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	Update outdated GPU section. (#629)
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					@ -836,11 +836,14 @@ EC2
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	-	Avoid sharing keys and [add individual ssh keys](http://security.stackexchange.com/questions/87480/managing-multiple-ssh-private-keys-for-a-team) for individual users.
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						-	Avoid sharing keys and [add individual ssh keys](http://security.stackexchange.com/questions/87480/managing-multiple-ssh-private-keys-for-a-team) for individual users.
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-	**GPU support:** You can rent GPU-enabled instances on EC2 for use in machine learning or graphics rendering workloads.
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					-	**GPU support:** You can rent GPU-enabled instances on EC2 for use in machine learning or graphics rendering workloads.
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	-	There are [three generations](http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using_cluster_computing.html) of GPU-enabled instances available:
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						-	There are [three types](http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using_cluster_computing.html) of GPU-enabled instances currently available:
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		- Third generation P2 series offers NVIDIA K80 GPUs in 1, 8 and 16 GPU configurations targeting machine learning and scientific workloads.
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							- The P3 series offers NVIDIA Tesla V100 GPUs in 1, 4 and 8 GPU configurations targeting machine learning, scientific workloads, and other high performance computign applications.
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		- Second generation G2 series offers NVIDIA K520 GPUs in 1 or 4 GPU configurations targeting graphics and video encoding.
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							- The P2 series offers NVIDIA Tesla K80 GPUs in 1, 8 and 16 GPU configurations targeting machine learning, scientific workloads, and other high performance computign applications.
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		- First generation CG1 instances are still available in some regions in a single configuration with a NVIDIA M2050 GPU.
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							- The G3 series offers NVIDIA Tesla M60 GPUs in 1, 2, or 4 GPU configurations targeting graphics and video encoding.
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	-	⛓ AWS offers an [AMI](https://aws.amazon.com/marketplace/pp/B01M0AXXQB?qid=1475211685369&sr=0-1&ref_=srh_res_product_title) (based on Amazon Linux) with most NVIDIA drivers and ancillary software (CUDA, CUBLAS, CuDNN, TensorFlow) installed to lower the barrier to usage. Note, however, that this leads to lock-in due to Amazon Linux and the fact that you have no direct access to software configuration or versioning.
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						-	AWS offers two different AMIs that are targeted to GPU applications. In particular, they target deep learning workloads, but also provide access to more stripped-down driver-only base images.
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							-	AWS offers both an Amazon Linux [Deep Learning AMI](https://aws.amazon.com/marketplace/pp/B077GF11NF?qid=1536363169916&sr=0-3&ref_=srh_res_product_title) (based on Amazon Linux) as well as an Ubuntu [Deep Learning AMI](https://aws.amazon.com/marketplace/pp/B077GCH38C). Both come with most NVIDIA drivers and ancillary software (CUDA, CUBLAS, CuDNN, TensorFlow, PyTorch, etc.) installed to lower the barrier to usage. 
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							-	⛓ Note that using these AMIs can lead to lock in due to the fact that you have no direct access to software configuration or versioning.
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							-	🔸 The compendium of frameworks included can lead to long instance startup times and difficult-to-reason-about environments.
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	-	🔹As with any expensive EC2 instance types, [Spot instances can offer significant savings](#ec2-cost-management) with GPU workloads when interruptions are tolerable.
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						-	🔹As with any expensive EC2 instance types, [Spot instances can offer significant savings](#ec2-cost-management) with GPU workloads when interruptions are tolerable.
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- All current EC2 instance types can take advantage of IPv6 addressing, so long as they are launched in a subnet with an allocated CIDR range in an IPv6-enabled VPC.
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					- All current EC2 instance types can take advantage of IPv6 addressing, so long as they are launched in a subnet with an allocated CIDR range in an IPv6-enabled VPC.
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