That's exactly how I understand, and I'm using 0.4, so Tim's suggestion above won't work...I presume this is not related to the implementation of svds, since other built-in functions also takes much more time and memory on the first running:
julia> @time sprand(5,5,0.1) elapsed time: 0.314905039 seconds (11 MB allocated) julia> @time sprand(5,5,0.1) elapsed time: 3.0776e-5 seconds (976 bytes allocated) Cheers, Todd Leo On Wed, Feb 25, 2015 at 5:00 PM Viral Shah <[email protected]> wrote: > No need to precompile. svds was recently added to base - but it won't > exist in 0.3. > > -viral > > > On Wednesday, February 25, 2015 at 12:32:09 PM UTC+5:30, Todd Leo wrote: >> >> Isn't svd/svds already included in base? Do I need to precompile them? >> >> On Saturday, February 7, 2015 at 3:48:50 AM UTC+8, Tim Holy wrote: >>> >>> Since it allocates 120MB on the first call and only 9kB on the second, >>> all that >>> memory is just due to compilation. >>> >>> The only way I know to fix that is to precompile some of the functions >>> when you >>> build julia. If this is a big deal to you, consider adding your own >>> custom >>> userimg.jl (and see base/precompile.jl for a model). >>> >>> http://docs.julialang.org/en/latest/manual/modules/?highligh >>> t=userimg#module-initialization-and-precompilation >>> >>> --Tim >>> >>> On Friday, February 06, 2015 11:23:52 AM Viral Shah wrote: >>> > This is because the internal operations with svds are allocating new >>> > vectors every iteration. This PR should address it, but needs to be >>> > completed, >>> > >>> > https://github.com/JuliaLang/julia/pull/7907 >>> > >>> > Also, array indexing giving views by default will also help here. >>> > >>> > -viral >>> > >>> > On Friday, February 6, 2015 at 7:50:24 PM UTC+5:30, Todd Leo wrote: >>> > > Hi Julians, >>> > > >>> > > I am trying to apply svd on a very large sparse matrix using svds. >>> When >>> > > warming up svds function, I used a very small random vector, and the >>> > > number >>> > > of singular values (nsv) is set to one. However, this simple set up >>> > > results >>> > > in a considerable high cost of time, and as much as 120MB memory is >>> > > occupied. To me, it doesn't make sense, and one can reproduce it by: >>> > > >>> > > julia> @time svds(sprand(3,3,0.1), nsv = 1) >>> > > >>> > >> elapsed time: 2.640233094 seconds (117 MB allocated, 1.06% gc time >>> in 5 >>> > >> >>> > >>> pauses with 0 full sweep) >>> > > >>> > > Regards, >>> > > Todd >>> >>>
