Hi Shivangi Giri,
I understand that you are seeking to speed up the script using the "Parallel Computing Toolbox" (PCT) or by shifting calculations to the GPU.
It depends upon the specific operations that you are performing.
- When dealing with a for loop where each iteration's calculations are independent of others, leverage the 'parfor' (parallel for) functionality.
- ‘parfor' enables parallelization of the loop, allowing independent calculations to be performed concurrently, thereby reducing overall execution time. Refer the following MATLAB document for more info,
- https://www.mathworks.com/help/parallel-computing/parfor.html
- https://www.mathworks.com/help/parallel-computing/parfor.html#:~:text=and%20Cloud.-,Test%20parfor%2DLoops%20by%20Switching%20Between%20Parallel%20and%20Serial%20Execution,-You%20can%20specify
- If you are performing operations on large set of data, then you can transfer the data to GPU and then proceed to perform the operation. This will improve runtime if the operation is supported on GPU. Refer the following MATLAB documentations for more info.
- https://www.mathworks.com/help/parallel-computing/gpuarray.html#:~:text=Use%20gpuArray%20to%20convert
- https://in.mathworks.com/help/parallel-computing/illustrating-three-approaches-to-gpu-computing-the-mandelbrot-set.html
Hope this is helpful.
