MATLAB: I know gpuarray could improve for large sized matrix multiplication, but does it also improve if it has very large symbolic elements

gpgpugpuarrayMATLABmatrix multiplication

Dear all,

Just as the question says, I know that gpuarray could improve large sized matrix multiplication. However, what if I have a huge symbolic expression for each elements? Would gpuarray still outperform cpu computation?

In another words, does GPGPU perform better than CPU in multiplication of both large matrix and large elements? Or does GPGPU excel in either one of the departments over CPU?

I'm asking this because if GPGPU only excel in one of the two departments, then it is possible that CPU can outperform GPGPU when the other department is significantly large. If so, then use of gpuarray may possibly worsen the performance.

Best Answer

There is no gpu support for the symbolic toolbox.

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MATLAB: Max Matrix Size for GPU Acceleration

The gpuArray support in Parallel Computing Toolbox cannot support arrays larger than the physical memory of your GPU, so you will not be able to use this support directly. You might be able to write a 'divide and conquer' algorithm to implement the matrix multiplication using the GPU to perform the actual multiplications, however whether this beats the multi-threaded CPU implementation in MATLAB would depend a lot not only on the GPU you have, but also the speed of the PCI bus.

MATLAB: Elementwise multiplication, function definition

[x, y] = meshgrid(linspace(0,400,400),linspace(0,30000,400));
A1 = -8.269000000000000;
m1 = 2.071000000000000;
m2 = 0.239700000000000;
B1 = -13.100000000000000;
n1 = 2.813000000000000;
B2 = -49.960000000000001;
n2 = 18.170000000000002;
z1 = (10^A1*x.^m1.*y.^m2+y.*(10^B1*x.^n1+10^B2*x.^n2))*100;
min(min(z1))

Best Answer

Related Solutions

MATLAB: Max Matrix Size for GPU Acceleration

MATLAB: Elementwise multiplication, function definition

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