Comments (4)
I have the required environment set up. In fact by just changing that I am not able to cut down the running time of my application. Thank you.
from neuralnetworks.
You may not get any runtime improvement even if it does move it to the GPU - it really depends on how big the networks you're working with are...
from neuralnetworks.
I've tried GPU, CPU, and SEQ for MINST testLeNetSmall, testSigmoidHiddenBP and XorTest testCNNMLPBP and none of them give a speed-up for GPU. In fact, sometimes CPU is faster, but never GPU. Can anyone give an example of a network that would benefit from being run on the GPU?
from neuralnetworks.
I got the GPU run faster, but only by making huge networks that would take forever to complete for example I modified the testLenetSmall
function to have this network:
NeuralNetworkImpl nn = NNFactory.convNN(new int[][] { { 28, 28, 1 }, { 5, 5, 120, 1 }, { 2, 2 }, { 5, 5, 120, 1 }, { 2, 2 }, { 3, 3, 120, 1 }, { 2, 2 }, {2048}, {2048}, {10} }, true);
Basically I added a 3rd convolutional net, bumped up the number of filters in in all covnets to 120 (from 20 and 50), quadrupled the neurons in the final hidden layer and added another hidden layer with 2048 neurons. The GPU enabled version runs about 2.4 times faster, but it's still dog slow taking something like 12 - 14 seconds per batch (the batch size is 1) so training the entire dataset of 60000 images would take 8.3 to 9.7 days. So like 10 days per epoch on the GPU. Meanwhile I built a comparable network in Lasagne/Theano and it takes around 420 seconds per epoch on the CPU (in a VM at that) which is about 2000 times faster.
from neuralnetworks.
Related Issues (20)
- Is it possible to implement sparse autoencoder with your lib? HOT 1
- Simple forward example? HOT 1
- Test case MnistTest fail on every tests HOT 2
- Index out of range: 0 -> 89+0 to 0
- Differences between Java1.7 and Java1.8 neyral net libraries
- MnistTest.testLeNetSmall fails with 90% error rate HOT 1
- XOR test fails
- Train method fails in MultipleNeuronsOutputError.getTotalErrorSamples
- Saving/Loading networks
- DBN with softmaxlayer on top
- How to run the project in Eclipse ?
- Can the examples run without opencl.so ?
- neuralnetworks is 2000 times slower using GPU than Theano using CPU HOT 1
- How can I train my net with deep learning ?
- OS Differences
- Strange behavior when calculating Layers (probably Aparapi related) HOT 2
- Execution mode GPU failed: OpenCL execution seems to have failed (runKernelJNI returned -51) com.aparapi.internal.exception.AparapiException: OpenCL execution seems to have failed (runKernelJNI returned -51)
- OpenCl problem
- Is this repo dead ? HOT 3
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from neuralnetworks.