yes, but those are scalars not (potentially big) arrays.
Sábado, 12 de Julho de 2014 21:33:17 UTC+1, Stefan Karpinski escreveu: > > On 32-bit systems, Int is Int32. 64-bit systems tend to have enough > memory, not to mention the fact that pointers, indices, etc. are natively > 64-bit on those systems. > > > On Sat, Jul 12, 2014 at 1:21 PM, J Luis <[email protected] <javascript:>> > wrote: > >> >> >> Sábado, 12 de Julho de 2014 21:16:04 UTC+1, John Myles White escreveu: >> >>> On Jul 12, 2014, at 1:04 PM, J Luis <[email protected]> wrote: >>> >>> > That is also true but a much more rare case, typemax(Int32) is still a >>> quite high number for an array size and before an Int64 is needed changes >>> are non negligible that a memory requested failed because a big contigous >>> chunk of memory was not available. Well, this is my Matlab experience, >>> which I would like not have repeated in Julia. >>> >>> Have you hit a problem with this in Julia in practice or is it a mostly >>> hypothetical concern? I’ve worked with arrays that contain billions of >>> entries a bunch of times and haven’t had any problems on a machine with >>> sufficient RAM to cope with that kind of workload. >>> >> >> Regarding the Julia world is only, as you say, an hypothetical concern >> ... but based on previous experience. The "sufficient RAM" is the keyword. >> With 32 bits less RAM (e.g. as in laptops) may have been the "sufficient". >> >> Joaquim >> > >
