Ha, I had exactly the same issue (I pushed a perf update with a commented out impl), I assumed it was something (very) wrong in my understanding of control flow!
I don't think see how it would rely on anything, ordering (?)... perplexing. On Tuesday, 1 July 2014 16:45:04 UTC-7, Iain Dunning wrote: > > Yeah we changed the example, so best to take it from the one in the > release version... > > I removed the dictionary from search() but its now no longer solving all > the problems(!) - does the algorithm rely somehow on the way the dictionary > is constructed? > > > On Tuesday, July 1, 2014 6:59:02 PM UTC-4, andy hayden wrote: >> >> I was using Cbc. >> >> SolveModel is a copy and paste job from JuMP (from the last release >> rather than master) so may not work with JuMP from master - I couldn't get >> the version from master working since it was incompatible with the JuMP >> release I had! It'd be great to just be able to just include the file, but >> I couldn't get that working so I just pasted it in (I should probably clean >> Bench as I made quite a mess, apologies about that.)... so it may be you >> need to update SolveModel from JuMP master/your version of JuMP to get >> Bench working. >> >> It's amazing how some small tweaks like this go so far, there's a few >> other bits that are obvious even to me (but I just couldn't get working). >> >> >> On 1 July 2014 15:47, Iain Dunning <[email protected]> wrote: >> >>> JuMP won't be getting any faster, its entirely limited by the speed of >>> the MIP solver. Which one did you use? >>> >>> >>> On Tuesday, July 1, 2014 6:47:04 PM UTC-4, Iain Dunning wrote: >>>> >>>> I was unable to run Bench.jl (ERROR: varzm! not defined), but, on my >>>> computer just using runtests.jl, a fixed seed, and total time for 100 >>>> random >>>> >>>> *Initial >>>> elapsed time: 1.641434988 seconds (282491732 bytes allocated, 5.99% gc >>>> time) >>>> >>>> *Change globals to const >>>> elapsed time: 1.563094028 seconds (261818132 bytes allocated, 6.61% gc >>>> time) >>>> >>>> * Changing from using a Dict{Int64, *} for the Grid types to just a >>>> Vector{*}, as well as those other globals >>>> elapsed time: 1.373703078 seconds (191864592 bytes allocated, 4.91% gc >>>> time) >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> On Tuesday, July 1, 2014 6:27:15 PM UTC-4, andy hayden wrote: >>>>> >>>>> Bench.jl has a bench_compare method which returns a DataFrame of times >>>>> (I then divide the median of Python vs Julia columns), I'll add this >>>>> output >>>>> to the Bench script as it's useful to see (would be nice to add more >>>>> stats, >>>>> as it's just a DataFrame of all the solved puzzles in seconds). By >>>>> default >>>>> it runs a hundred random sudoku's on Julia, Python, and JuMP (the same on >>>>> each)... >>>>> >>>>> Thanks Steven: Making those const makes a huge difference, Julia wins >>>>> (from 20% slower to 10% faster for me with just that change). >>>>> I will have a play and see how your other suggestions play out. >>>>> >>>>> I was also very impressed with JuMP here... and it may be the latest >>>>> is even faster (I'm using the version from the last release rather than >>>>> master, and it has changed since then). >>>>> >>>>> >>>>> On Tuesday, 1 July 2014 15:11:27 UTC-7, Iain Dunning wrote: >>>>>> >>>>>> I'm working on improving this, but I'm not sure how you are measuring >>>>>> that 20% slower - can you be more specific? >>>>>> >>>>>> On Tuesday, July 1, 2014 1:37:00 PM UTC-4, andy hayden wrote: >>>>>>> >>>>>>> I recently ported Norvig's Solve Every Sudoku Puzzle >>>>>>> <http://norvig.com/sudoku.html> to Julia: https://github.com/ >>>>>>> hayd/Sudoku.jl >>>>>>> >>>>>>> Some simple benchmarks suggest my Julia implementation solves around >>>>>>> 20% slower* than the Python version, and 3 times faster than the >>>>>>> implementation on JuMP (vendorized from the latest release), against >>>>>>> the >>>>>>> random puzzles. I tried to include the solver from >>>>>>> attractivechaos/plb >>>>>>> <https://github.com/attractivechaos/plb/tree/master/sudoku> but >>>>>>> couldn't get it working for comparison... >>>>>>> >>>>>>> I'm new to Julia so would love to hear people's thoughts / any >>>>>>> performance tips! >>>>>>> I've not delved too deeply into the Profile, but @time suggests 10% >>>>>>> of time is GC. >>>>>>> >>>>>>> **I'm sure I've lost some performance in translation which could be >>>>>>> easily sped up...* >>>>>>> >>>>>>> Best, >>>>>>> Andy >>>>>>> >>>>>> >>
