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Questions tagged [gpu]

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3
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2answers
59 views

How to use a NN architecture that is too big for GPU?

Initially posted in Stack Overflow. I would like to implement a model which is actually 2 neural networks stacked together. However the size of these 2 architecture is too big to fit in GPU at the ...
0
votes
0answers
19 views

Multiple GPU in MXNet C++

I am trying to make MXNet (C++ API) learn, with a common sample in C++, on multiple GPU. According to this MXNet forum post, we need to aggregate manually the gradients that we fetch at the ...
0
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0answers
7 views

How can GPU speed up RNN with Sequence Data (no shuffle)?

It has been stated that CuDNNLSTM with GPU support greatly speeds up training compared to LSTM on CPU in Keras. But if I am working with sequence data in a time series, how can the data be processed ...
1
vote
1answer
23 views

How to speed up passing of images to a GPU

I am using Ubuntu 16.04 LTS installed on a 4TB HDD. I am working with a large dataset (more than 30 GB and 150,000 images). I have a single 11GB GTX 1080 Ti GPU card on my system. I am training a mask ...
0
votes
1answer
21 views

Validation loss differs on GPU vs CPU

I am consistently seeing higher validation loss when I train & evaluate a model on AWS GPU vs local CPU. I am using the exact same train/eval datasets and the exact same Tensorflow code and ...
0
votes
0answers
46 views

Threadripper, multicores vs GPU for Keras

I am approaching building new Deep Learning rig on Linux. I have a couple of machines I use for development for my Deep Learning projects. What is important is the speed of various CPUs. I have ...
0
votes
1answer
209 views

can't install tensorflow with gpu [closed]

I'm trying to install Tensorflow using GPU with CUDA 9.0. I have downloaded and installed CuDNN v 7.0.5. However when I want to train a model on Keras I get an issue: ...
0
votes
1answer
169 views

Multiple keras models parallel - time efficient

I am trying to load two different keras models in parallel. I tried to use the functional API model: ...
1
vote
0answers
33 views

Deep Learning in Spark Clusters vs on GPUs?

What would be a better way to perform deep learning on any given task, either using Spark Clusters or by taking advantage of GPU's multiple cores. Which would give less training time and be better ...
1
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0answers
28 views

Neuroevolution library/framework with GPU CUDA support

I'm looking for working library/framework allowing you to use neuroevolution algorithms like NEAT with GPU support (CUDA). Are there any working libraries? I know about AccNEAT library but I couldn't ...
0
votes
1answer
21 views

When memory errors occur with model.fit(), is it due to GPU RAM or normal RAM?

With respect to this question, https://stackoverflow.com/questions/51895278/how-to-know-when-to-use-fit-generator-in-keras-when-training-data-gets-too-big when memory errors are reported due to ...
2
votes
1answer
71 views

Is GEMM used in Tensorflow, Theano, Pytorch

I know that Caffe uses GEneral Matrix to Matrix Multiplication (GEMM) which is part of Basic Linear Algebra Subprograms (BLAS) library for performing convolution operations. Where a convolution is ...
0
votes
1answer
41 views

Running a python script with heavy memory requirements [closed]

I need to run a python script where I am loading several(~15) large modules including keras and load several (approx 20) LSTM models and large amount of data for computation. These script has several ...
0
votes
0answers
20 views

Memory Run-out While Fetching Data

I am trying to reproduce deep video portrait(2018) and I'd already comprised model refererencing pix2pix(2017). I am borrowing V100 Volta 16GB GPU from the AWS and ...
0
votes
0answers
12 views

Neural Networks vs Hardware: Approach Question

I'm trying to find a good neural network topology to run on CogniMem FPGA device. But I want to clarify if my approach is correct:- Is a type of hardware (like FPGA or GPU) good for one type of ...
1
vote
0answers
196 views

Model Parallelism not working? Inception v3 with keras and tensorflow

I have been stuck with a problem like this for a while now. I have an AWS setup with 500 GB of ram and about 7 GPUs. Now the issue is that each time I try to run my keras with tensorflow as back-end ...
0
votes
1answer
24 views

Moving from macbook (without GPU) to linux system with Titan V, only getting a 4x speedup, what am I doing wrong?

