Hi Steven and Daniel, thank you so much for the corrections and suggestions!
> On Sep 2, 2016, at 9:17 AM, Steven G. Johnson wrote:
>
> Try:
>
> function foo_old!(a)
> for i in 1:size(a, 2)
> a[:, i] /= norm(a[:, i])
> end
> return a
> end
>
> function foo_new!(a)
> fo
allocations: 160 bytes)
42
Is @time counting the stack allocations as well? Otherwise I don’t see why any
heap allocation is needed.
> On Sep 2, 2016, at 7:41 AM, Mauro wrote:
>
> On Fri, 2016-09-02 at 13:34, Jong Wook Kim wrote:
>> Hi Yichao, what a nice idea :)
>>
>
AM, Yichao Yu wrote:
>
>
>
> On Fri, Sep 2, 2016 at 7:03 AM, Jong Wook Kim <mailto:ilike...@gmail.com>> wrote:
> Hi,
>
> I'm using Julia 0.4.6 on OSX El Capitan, and was trying to normalize each
> column of matrix, so that the norm of each column becomes
Hi,
I'm using Julia 0.4.6 on OSX El Capitan, and was trying to normalize each
column of matrix, so that the norm of each column becomes 1. Below is a
isolated and simplified version of what I'm doing:
function foo1()
local a = rand(1000, 1)
@time for i in 1:size(a, 2)
a[:, i
I'm wondering if HPTCDL(High Performance Technical Computing in Dynamic
Languages) workshop is being planned this year.
I could only find the proceedings of the first workshop (2014), and only a
call for papers for the 2015 workshop.
Does anyone know the details of the HPTCDL workshop in 2015 a
I can easily type floating point literals of wanted precision:
julia> typeof(3.14f0)
Float32
julia> typeof(3.14)
Float64
julia> typeof(3.14e0)
Float64
But i have to resort to converter method, in order to avoid being
platform-dependent.
julia> typeof(42) # platform-dependent
Int64
julia>