- X = 60000 x 2
- Pairwise distance matrix size= 60000 x 60000 = 36 x 10^8 elements
"Maximum variable size allowed on the device is exceeded" error when using internal.stats.gpu.pdist2?
13 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Hello, I hope you are well. I'm encountering an issue with the pdist2 function on my GPUs. I have both an A6000 with 40 GB of memory and an A100 with 80 GB of memory,
load('Dataset_1.mat')
X=single(Dataset(:,[2 4]));
X_CPU = X(1:60000,:);
X_GPU = gpuArray(X_CPU); % Convert data to gpuArray
% Compute pairwise distances more efficiently
D = pdist2(X_GPU, X_GPU, 'squaredeuclidean');
but I'm getting the same error on both devices. the error as shown below
Error using internal.stats.gpu.pdist2 Maximum variable size allowed on the device is exceeded.
Error in gpuArray/pdist2 (line 262) [doTranspose,D] = internal.stats.gpu.pdist2(X.',Y.',dist,additionalArg,smallestLargestFlag,d.AvailableMemory);
How can I solve this error?
0 comentarios
Respuestas (1)
Meet
el 3 de Sept. de 2024
Hi Med,
When calculating pairwise distances for your dataset "Dataset_1.mat," you encounter memory constraints due to the following reasons:
NVIDIA libraries that MATLAB uses for GPU computation store array lengths as 32-bit integers, limiting arrays to a maximum of intmax('int32') elements. This imposes a hard limit on array size.
As a workaround, you can try applying the pairwise distance calculation to smaller chunks of your dataset. This method involves processing smaller portions of the data and storing the results in a final cell array. It achieves the same outcome as applying the “pdist2” function to the entire dataset but handles it in more manageable parts, which are then aggregated.
load('Dataset_1.mat')
X = single(Dataset(:,[2 4]));
X_CPU = X(1:60000,:);
X_GPU = gpuArray(X_CPU);
chunkSize = 10000; % Adjust chunkSize parameter based on available memory
numChunks = ceil(size(X_GPU, 1) / chunkSize);
% D_parts would store the final result of the pairwise distance of your dataset
D_parts = cell(numChunks, numChunks);
for i = 1:numChunks
idx1 = (i-1)*chunkSize + 1 : min(i*chunkSize, size(X_GPU, 1));
for j = 1:numChunks
idx2 = (j-1)*chunkSize + 1 : min(j*chunkSize, size(X_GPU, 1));
% Calculate distances for each chunk
D_chunk = pdist2(X_GPU(idx1, :), X_GPU(idx2, :), 'squaredeuclidean');
% Store the result in a cell array
D_parts{i, j} = gather(D_chunk); % gather to CPU if GPU memory is a constraint
end
end
You can refer to the resources below for more information:
0 comentarios
Ver también
Categorías
Más información sobre GPU Computing en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!