://gist.github.com/yurivish/aff46c190c1ac538c46f I've written a small benchmark script to try and diagnose the problem. It reports lots of memory use for larger collections, even during calls to getindex(). Here's the output for several runs; the function, which is included in the gist, creates and queries a list of Int64s. julia> benchmark(100) Timing 100 insert operations. elapsed time: 0.000188415 seconds (11200 bytes allocated) Timing 100 random access operations. elapsed time: 0.000294615 seconds (0 bytes allocated) Timing 100 remove operations. elapsed time: 6.6692e-5 seconds (0 bytes allocated) julia> benchmark(1000) Timing 1000 insert operations. elapsed time: 0.0024881 seconds (208080 bytes allocated) Timing 1000 random access operations. elapsed time: 0.003553674 seconds (95776 bytes allocated) Timing 1000 remove operations. elapsed time: 0.001143906 seconds (74496 bytes allocated) julia> benchmark(1000000) Timing 1000000 insert operations. elapsed time: 6.920983574 seconds (521837776 bytes allocated) Timing 1000000 random access operations. elapsed time: 16.232631535 seconds (1010908560 bytes allocated) Timing 1000000 remove operations. elapsed time: 5.399104537 seconds (387715296 bytes allocated) Any insight into potential improvements to (or problems with) the code would be appreciated. Cheers, Yuri
