Simplify Machine Learning with the Deep Learning AMI | AWS Floor28
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Machine Learning involves many different tools. Installing and setting them up properly is a time-consuming task, especially when working at scale. To solve this problem, AWS has built a collection of Amazon Machine Images (AMI) which package all the popular Machine Learning and Python tools: TensorFlow, PyTorch, conda and many more. In this session, we'll take you through a tour of these Deep Learning AMIs and we'll show you how to use them to speed up and simplify your projects.
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Simplify Machine Learning with the Deep Learning AMI | AWS Floor28
- 1. Keeping your sanity with the Deep Learning AMI Julien Simon Principal Technical Evangelist, AI and Machine Learning, AWS @julsimon
- 2. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Getting into Deep Learning, day 1 Deep Learning, yeah! Let’s create an EC2 instance and get to work!
- 3. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Getting into Deep Learning, day 5 Deep Learning, WTF! Security Group Python 3Python 2 Numpy Pandas Tensorflow Apache MXNet Gluon KerasTorch PyTorch ChainerHorovod ONNX Caffe Microsoft CNTK Theano Anaconda Model Serving Tensorboard Intel MKL CUDA 8.x/9.x GPU driversvirtualenv distributed training Jupyter pip
- 4. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Put Machine Learning in the hands of every developer and data scientist Our mission
- 5. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Application Services Platform Services Frameworks & Infrastructure API-driven services: Vision, Language & Speech Services, Chatbots AWS ML Stack Deploy machine learning models with high-performance machine learning algorithms, broad framework support, and one-click training, tuning, and inference. Develop sophisticated models with any framework, create managed, auto-scaling clusters of GPUs for large scale training, or run prediction on trained models.
- 6. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Application Services Platform Services Frameworks & Infrastructure API-driven services: Vision, Language & Speech Services, Chatbots AWS ML Stack Deploy machine learning models with high-performance machine learning algorithms, broad framework support, and one-click training, tuning, and inference. Develop sophisticated models with any framework, create managed, auto-scaling clusters of GPUs for large scale training, or run prediction on trained models.
- 7. The Deep Learning AMI
- 8. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. The Deep Learning AMI, minute 1 Focus on ML/DL, not on setup! Security Group Python 3Python 2 Numpy Pandas Tensorflow Apache MXNet Gluon KerasTorch PyTorch ChainerHorovod ONNX Caffe Microsoft CNTK Theano Anaconda Model Serving Tensorboard Intel MKL CUDA 8.x/9.x GPU driversvirtualenv distributed training Jupyter pip
- 9. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. AWS Deep Learning AMIs Preconfigured environments to quickly build Deep Learning applications Conda AMI For developers who want pre- installed pip packages of DL frameworks in separate virtual environments. Base AMI For developers who want a clean slate to set up private DL engine repositories or custom builds of DL engines. AMI with source code For developers who want preinstalled DL frameworks and their source code in a shared Python environment. https://aws.amazon.com/machine-learning/amis/
- 10. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon EC2 C5 / C5d instances AVX 512 72 vCPUs “Skylake” 144 GiB memory C5 12 Gbps to EBS 2X vCPUs 2X performance 3X throughput 2.4X memory C4 36 vCPUs “Haswell” 4 Gbps to EBS 60 GiB memory C5: N e xt Ge n e ra t io n Co m put e -Opt im ize d In st a n ce s wit h In t e l® X e o n ® Sca la ble Pro ce sso r A WS Co m put e o pt im ize d in st a n ce s suppo rt t h e n e w In t e l® A V X -512 a d v a n ce d in st ruct io n se t , e n a blin g y o u t o m o re e f f icie n t ly run v e ct o r pro ce ssin g wo rklo a d s wit h sin gle a n d d o uble f lo a t in g po in t pre cisio n , such a s A I/ m a ch in e le a rn in g o r v id e o pro ce ssin g. 25% improvement in price/performance over C4
- 11. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Faster TensorFlow training on C5 https://aws.amazon.com/blogs/machine-learning/faster-training-with-optimized-tensorflow-1-6- on-amazon-ec2-c5-and-p3-instances/
- 12. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. Amazon EC2 P3 Instances • P3.2xlarge, P3.8xlarge, P3.16xlarge • Up to eight NVIDIA Tesla V100 GPUs in a single instance • 40,960 CUDA cores, 5120 Tensor cores • 128GB of GPU memory • 1 PetaFLOPs of computational performance – 14x better than P2 • 300 GB/s GPU-to-GPU communication (NVLink) – 9x better than P2 T h e f a s t e s t , m o s t p o w e r f u l G P U i n s t a n c e s i n t h e c l o u d
- 13. Demo: start a p3 instance running the Deep Learning AMI
- 14. Demo: train a Tensorflow model and visualize training with TensorBoard
- 15. Demo: train a Tensorflow model and serve it with Tensorflow Model Server
- 16. Demo: work with Jupyter notebooks … or you could use notebook instances in Amazon SageMaker ;)
- 17. Resources https://ml.aws https://aws.amazon.com/machine-learning/amis/ https://medium.com/@julsimon
- 18. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Floor28 Agenda GameDay 24 Oct Enterprise IT Day 23 Oct Builders Day AppSync, Alexa & IoT 22 Oct Big Data Day 14 Oct ML & DL Day 15 Oct DevOps Day 16 Oct DevOps Day 17 Oct Technical Sessions Serverless Data Workshop Big Data UG Meetup Technical Sessions SageMaker Workshop ML&DL Meetup Technical Sessions K8s Workshop DevOps Meetup Technical Sessions Spot Workshop Databases Day 18 Oct Technical Sessions Serverless Workshop Virtual assistants UG Meetup Technical Sessions PyTorch Meetup Technical Sessions CDK Workshop AWS IL UG Meetup Builders Day Serverless backend 21 Oct Technical Sessions
- 19. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. SSID: Guest Password: Cube@11999 GAME DAY PUT YOUR SKILLS TO THE TEST OCT 24 Register now: bit.ly/Floor28GameDay
- 20. © 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved. https://amzn.to/2DAEUW8
- 21. Thank you! Julien Simon Principal Technical Evangelist, AI and Machine Learning @julsimon