Using a single BitArray increases performance by 10x! I've pushed that to github. It also feels a much neater solution.
I still can't work out how to strip out the dictionary in solve.. On Tuesday, 1 July 2014 17:28:06 UTC-7, andy hayden wrote: > > It could be what quinnj's port does > https://github.com/attractivechaos/plb/blob/master/sudoku/sudoku_v1.jl. I > couldn't get this working to compare... > > > > On 1 July 2014 17:13, Iain Dunning <[email protected]> wrote: > >> Stripping out the dictionary stuff in search and doing it in a single >> array pass has knocked me down to >> elapsed time: 1.305257143 seconds (183884144 bytes allocated, 3.85% gc >> time) >> >> Changing to bitarrays would be the real fix, and I got halfway, but >> converting the code was so painful I might just write my own solver based >> on the same bruteforce idea. >> >> On Tuesday, July 1, 2014 7:58:44 PM UTC-4, andy hayden wrote: >>> >>> 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 >>>>>>>>>> >>>>>>>>> >>>>> >
