On Sat, Oct 1, 2016 at 8:51 PM, David Gleich wrote:
> Thanks for that pointer. I'll take a look!
I have a collection of really simple ones here[1]. It's not systematic
or comprehensive in any sense but does check a few operations that I
care about (simd and math functions)
Thanks for that pointer. I'll take a look!
On Saturday, October 1, 2016 at 3:59:18 PM UTC-4, cormu...@mac.com wrote:
>
> I asked a similar question last week. The standard recommendation is
> https://github.com/JuliaCI/BaseBenchmarks.jl. It didn't really meet what
> I was looking for -- a
When you want to use the fields of a type as arguments to a function or
where you want to apply a type-wrapped version an imported operator,
TypedDelegation is available.
Eight macros are exported. Four are for use where one field within a type
is needed, and four where two fields within a
Thanks a lot, Steve.
> On Oct 1, 2016, at 17:13, Steven G. Johnson wrote:
>
> https://github.com/JuliaLang/julia/blob/c4ebf7c8bbdfaba034a08fa795b93a5732514c64/src/jltypes.c#L3724
https://github.com/JuliaIO/NRRD.jl
thats pure Julia
Am Samstag, 1. Oktober 2016 20:48:37 UTC+2 schrieb Steven G. Johnson:
>
>
>
> On Monday, September 26, 2016 at 9:59:15 AM UTC-4, David Smith wrote:
>>
>> I also don't need it to read image formats. Part of the reason behind
>> RawArray is to
https://github.com/JuliaLang/julia/blob/c4ebf7c8bbdfaba034a08fa795b93a5732514c64/src/jltypes.c#L3724
I asked a similar question last week. The standard recommendation is
https://github.com/JuliaCI/BaseBenchmarks.jl. It didn't really meet what I was
looking for -- a quick, easy to run benchmark to compare machines -- but you
may find it useful for your purposes.
There's `Gather` (low-level, adapted straight from the MPI standard) and
`gather` (high-level, convenient for Julia, but apparently not yet
implemented).
-erik
On Sat, Oct 1, 2016 at 3:50 PM, Joaquim Dias Garcia <
joaquimdgar...@gmail.com> wrote:
> Thanks! Thats nice, I was misled by the gather
Thanks! Thats nice, I was misled by the gather function, i think I was looking
too low level.
Joaquim
> On 1 Oct 2016, at 16:37, Erik Schnetter wrote:
>
> In Julia, `MPI` can send objects of any type. These objects will
> automatically be serialized and deserialized. The
In Julia, `MPI` can send objects of any type. These objects will
automatically be serialized and deserialized. The respective functions are
```Julia
function send(obj, dest::Integer, tag::Integer, comm::Comm)
function recv(src::Integer, tag::Integer, comm::Comm)
```
Note the lower-case function
Hi all,
I have the following type:
type bar
a::Int
b::Vector{Matrix{Float64}}
c::Vector{Float64}
end
I would like to send instances of that type via MPI.
Can I do it?
Is there any serialization/deserialization procedure i could use for that?
thanks!
* Would anyone know in which file of https://github.com/JuliaLang/julia is
the definition of {true} defined? Thanks
On Saturday, October 1, 2016 at 3:35:10 PM UTC-3, Kevin Liu wrote:
>
> Hello. Would anyone know in which file of
> https://github.com/JuliaLang/julia would the definition of
On Monday, September 26, 2016 at 9:59:15 AM UTC-4, David Smith wrote:
>
> I also don't need it to read image formats. Part of the reason behind
> RawArray is to avoid standard image formats because they are not optimized
> for large complex-float arrays. I just want to save multi-GB data
Hello. Would anyone know in which file
of https://github.com/JuliaLang/julia would the definition of {true} be
defined? Thanks
We just got a few new large memory machines with Haswell and Broadwell
architectures.
I'm wondering what is the current recommendation for getting Julia to run
as fast as possible on these machines.
We have a license for the Intel Compilers and MKL.
So the question is: What's the best way to
I am trying to find a way to check the membership of a user defined type
object in a heap. This is the code I have written:
type HeapEntry
k::Int
dist::Float64
end
isless(e1::HeapEntry, e2::HeapEntry) = e1.dist < e2.dist
heap1 = []
Collection.heappush!(heap1, HeapEntry(1, 10.0))
But
We can add a note to the downloads page saying that past versions are still
available by just modifying the version number in the url, if that would
help.
On Saturday, October 1, 2016 at 2:17:09 AM UTC-7, Mauro wrote:
>
> On Sat, 2016-10-01 at 10:38, ami...@gmail.com wrote:
> > Great, a bit
In your two examples, note the difference *when* the macro argument is
multiplied by 2.
@ex_timestwo happens at runtime
@n_timestwo happens at macro expansion time
a = 6
@ex_timestwo(a)
will return 12 as expected,
whereas:
a = 6
@n_timestwo(a)
will still result in error because at macro
On Sat, Oct 1, 2016 at 5:26 AM, Lyndon White wrote:
> I was generally under the impression that a macro always had the return a
> `Expr`
> and that doing otherwise would make the compiler yell at me.
>
> Apparently I was wrong, at least about the second part:
>
I was generally under the impression that a macro always had the return a
`Expr`
and that doing otherwise would make the compiler yell at me.
Apparently I was wrong, at least about the second part:
https://github.com/ChrisRackauckas/ParallelDataTransfer.jl/issues/3
macro ex_timestwo(x)
On Sat, 2016-10-01 at 10:38, amik...@gmail.com wrote:
> Great, a bit ashamed I didn't even try that... Thank you Mauro.
No worries, if I recall correctly, I know because I had asked too...
Great, a bit ashamed I didn't even try that... Thank you Mauro.
For simple cases there's also the IndirectArrays package:
https://github.com/JuliaArrays/IndirectArrays.jl
Best,
--Tim
On Fri, Sep 30, 2016 at 10:51 PM, wrote:
> OK! many thanks for your fast reply
> --a
>
>
> On Friday, September 30, 2016 at 3:53:43 PM UTC+2,
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