Hi,

Can anyone suggest how to retain data in GPU memory across two mexcuda functions? The basic steps followed are shown below:

```
1. Initialize data array 'A' using MATLAB
2. Transfer data to GPU memory using mexcuda function #1 and compute sum of array elements --> CUDA Kernel 1
3. Call mexcuda function#2 to compute the square of all elements of array 'A' (which is already stored in GPU memory) --> CUDA Kernel 2
```

Clarification:

How to share the data between mexcuda function #1 and #2 so that the step 3 does not need transfer of data array ‘A’ again to GPU memory?

P.S: For simplification purposes, the array ‘A’ is initialized to 10 elements. Actually I have an array with >1000 elements as well as additional computations.

Thanks in advance

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data array A[0] = 0.5;

data array A[1] = 1.5;

data array A[2] = 2.5;

data array A[3] = 3.5;

data array A[4] = 4.5;

data array A[5] = 5.5;

data array A[6] = 6.5;

data array A[7] = 7.5;

data array A[8] = 8.5;

data array A[9] = 9.5;

data array A[10] = 10.5;