I just saw another part of your message, I am wondering also why memory consumption is so high.
El martes, 29 de abril de 2014 11:31:09 UTC+2, Carlos Becker escribió: > > This is likely to be because Julia is creating temporaries. This is > probably why you get increasing memory usage when increasing array size. > > This is a long topic, that will have to be solved (hopefully soon), I had > a previous question related to something similar here: > https://groups.google.com/d/topic/julia-users/Pbrm9Nn9fWc/discussion > > > El martes, 29 de abril de 2014 08:05:17 UTC+2, John Aslanides escribió: >> >> I'm aware that evaluating a vectorized operation (say, an elementwise >> product of two arrays) will result in the allocation of a temporary array. >> I'm surprised, though, at just how much memory this seems to consume in >> practice -- unless there's something I'm not understanding. Here is an >> extreme example: >> >> julia> a = rand(2); b = rand(2); >> >> julia> @time a .*= b; >> elapsed time: 0.505942281 seconds (11612212 bytes allocated) >> >> julia> @time a .*= b; >> elapsed time: 1.4177e-5 seconds (800 bytes allocated) >> >> julia> @time a .*= b; >> elapsed time: 2.5334e-5 seconds (800 bytes allocated) >> >> 800 bytes seems like a lot of overhead given that a and b are both only >> 16 bytes each. Of course, this overhead (whatever it is) becomes >> comparatively less significant as we move to larger arrays, but it's still >> sizeable: >> >> julia> a = rand(20); b = rand(20); >> >> julia> @time a.*= b; >> elapsed time: 1.4162e-5 seconds (944 bytes allocated) >> >> julia> @time a.*= b; >> elapsed time: 2.3754e-5 seconds (944 bytes allocated) >> >> Can someone explain what's going on here? >> >
