When I put that code inside a function, I got the same behavior.
For single process, K = Float64[dot(X[:,i], X[:,j]) for i=1:5, j=1:5] does
the job.
But for parallel I got error: "ERROR: malformed @parallel loop"
Rizal
On Mon, Nov 9, 2015 at 10:48 AM, Kristoffer Carlsson <kcarlsso...@gmail.com>
wrote:
> Don't run the code in global scope or alternatively be explicit about the
> type you want, for example Float64[....]
>
> On Monday, November 9, 2015 at 5:42:15 PM UTC+1, rizal zaini wrote:
>>
>> My concern is also on parallel code:
>>
>> julia> K = @parallel [dot(X[:,i], X[:,j]) for i=1:5, j=1:5] 5x5
>> DArray{Any,2,Array{Any,2}}: 1.35134 1.36439 1.28474 1.13181 1.07863 1.36439
>> 1.40077 1.25708 1.22365 1.08332 1.28474 1.25708 1.54494 0.95311 1.15779
>> 1.13181 1.22365 0.95311 1.70348 1.30076 1.07863 1.08332 1.15779 1.30076
>> 1.34577
>>
>> I expect to get a DArray{Float64,2,Array{Float64,2}} rather than
>> DArray{Any,2,Array{Any,2}}
>>
>> Please help.
>>
>> Rizal
>>
>> On Mon, Nov 9, 2015 at 9:11 AM, rizal zaini <riza...@gmail.com> wrote:
>>
>>> Hi all
>>>
>>> I want to create matrix containing dot products
>>>
>>> julia> X = rand(5,5)
>>> 5x5 Array{Float64,2}:
>>> 0.274799 0.564619 0.915595 0.341059 0.57361
>>> 0.0806822 0.293939 0.379279 0.608582 0.652441
>>> 0.264678 0.532751 0.289088 0.457759 0.492777
>>> 0.33856 0.495587 0.499099 0.548237 0.402534
>>> 0.686305 0.168385 0.8322 0.605532 0.518693
>>>
>>> julia> K = [dot(X[:,i], X[:,j]) for i=1:5, j=1:5]
>>> 5x5 Array{Any,2}:
>>> 0.737716 0.603229 1.09884 0.865174 0.832958
>>> 0.603229 0.962978 1.16994 0.988988 1.06501
>>> 1.09884 1.16994 2.00739 1.45298 1.54767
>>> 0.865174 0.988988 1.45298 1.36347 1.35304
>>> 0.832958 1.06501 1.54767 1.35304 1.42861
>>>
>>> I expect to get an Array{Float64,2}, but what I got is Array{Any,2}.
>>> How to get Array{Float64,2} using Array comprehension?
>>>
>>> Thanks before
>>> Rizal
>>>
>>
>>
