# Machine Learning on Amazon AWS GPU Instances

DevFeed: [Machine Learning on Amazon AWS GPU Instances](<https://devfeed.tech/articles/machine-learning-on-amazon-aws-gpu-instances-31830.md>)

Original publisher: [Read original article](<https://www.metachris.dev/2015/11/machine-learning-on-amazon-aws-gpu-instances/>)

Author: Chris Hager

Published: 2015-11-22T00:00:00Z

Content type: tutorial

Language: en

Sources: [Chris Hager](<https://devfeed.tech/sources/chris-hager.md>)

Topics: [GPU](<https://devfeed.tech/topics/gpu.md>), [Amazon EC2](<https://devfeed.tech/topics/amazon-ec2.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [Machine learning](<https://devfeed.tech/topics/machine-learning.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [Server](<https://devfeed.tech/topics/server.md>)

Tags: [aws](<https://devfeed.tech/tags/aws.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [python](<https://devfeed.tech/tags/python.md>), [s3](<https://devfeed.tech/tags/s3.md>), [save](<https://devfeed.tech/tags/save.md>), [servers](<https://devfeed.tech/tags/servers.md>), [storage](<https://devfeed.tech/tags/storage.md>)

## AI overview

A practical guide to using Amazon AWS GPU instances for machine learning. It describes the available G2 instance types, their NVIDIA GPU hardware, preinstalled AMIs, spot-instance pricing, model snapshots, S3 storage, AMIs, and EBS for large datasets.

## Source excerpt

Machine learning algorithms regularly utilize GPUs to parallelize computations, and Amazon AWS GPU Instances provide cheap and on-demand access to capable virtual servers with NVIDIA GPUs. GPU Instances come in two flavors: G2.2xlarge and G2.8xlarge: Model GPUs vCPU Mem (GiB) SSD Storage (GB) g2.2xlarge 1 8 15 1 x 60 g2.8xlarge 4 32 60 2 x 120 The GPU instances feature Intel Xeon E5-2670 (Sandy Bridge) Processors and NVIDIA GPUs with 1,536 CUDA cores and 4GB of video memory each.