trains with cpu but not with gpu about cxxnet HOT 5 CLOSED

I guess you are using CUDA6
You can change

https://github.com/tqchen/mshadow/blob/master/mshadow/cuda/tensor_gpu-inl.cuh#L14

to

#if !defined(CUDA_ARCH) || CUDA_ARCH >= 200

On Thu, Nov 20, 2014 at 8:54 PM, lexbee [email protected] wrote:

Hi again,

I got everything setup with my own data. When I go to train with dev=gpu
the program just stops after "update round 0". There is no error given
(please see below). I get the same issue when I try to run the MNIST
example with gpu. dev=cpu makes everything work fine. I don't think there
is a problem with my cuda installation because it seems to recognize the
video card and I have used the gpu in other frameworks before. Any ideas?

lex@lex-lin:/Documents/cxxnet/bin$ ./cxxnet
../example/ImageNet/ImageNet.conf
Use CUDA Device 0: GeForce GTX TITAN Black
CXXNetTrainer, devCPU=0
ConvolutionLayer: nstep=15
ConvolutionLayer: nstep=9
ConvolutionLayer: nstep=43
ConvolutionLayer: nstep=26
ConvolutionLayer: nstep=26
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
SGDUpdater: eta=0.010000, mom=0.900000
SGDUpdater: eta=0.020000, mom=0.900000
node[0].shape: 256,3,227,227
node[1].shape: 256,96,55,55
node[2].shape: 256,96,55,55
node[3].shape: 256,96,27,27
node[4].shape: 256,96,27,27
node[5].shape: 256,256,27,27
node[6].shape: 256,256,27,27
node[7].shape: 256,256,13,13
node[8].shape: 256,256,13,13
node[9].shape: 256,384,13,13
node[10].shape: 256,384,13,13
node[11].shape: 256,384,13,13
node[12].shape: 256,384,13,13
node[13].shape: 256,256,13,13
node[14].shape: 256,256,13,13
node[15].shape: 256,256,6,6
node[16].shape: 1,1,256,9216
node[17].shape: 1,1,256,4096
node[18].shape: 1,1,256,4096
node[19].shape: 1,1,256,4096
node[20].shape: 1,1,256,4096
node[21].shape: 1,1,256,1000
ThreadImagePageIterator:image_list=/home/lex/Documents/cxxnet/lexutils/train.lst,
bin=/home/lex/Documents/cxxnet/tools/TRAIN.BIN
ThreadBufferIterator: buffer_size=2
ThreadImagePageIterator:image_list=/home/lex/Documents/cxxnet/lexutils/test.lst,
bin=/home/lex/Documents/cxxnet/tools/TEST.BIN
initializing end, start working
update round 0lex@lex-lin:/Documents/cxxnet/bin$

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#10.

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Bing XU (许冰)

Computing Science Department

University of Alberta

Tel: +1-780-680-8644
Skype: antinucleon

from cxxnet.

I have changed the master in mshadow to reflect that. This is a problem in recent update of nvcc compiler no longer support CUDA_ARCH

from cxxnet.

thank you for the quick response.

I tried adjusting the line myself and still no luck. I then erased mshadow directory and cxxnet in bin and recompiled from the master and still no luck

from cxxnet.

Maybe you can try make clean and do it over gain? You should be able to see some message like "compiled with 2.0"

from cxxnet.

make clean and recompile worked

thanks again!

from cxxnet.