Steven G. Johnson wrote:
>
>
>
> On Monday, September 12, 2016 at 7:32:48 AM UTC-4, Neal Becker wrote:
>>
>> PnSeq.jl calls rand() to get a Int64, caching the result and then
>> providing
>> N bits at a time to fill an Array. It's supposed to be a fast way to get
>> an
>> Array of small-width random integers.
>>
>
> rand(T, n) already does this for small integer types T. (In fact, it
> generates 128 random bits at a time.) See base/random.jl
>
<https://github.com/JuliaLang/julia/blob/d0e7684dd0ce867e1add2b88bb91f1c4574100e0/base/random.jl#L507-L515>
> for how it does it.
>
> In a quick test, rand(UInt16, 10^6) was more than 6x faster than
> pnseq(16)(10^6, UInt16).
Thanks for the ideas. Here, though, the generated values need to be
Uniform([0...2^N]), where N could be any number. For example [0...2^3].
So the output array itself would be Array{Int64} for example, but the values
in the array are [0 ... 7]. Do you know a better way to do this?
>
> (In a performance-critical situation where you are calling this lots of
> times to generate random arrays, I would pre-allocate the array A and call
> rand!(A) instead to fill it with random numbers in-place.)
