[Paraview] Non-blocking coprocessing

[Ufuk Utku Turuncoglu (BE)]

Hi Tim,

I am not sure about the non-blocking type communication is supported by 
ParaView, Catalyst or not but i think that assigning an extra core for 
global reduction is possible. You could use MPI communication for this 
purpose. So, look at following code of mine for overloaded 
coprocessorinitializewithpython function. As you can see, it also gets 
the MPI communicatior and it allows to use a pool of processor (or 
cores) for co-processing. In my case, it is running smoothly without any 
problem. I hope it helps.

--ufuk

extern "C" void my_coprocessorinitializewithpython_(int *fcomm, const 
char* pythonScriptName, const char strarr[][255], int *size) {
   if (pythonScriptName != NULL) {
     if (!g_coprocessor) {
       g_coprocessor = vtkCPProcessor::New();
       MPI_Comm handle = MPI_Comm_f2c(*fcomm);
       vtkMPICommunicatorOpaqueComm *Comm = new 
vtkMPICommunicatorOpaqueComm(&handle);
       g_coprocessor->Initialize(*Comm);
       vtkSmartPointer<vtkCPPythonScriptPipeline> pipeline = 
vtkSmartPointer<vtkCPPythonScriptPipeline>::New();
       pipeline->Initialize(pythonScriptName);
       g_coprocessor->AddPipeline(pipeline);
       //pipeline->FastDelete();
     }

     if (!g_coprocessorData) {
       g_coprocessorData = vtkCPDataDescription::New();
       // must be input port for all model components and for all dimensions
       for (int i = 0; i < *size; i++) {
         g_coprocessorData->AddInput(strarr[i]);
         std::cout << "adding input port [" << i << "] = " << strarr[i] 
<< std::endl;
       }
     }
   }
}

On 25/10/16 01:56, Gallagher, Timothy P wrote:
>
> Hello again!
>
>
> I'm looking at using coprocessing for something that may take awhile 
> to actually compute, so I would like to do it in a non-blocking 
> fashion. Essentially I am going to be extracting data from the 
> simulation into some numpy arrays (so once copied, the original data 
> in the pipeline can change) and then send it to the root processor to 
> do some global operations.
>
>
> The global operations may take some time (not minutes, but longer than 
> I want my simulation to wait for it to complete). Is there a way to do 
> part of the pipeline in a non-blocking fashion, where the script calls 
> a function that will write out a data file when processing and then 
> returns control to the simulation prior to the function completion? 
> Will I have to do something in native-python, like spawn a new thread 
> to do the function call, or is there a way to do it with how Paraview 
> operates?
>
>
> On a related note, I may not want to have the root processor of the 
> coprocessing to have any simulation code running on it. If I am 
> running my simulation on N cores, is it possible to have N+1 cores 
> running the coprocessor pipeline where the extra core receives the 
> global data reduction from the N cores and does the crunching? Or am I 
> starting to ask for too much there?
>
>
> Thanks as always,
>
>
> Tim
>
>
>
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