The document presents a discussion by Vincent Van Steenbergen on distributed deep learning using Apache Spark on AWS. It highlights the importance of training models efficiently and the benefits of using cloud computing resources, such as AWS GPU instances, to enhance deep learning capabilities. Notably, the results indicate a significant speedup in training times and improved accuracy in image classification tasks.

1. DISTRIBUTED DEEP
LEARNING
SPARK ON AWS
Presented by Vincent Van Steenbergen - @nsteenv

2. WHOAMI
VINCENT VAN STEENBERGEN
Data Engineer @ Abstract Minds
Playing with Scala, Akka & Spark +/- 3 years
Deeply interested in Artificial Intelligence and Data Analysis

3. DISCLAIMER

4. DEEP LEARNING
convolutional neural networks

5. APPLICATIONS

6. IMAGE ANALYSIS

7. IMAGE GENERATION

8. GAMES

9. TRAINING A MODEL REQUIRES:
a lot of time
even more computing power
Ex: AlphaGo - 1202 CPU and 176 GPU

10. SO HOW CAN I DO THAT...
from my laptop?
for a decent cost?
within a short timespan?
possible on a laptop but very slow
solution: distribute training over a cluster

11. APACHE SPARK
Scala/Python framework for big data analysis
Like Hadoop but faster

12. ADVANTAGES
Able to handle potentially Tb of data in streaming
Parallelise operations on a big cluster of machines
Improves accuracy of results

13. AMAZON WEB SERVICES (EC2)
GPU instances (g2.2xlarge, g2.8xlarge)
Spot instances (on demand, generally 2-3 times cheaper
than regular instances)

14. G2.8XLARGE CONFIGURATION
Four NVIDIA GRID GPUs, each with 1,536 CUDA cores and 4
GB of video memory
32 vCPUs
60 GiB of memory
240 GB (2 x 120) of SSD storage
Average price: $1.00 per hour

15. NOT BAD...

16. DEEP LEARNING FRAMEWORKS
TensorFlow (Google)
Caffe (Berkeley)

17. MNIST DATASET
Handwriten digits dataset

18. CROSS VALIDATION

19. COMPUTATION TIME

20. RESULTS
7x speedup compared to training the models one at a time
on one machine
best result with hyperparameter tuning has a 99.47%
accuracy on the test set
which is a 34% reduction of the test error.

21. IMAGE CLASSIFICATION

22. RESULTS
('coral reef', 0.88503921),
('scuba diver', 0.025853464),
('brain coral', 0.0090828091),
('snorkel', 0.0036010914),
('promontory, headland, head, foreland', 0.0022605944)])

23. THANK YOU!
Any questions?
My email: v.vansteenbergen@gmail.com

24. RESSOURCES
Sample launch scripts
Neural Networks
Deep Learning
cuDNN