SageMaker Notebook Instances now support the ml.g5 instance family, and Python 3.8 kernels
New upgrades are now available for customers using Amazon SageMaker Notebook Instances, including the availability of the ml.g5 GPU instance family, and Python 3.8 support.
New upgrades are now available for customers using Amazon SageMaker Notebook Instances, including the availability of the ml.g5 GPU instance family, and Python 3.8 support.
Amazon SageMaker customers can now select ml.g5 instances powered by NVIDIA A10G Tensor Core GPUs, when creating an Amazon SageMaker Notebook Instance using the Amazon Linux 2 (AL2) operating system. ml.g5 instances feature up to 8 NVIDIA A10G Tensor Core GPUs and 2nd generation AMD EPYC processors. They also support up to 192 vCPUs, up to 100 Gbps of network bandwidth, and up to 7.6 TB of local NVMe SSD storage. Customers can choose the most appropriate instance size from eight options, offering between one and eight GPUs. To read more about ml.g5 instances, visit the AWS news blog or visit the G5 instance page to learn more.
Additionally, customers can now use Python 3.8 kernels with their notebooks on Amazon SageMaker Notebook instances. Customers can select from Conda images with Python 3.8 for either Pytorch or Tensorflow for their notebooks.
Python 3.8 kernels are available in all public AWS regions. ml.g5 instances are available in the following AWS regions: US East (N. Virginia), US West (Oregon) and Europe (Ireland).
To get started, visit the Amazon SageMaker console and select one of the eight ml.g5 instances available when creating a SageMaker Notebook on the AL2 operating system. Then select either conda_tensorflow2_p38 or conda_pytorch_p38 from among the various kernel options.