I was prototyping a network architecture out on the macbook, and after finding something I was somewhat happy with, I wanted to test it out on a big data set on a system with a Titan V as the macbook ...
2
votes
0answers
215 views

Why Tensorflow does NOT quit when CUDA_ERROR_OUT_OF_MEMORY

It was my understanding that when trying to create a tensorflow session, if the amount of available GPU memory is not enough for what the program asks for, the program should raise an error and exit. ...
1
vote
1answer
49 views

How to setup my Ubuntu PC for these Deep Learning frameworks? [closed]

I need to use both NVIDIA Digits and tensorflow Object Detection API for different deep learning purposes. I am a bit lost with the compatibility issues, especially for what concerns CUDA. So which ...
0
votes
0answers
122 views

What should be the value of parallel iterations in tensorflow RNN implementations?

tf.nn.dynamic_rnn() and tf.nn.raw_rnn() take in an argument called parallel_iterations. The documentation says: ...
2
votes
0answers
146 views

GPU Processing in R (using openCL)

I am trying to estimate a parameter by repeated sampling (Monte Carlo simulation). Each time I sample, I have to run a particular operation on a data.table object. ...
0
votes
0answers
48 views

how much GPU RAM is needed for Locally-connected layer

I want to implement DeepFace, which is very successful architecture in face recognition,in DeepFace network they used ...
2
votes
0answers
183 views

External GPU vs. internal GPU for machine learning

What are the pros/cons of using external GPUs (e.g., connected through thunderbolt) vs. internal GPUs for machine learning?
0
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0answers
18 views

Error after activation of theano enviroment in Amazon ec2 Deep Learing AMI

After activate Theano_p36 enviroment in an Deep Learning AMI on amazon ec2 I get the following error: ...
0
votes
0answers
211 views

Keras/Tensorflow and memmap files

I am trying to read a large dataset to train on a simple network using one GPU. The dataset is created as 5 large NumPy files (one for each column) and I am trying to read it with: user_id = np.load('...
3
votes
2answers
378 views

Accelerate deep learning model training on several GPUs

I have a deep learning model that can be trained in one GPU, however, is very slow. Is there a way to accelerate the training by parallelizing it across several GPUs? How would be the training process?...
16
votes
3answers
12k views

Multi GPU in keras

How you can program keras library (or tensorflow) to partitionate training on multiple GPU, let's say you are in an amaozn ec2 instance that has 8 GPU's and you want to use all of them to train faster,...
6
votes
3answers
5k views

Should I use GPU or CPU for inference?

I'm running a deep learning neural network that has been trained by a GPU. I now want to deploy this to multiple hosts for inference. The question is what are the conditions to decide whether I should ...
1
vote
0answers
480 views

Trying to use GPU of laptop for TensorFlow [closed]

I have an HP au111tx laptop with Nvidia 940mx graphics card. Is it possible for me to use this graphics card exclusively for ML. I want to use the integrated graphics card for normal display. I can ...
1
vote
1answer
4k views

What is the difference between Pytorch's DataParallel and DistributedDataParallel?

I am going through this imagenet example. And, in line 88, the module DistributedDataParallel is used. When I searched for the same in the docs, I haven’t found anything. However, I found the ...
2
votes
0answers
372 views

What are the key differences between FPGA and GPUs for Deep Learning?

I'm trying to investigate the ways in which FPGAs differ to GPUs for the purpose of deep learning. I understand this is a complex question and not necessarily easy to answer in one go, however what I'...
0
votes
0answers
340 views

Running Tensorflow script on multiple nodes on cluster

I am working on a cluster having 4 nodes and 4 GPUs in total. I wanted to run my Tensorflow script on multiple nodes with GPUs at the backend. Can someone guide me about what changes should I ...
0
votes
2answers
4k views

Does any cloud service provide free GPU access?

Is there any cloud developer platform which provides free access to an NVIDIA GPU instance, maybe only for a limited trial period? I'd like to work on it before committing to a paid option. I have ...
10
votes
1answer
959 views

GPU Accelerated Data Processing for R in Windows

I'm currently taking a paper on Big Data which has us utilising R heavily for data analysis. I happen to have a GTX1070 in my pc for gaming reasons. Thus, I thought it would be really cool if I could ...
0
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0answers
112 views

Is there any single disadvantage to use GPU in deep learning?

