MATLAB: Select a GPU to be used by a function running in parallel(parfeval)

gpuguiimaqtoolMATLABparfeval

Hello,

I am using two GPUs in a GUI postprocessing images live.

I am using the 'FramesAcquiredFcn' as a hub to transfer data from the buffer to the CPU RAM memory ('getdata') and launch a 'parfeval' function on GPU postprocessing these data. I have 1 pool with 3 workers initialized (one for the 'FramesAcquiredFcn' and one for each GPU). I can check that when the 'parfeval' function is not finished at the next iteration the second GPU is used instead. Now, I know that using 'wait' I can force the first GPU to be used.

However, I would like to split my postprocessing between these two GPUs because one is more powerful than the other. Hence, I would need the first 'parfeval' function to use the GPU1 pass the outputs (using 'afterEach'?) to an other parfeval function using the GPU2.

I have read the 'help selectGPU' but could not figure out how to modify it for my purpose.

Any help will be welcome.

Best Answer

I'd have to know what kind of postprocessing you're doing - please post some code. On the face of it, the answer is simply to use gpuDevice(i) to select a particular device for each of your parfeval calls.

Related Solutions

MATLAB: How to use multiple GPUs asynchronously

If you have 2 GPUs, you could use SPMD like this:

parpool('local', 2); % ensure the pool is of size 2
spmd
  % set each worker to use a GPU device based
  % on their "labindex"
  gpuDevice(labindex);
  x = gpuArray(...);
  if labindex == 1
    y1 = gpuFunction1(x);
  elseif labindex == 2
    y2 = gpuFunction2(x);
  end
end
% Note that y1 and y2 are 'Composite', so we must
% use indexing to retrieve the values
y1 = y1{1};
y2 = y2{2};

Note that the SPMD block approach shown is still synchronous with respect to the client. If you want the GPU work to be asynchronous with respect to the client, you need to use either batch (without a parallel pool open), or parfeval (with a parallel pool open).

Here's how you might use parfeval:

% setup as before
parpool('local', 2);
spmd, gpuDevice(labindex); end
% now invoke asynchronous work
x = gpuArray(...);
% Here the "1" is the number of outputs from gpuFunction#
f1 = parfeval(@gpuFunction1, 1, x);
f2 = parfeval(@gpuFunction2, 1, x);
% The MATLAB client is now idle, you can check to see if the
% work is done by examining the state:
disp(f1.State)
% Or, you can wait for the results - "fetchOutputs" blocks
% until the results are ready.
result1 = fetchOutputs(f1);
result2 = fetchOutputs(f2);

MATLAB: From multi-core CPU to GPU

PARFOR is meant for parallelizing tasks on CPU cores, not on the GPU. You cannot use GPU cores to parallelize complex MCode for-loops. They aren't the appropriate hardware for that.

Best Answer

Related Solutions

MATLAB: How to use multiple GPUs asynchronously

MATLAB: From multi-core CPU to GPU

Related Question