DIGITS DEEP LEARNING GPU TRAINING SYSTEM

Transcription

1 DIGITS DEEP LEARNING GPU TRAINING SYSTEM

2 AGENDA 1 Introduction to Deep Learning 2 What is DIGITS 3 How to use DIGITS

3 Practical DEEP LEARNING Examples Image Classification, Object Detection, Localization, Action Recognition, Scene Understanding Speech Recognition, Speech Translation, Natural Language Processing Pedestrian Detection, Traffic Sign Recognition Breast Cancer Cell Mitosis Detection, Volumetric Brain Image Segmentation

4 What is DEEP LEARNING? Input Result

5 Image Classification with DNNs Training Inference cars buses trucks motorcycles truck

6 Image Classification with DNNs Training cars buses trucks motorcycles Typical training run Pick a DNN design Input 100 million training images spanning 1,000 categories One week of computation Test accuracy If bad: modify DNN, fix training set or update training parameters

7 Why are GPUs good for deep learning? Neural Networks GPUs Inherently Parallel Matrix Operations FLOPS GPUs deliver -- same or better prediction accuracy 28% % 16% 60 12% 7% faster results smaller footprint lower power person dog chair bird frog

8 Deep Learning Acceleration with GPUs CPU is 16 core Haswell E at 2.3 GHz, with 3.6 GHz Turbo GPU is NVIDIA Titan X

9 WHO IS USING DEEP Learning? Industry Use Cases Research Image Recognition Image Analytics for Creative Cloud Image Classification Recommendation Speech/Image Recognition Hadoop Search Rankings Face Recognition Gesture Recognition Video Search & Analytics Speech Recognition & Translation Recommendation Engines Indexing & Search

10 What is DIGITS Deep Learning GPU Training System

11 DIGITS Deep Learning GPU Training System Visualization tool for DNN training Use default network, import one, or design your own Import your training data from disk or web Monitor multiple trainings in parallel

12 DIGITS Deep Learning GPU Training System Who it is for Deep learning researchers Automotive Medical Researchers Defense Intelligent Video Analytics Web Companies Startups

13 DIGITS Deep Learning GPU Training System Available at developer.nvidia.com/digits Free to use v1.0 supports classification on images Future versions: More problem types and data formats (video, speech) (Also available on Github for advanced developers)

14 NVIDIA DIGITS Roadmap Version 1 March 2015 Version 2 Version 3 Support for image classification networks Visualize layer-wise responses Run locally, manage single- GPU jobs Caffe Additional image analysis network types Richer visual analysis tools Run locally, more job management options Additional frameworks Continued improvement to visualization tools Front end to cluster task scheduler API for easy framework integration 2015 Features Framework Support

15 Using DIGITS Deep Learning GPU Training System

16 Two options digits-devserver How to start DIGITS Starts a development server that listens on port 5000 digits-server Gunicorn application that listens on port You can configure this with nginx, and access DIGITS Main Console

17 Main Console Create your dataset Configure your Network DIGITS Workflow Create your database Configure your model Choose your database Start Training Choose a default network, modify one, or create your own

18 Main Console Create your dataset Configure your Network DIGITS Workflow Create your database Configure your model Choose your database Start Training Choose a default network, modify one, or create your own

19 Create the Database DIGITS can automatically create your training and validation set OR Insert the path to your train and validation set Image parameter options OR use a URL list Create your dataset

20 Create the Database images Image directory on host machine Insert the path to your images here DIGITS creates your training and validation set for you. truck person planes cats images images cars house dogs bikes

21 Create the Database Create Training and Validation Set Training Validation truck person planes cats images images cars house dogs bikes

22 Create the Database train cats planes Apply rotation, color distortion, noise to training set val

23 Creating the Database Training and validation data set information Category data information is posted Job status information displays here progress, completion, and errors

24 Main Console Create your dataset Configure your Network DIGITS Workflow Create your database Configure your model Choose a default network, modify one, or create your own Choose your database Start Training

25 Network Configuration Select training dataset OR choose a previous configuration OR add it here Choose a preconfigured network Insert your network here Start training

26 Network Configuration Select training dataset Select a standard network and start training OR Customize a Standard Network Choose a preconfigured network

27 Network Configuration Select training dataset Select a standard network and start training OR Make network changes here Customize a Standard Network Choose a preconfigured network

28 Network Configuration Select training dataset Select a standard network and start training OR Make network changes here Customize a Standard Network Choose a preconfigured network

29 Network Configuration Select training dataset Select a standard network and start training OR Make network changes here Choose a preconfigured network Customize a Standard Network Visualize your network

30 Network Configuration Select training dataset Select a standard network and start training OR Make network changes here Choose a preconfigured network Customize a Standard Network Visualize your network Start training Start training

31 DIGITS Download network files Visualize DNN performance in real time Compare networks Training status Classification Accuracy and loss values during training Learning rate Classification on the with the network snapshots

32 DIGITS Compare Networks

33 DIGITS Classify Multiple Images Upload a text file with URLs or images on the host machine

34 Thank you!

35 NVIDIA Resources Try out GPU Computing: developer.nvidia.com/cuda-education-training Subscribe to Parallel Forall blog: devblogs.nvidia.com/parallelforall CUDACasts at bit.ly/cudacasts Self-paced labs: nvidia.qwiklab.com 90-minute labs, simply need a supported web browser Sign up as a Registered Developer - Technical Questions: NVIDIA Developer forums devtalk.nvidia.com Search or ask on stackoverflow.com/tags/cuda GPU Technology Conference