In most cases I frequently heard that to make a deep learning experiment, it is highly recommended to use GPU. It makes the computation blazingly faster than CPU, and sounds like a magical tool (...
22
votes
3answers
18k views

Choosing between CPU and GPU for training a neural network

I've seen discussions about the 'overhead' of a GPU, and that for 'small' networks, it may actually be faster to train on a CPU (or network of CPUs) than a GPU. What is meant by 'small'? For ...
4
votes
2answers
594 views

What does images per second mean when benchmarking Deep Learning GPU?

I've been reviewing performance of several NVIDIA GPU's and I see that typically results are presented in terms of "images per second" that can be processed. Experiments are typically being performed ...
6
votes
2answers
14k views

What is the best hardware/GPU for deep learning? [closed]

What is the best GPU for deep learning currently available on the market? I've heard that Titan X Pascal from NVidia might be the most powerful GPU available at the moment, but would be interesting ...
1
vote
0answers
180 views

Machine learning graphics card - half precision performance

Are there any consumer level graphics cards (i.e. less than, say, $1500) that have decent half precision (fp16) support? The latest Titan X was rumoured to have native fp16 support but that didn't ...
14
votes
3answers
13k views

Using TensorFlow with Intel GPU

I am a newb in deep learning. Is there no way now to use TensorFlow with Intel GPUs? If yes, please point me in the right direction. If not, please let me know which framework, if any, (Keras, Theano,...
4
votes
1answer
2k views

Input Pipeline for Tensorflow on GPU

The tensorflow example CIFAR10 uses input pipelines to load data from the disk to a queue. I would like to implement this for my own models, but I run into an error that I can't fix somehow. My ...
8
votes
3answers
4k views

CNN memory consumption

I'd like to be able to estimate whether a proposed model is small enough to be trained on a GPU with a given amount of memory If I have a simple CNN architecture like this: ...
4
votes
1answer
110 views

Estimating Titan X graphics card impact on performance

I'm currently training CNNs using Tensorflow (Python) on my GTX 970 (specs here). I recently took a look at the new pascal based Titan Xs and I'm wondering what an estimated performance/speed gain ...
0
votes
2answers
765 views

Which deep learning framework have support for gtx580 GPU? [closed]

I would like to train convolutional neural networks using a gtx580 gpu. I tried setting up TensorFlow but it did not work (wrong cuda compute compability). Which deep learning framework can best ...
5
votes
1answer
441 views

After the training phase, is it better to run neural networks on a GPU or CPU?

Sorry if this is the wrong forum for the question. My understanding was GPUs were more efficient for running neural nets, but someone recently suggested GPUs are only needed for the training phase. ...
1
vote
1answer
2k views

Making Keras + Tensorflow code execution deterministic on a GPU

I'm executing this code from https://www.kaggle.com/danijelk/allstate-claims-severity/keras-starter-with-bagging-lb-1120-596 on a nvidia geforce 960M. ...
8
votes
1answer
6k views

Why doesn't training RNNs use 100% of the GPU?

I wonder why training RNNs typically doesn't use 100% of the GPU. For example, if I run this RNN benchmark on a Maxwell Titan X on Ubuntu 14.04.4 LTS x64, the GPU utilization is below 90%: The ...
1
vote
2answers
893 views

Benchmarks based on neural networks libraries to compare the performance between different GPUs

I am looking for benchmarks based on neural networks libraries (Theano/TensorFlow/Torch/Caffe/…) to compare the performance between different GPUs. I am aware of: https://github.com/jcjohnson/cnn-...
2
votes
0answers
73 views

GPU Utilisation Issues

I observed that my GPU's memory is being consumed but the Utilisation stays 0. Because of this, my model is taking forever to load. I have tweaked this code to handle multilabel data. The only changes ...
2
votes
3answers
23k views

Switching Keras backend Tensorflow to GPU

I use Keras-Tensorflow combo installed with CPU option (it was said to be more robust), but now I'd like to try it with GPU-version. Is there a convenient way to switch? Or shall I re-install fully ...