I would like to create Matlab GPU arrays that have a number of elements exceeding the max value of int32 (~2e9). In Matlab, when I try to do this, I get a "Max variable size exceeded" error. Other answers on this forum point to this limitation in GPU array size being caused by limitations in the CUDA API. However, I don’t believe this is accurate. Other languages, like Python 3.9 using theTensorflow 2.11 library for example, that are built on CUDA/CUBLAS allow for arrays that have a number of elements that exceed the MATLAB limitation.
Why is this the case, and why does Matlab seem limited where other languages are not?
The version of Matlab that I am using is 2024a, tested on both Win11 and Ubuntu 20.04LTS with a Nvidia Ada A6000 GPU (VRAM 48GB).
Matlab Code to reproduce:
g = gpuDevice();
arr = ones(1e4, 1e4, 60, ‘single’);
gpu_arr = gpuArray(arr);
Matlab ERROR:
Error using gpuArray
Maximum variable size allowed on the device is exceeded.
Python Code to reproduce:
import tensorflow as tf
arr = tf.ones([10000, 10000, 60])I would like to create Matlab GPU arrays that have a number of elements exceeding the max value of int32 (~2e9). In Matlab, when I try to do this, I get a "Max variable size exceeded" error. Other answers on this forum point to this limitation in GPU array size being caused by limitations in the CUDA API. However, I don’t believe this is accurate. Other languages, like Python 3.9 using theTensorflow 2.11 library for example, that are built on CUDA/CUBLAS allow for arrays that have a number of elements that exceed the MATLAB limitation.
Why is this the case, and why does Matlab seem limited where other languages are not?
The version of Matlab that I am using is 2024a, tested on both Win11 and Ubuntu 20.04LTS with a Nvidia Ada A6000 GPU (VRAM 48GB).
Matlab Code to reproduce:
g = gpuDevice();
arr = ones(1e4, 1e4, 60, ‘single’);
gpu_arr = gpuArray(arr);
Matlab ERROR:
Error using gpuArray
Maximum variable size allowed on the device is exceeded.
Python Code to reproduce:
import tensorflow as tf
arr = tf.ones([10000, 10000, 60]) I would like to create Matlab GPU arrays that have a number of elements exceeding the max value of int32 (~2e9). In Matlab, when I try to do this, I get a "Max variable size exceeded" error. Other answers on this forum point to this limitation in GPU array size being caused by limitations in the CUDA API. However, I don’t believe this is accurate. Other languages, like Python 3.9 using theTensorflow 2.11 library for example, that are built on CUDA/CUBLAS allow for arrays that have a number of elements that exceed the MATLAB limitation.
Why is this the case, and why does Matlab seem limited where other languages are not?
The version of Matlab that I am using is 2024a, tested on both Win11 and Ubuntu 20.04LTS with a Nvidia Ada A6000 GPU (VRAM 48GB).
Matlab Code to reproduce:
g = gpuDevice();
arr = ones(1e4, 1e4, 60, ‘single’);
gpu_arr = gpuArray(arr);
Matlab ERROR:
Error using gpuArray
Maximum variable size allowed on the device is exceeded.
Python Code to reproduce:
import tensorflow as tf
arr = tf.ones([10000, 10000, 60]) gpu, parallel computing toolbox, gpuarray, memory, vram, cuda, python MATLAB Answers — New Questions

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