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Fix typo "computign" in two places (#702)

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Christopher Malerich 2019-05-22 08:49:09 -04:00 committed by Maish
parent 6fff0a76a4
commit b4aafff90f

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@ -850,8 +850,8 @@ EC2
- **GPU support:** You can rent GPU-enabled instances on EC2 for use in machine learning or graphics rendering workloads.
- There are [three types](http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using_cluster_computing.html) of GPU-enabled instances currently available:
- 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.
- 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.
- The P3 series offers NVIDIA Tesla V100 GPUs in 1, 4 and 8 GPU configurations targeting machine learning, scientific workloads, and other high performance computing applications.
- The P2 series offers NVIDIA Tesla K80 GPUs in 1, 8 and 16 GPU configurations targeting machine learning, scientific workloads, and other high performance computing applications.
- The G3 series offers NVIDIA Tesla M60 GPUs in 1, 2, or 4 GPU configurations targeting graphics and video encoding.
- 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.
- 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.