High Speed Pandas on an GPU in AWS Cloud with RAPIDS and NVIDIA NGC

High Speed Pandas on an GPU in AWS Cloud with RAPIDS and NVIDIA NGC

With NVIDIA RAPIDS you can have access to a highspeed Pandas-like dataframe that runs entirely in the GPU. This allows fast preprocessing and quick handoff to a GPU-based model such as deep learning or XGBoost. In this video I show you how to load data into S3 and EBS to be used by an NVIDIA NGC container.

With NVIDIA RAPIDS you can have access to a highspeed Pandas-like dataframe that runs entirely in the GPU. This allows fast preprocessing and quick handoff to a GPU-based model such as deep learning or XGBoost. In this video I show you how to load data into S3 and EBS to be used by an NVIDIA NGC container.

2:10 AWS File Systems 2:42 RAPIDS on Real Data 2:53 Kaggle Otto Group Challenge 3:09 Create an AWS S3 Bucket 3:26 Sending Data to AWS S3 3:55 Setting up AWS IAM Access 4:18 Create an AWS IAM Role for AWS EC2 4:44 Create an AWS IAM Policy 5:28 Create a new AWS EC2 Instance (with spot) 6:34 Connect to the Running EC2 Instance with Putty and Tunneling 7:00 Starting Docker on AWS EC2 7:09 Creating an AWS EBS Volume for EC2 8:37 Mount and format EBS Volume 11:24 Access NGC Images 13:52 Jeff's AWS Setup Chart 14:16 Accessing Jupyter NGC Instance 15:32 Using RAPIDS 18:20 Using XGBoost on an NVIDIA GPU

NVIDIA NGC:

https://ngc.nvidia.com/catalog

GitHub Files for RAPIDS Video:

https://github.com/jeffheaton/present...

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