Hi,

 > After poking around with different headers it appears I need one of the
> object type files such as "viennacl/matrix.hpp" in order to declare
> viennacl::context objects.  Shouldn't this be possible from just
> "viennacl/ocl/backend.hpp"?  Just curious on the design at this point.

have you tried to include viennacl/context.hpp directly?

Best regards,
Karli



> On Tue, May 10, 2016 at 8:40 AM, Charles Determan <cdeterma...@gmail.com
> <mailto:cdeterma...@gmail.com>> wrote:
>
>     Excellent, thank you for explaining that.  One followup thing, I am
>     trying a trivial function to test this:
>
>     int findContext(int x){
>          viennacl::context
>     ctx(viennacl::ocl::get_context(static_cast<long>(x)))
>          return x
>     }
>
>     but I keep getting a compiler error:
>
>      >error: variable ‘viennacl::context ctx’ has initializer but
>     incomplete type
>
>     Did I miss something?
>
>     Thanks,
>     Charles
>
>
>     On Mon, May 9, 2016 at 4:09 PM, Karl Rupp <r...@iue.tuwien.ac.at
>     <mailto:r...@iue.tuwien.ac.at>> wrote:
>
>         Hi Charles,
>
>         setContext() is not thread-safe, so if mclapply() is executing
>         in parallel, there will be a race. MPI works across processes,
>         so globals are not shared (and hence setContext() has no problems).
>
>         If you want to run multithreaded, you should manage the contexts
>         explicitly. That is, pass a viennacl::context object to the
>         respective constructors of viennacl::vector, viennacl::matrix,
>         etc. You can find examples here:
>         
> https://github.com/viennacl/viennacl-dev/blob/master/examples/tutorial/multithreaded.cpp
>         
> https://github.com/viennacl/viennacl-dev/blob/master/examples/tutorial/multithreaded_cg.cpp
>
>         Best regards,
>         Karli
>
>
>
>
>         On 05/09/2016 10:32 PM, Charles Determan wrote:
>
>             I am trying to use multiple GPU's in parallel using ViennaCL
>             through my
>             gpuR package.  In essence the context is selected at the R
>             level (one
>             context per device already initialized).  Then a matrix is
>             created on
>             that device.  The code looks like this:
>
>             create_matrix <- function(id){
>             # sets context
>             setContext(id)
>             # create matrix
>             mat <- vclMatrix(rnorm(16), nrow=4, ncol=4)
>             return(mat)
>             }
>
>             # a fork over context 1 and 2
>             out <- mclapply(1:2, function(x) create_matrix(x))
>
>             Yet, strangely this just hangs.  It doesn't return
>             anything.  Perhaps I
>             am missing something in how OpenCL contexts are handed in
>             parallel?  I
>             ask as I recall that PETSC had some multi GPU functionality
>             with MPI.
>             The above makes sense to me without MPI but again I may be
>             missing
>             something.
>
>             The actual copying happens in this file at line 36
>             (https://github.com/cdeterman/gpuR/blob/develop/src/dynVCLMat.cpp)
>             just
>             after "starting to copy".  It seems almost like it a problem
>             with the
>             class objects (defined in
>             
> https://github.com/cdeterman/gpuR/blob/develop/inst/include/gpuR/dynVCLMat.hpp).
>
>             Any insight would be appreciated.
>
>             Regards,
>             Charles
>
>
>             
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