From CPU code to GPU

2021 8 19
2 个回答
更新时间：2021 9 16
6 次查看（30 天）

0 个投票

Hello Everybody
I have an heavy code, it's a Split-Step Fourier program, with different external function.
The main vector (the propagating one) is 2^16 to 2^18 point. It currently work as a classic CPU program.
My computer has a CUDADevice with properties: Name: 'Quadro RTX 4000'. So I try to tranlate my program.
Before that I test the speed of the GPU vs CPU with some code I found here. And It's faster, Perfect
To translate my program I do this modification
A=gpuArray(A);
B=gpuArray(B);
And I try to do it for the most variable I have, it's quite long and painfull
I also do it in the function I need to use, to be sure that the most part of the variable are GpuArray
BUT, it's slower...
I never use GPU before, so I guess I am doing something wrong..
Thanks for your time
Martin

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回答（2 个）

MartinM
MartinM 2021-8-19

0 个投票

for exemple
clc,clear all
close all
%% CPU
tic
num.n=1*2^18;
num.tspan = 2e-09;
num.dt=num.tspan/(num.n-1);
T = zeros(1, num.n);
for k=1:1:num.n
T(k)=(k-1)*num.dt-num.tspan/2;
end
toc
%% GPU
clear all
close all
tic
num.n=gpuArray(1*2^18);
num.tspan =gpuArray(2e-09);
num.dt=gpuArray(num.tspan/(num.n-1));
T = gpuArray(zeros(1, num.n));
for k=1:1:num.n
T(k)=(k-1)*num.dt-num.tspan/2;
end
toc
the result is
Elapsed time is 0.027964 seconds.
Elapsed time is 47.296786 seconds.
Joss Knight
Joss Knight 2021-9-16

0 个投票

You need to vectorize your code. The GPU is not intended for performing this kind of looping series of operations on scalar variables. For instance use
k = gpuArray(1:num.n);
T=(k-1)*num.dt-num.tspan/2;
to compute every element of T at once.
You do not need to convert every variable to a gpuArray, just your inputs.

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MartinM
MartinM
2021-8-19

回答：

Joss Knight
Joss Knight
2021-9-16

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