using more than gpu

[Old posts from the commercial version of ArrayFire] Discussion of ArrayFire using CUDA or OpenCL.

Moderator: pavanky

using more than gpu

Postby pydive » Mon Dec 05, 2011 12:33 am

this is the output of ginfo using Jacket/matlab:

Detected CUDA-capable GPUs:
CUDA driver 270.81, CUDA toolkit 4.0
GPU0 Tesla C1060, 4096 MB, Compute 1.3 (single,double) (in use)
GPU1 Tesla C1060, 4096 MB, Compute 1.3 (single,double)
GPU2 Quadro FX 1800, 742 MB, Compute 1.1 (single)
Display Device: GPU2 Quadro FX 1800
The problem is :

1. Can I use the two Teslas at same time (parfor)? How?
2. How to know number of cores are currently running/executing the program?
3. After running the following code and make Quadro (in use) I found it takes less time than Tesla despite Tesla having 240 cores and Quadro has only 64? Maybe because it's the display device?maybe becouse it's single precision and Tesla is Double precision?

<!-- -->

clc; clear all;close all;
addpath ('C:/Program Files/AccelerEyes/Jacket/engine');
i = im2double(imread('cameraman.tif'));
i_gpu=gdouble(i);
h=fspecial('motion',50,45);% Create predefined 2-D filter
h_gpu=gdouble(h);
tic;
for j=1:500
x_gpu = imfilter( i_gpu,h_gpu );
end
i2 = double(x_gpu); %memory transfer
t=toc
figure(2), imshow(i2);

Any help with the code will be appreciated. As you can see it's very trivial example used to demonstrate power of GPU, no more.
pydive
 
Posts: 4
Joined: Mon Dec 05, 2011 12:31 am

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