Скачать или смотреть PipelineAI TensorFlow GPU Workshop LA NIPS Conference December 2017

http://pipeline.ai

Title

PipelineAI Distributed Spark ML + Tensorflow AI + GPU Workshop

Note: A GPU-based cloud instance will be provided to each attendee as part of this event!!

Time

Start: 9am PT Time

End: 1pm PT Time

Highlights

We will each build an end-to-end, continuous Tensorflow AI model training and deployment pipeline on our own GPU-based cloud instance.

At the end, we will combine our cloud instances to create the LARGEST Distributed Tensorflow AI Training and Serving Cluster in the WORLD!

Pre-requisites

Just a modern browser, internet connection, and a good night's sleep! We'll provide the rest.

Agenda

Spark ML

TensorFlow AI

Storing and Serving Models with HDFS

Trade-offs of CPU vs. *GPU, Scale Up vs. Scale Out

CUDA + cuDNN GPU Development Overview

TensorFlow Model Checkpointing, Saving, Exporting, and Importing

Distributed TensorFlow AI Model Training (Distributed Tensorflow)

TensorFlow's Accelerated Linear Algebra Framework (XLA)

TensorFlow's Just-in-Time (JIT) Compiler, Ahead of Time (AOT) Compiler

Centralized Logging and Visualizing of Distributed TensorFlow Training (Tensorboard)

Distributed Tensorflow AI Model Serving/Predicting (TensorFlow Serving)

Centralized Logging and Metrics Collection (Prometheus, Grafana)

Continuous TensorFlow AI Model Deployment (TensorFlow, Airflow)

Hybrid Cross-Cloud and On-Premise Deployments (Kubernetes)

High-Performance and Fault-Tolerant Micro-services (NetflixOSS)

More Info including GitHub and Docker Repos

http://pipeline.ai