Amazon EC2 Capacity Blocks for ML expands to P4d instances
Today, Amazon Web Services announces that Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML now supports P5 instances in the US East (N. Virginia) Region and P4d instances in the US East (Ohio) and US West (Oregon) Regions. You can use EC2 Capacity Blocks to reserve highly sought-after GPU instances in Amazon EC2 UltraClusters for a future date for the amount of time that you need to run your machine learning (ML) workloads.
Today, Amazon Web Services announces that Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML now supports P5 instances in the US East (N. Virginia) Region and P4d instances in the US East (Ohio) and US West (Oregon) Regions. You can use EC2 Capacity Blocks to reserve highly sought-after GPU instances in Amazon EC2 UltraClusters for a future date for the amount of time that you need to run your machine learning (ML) workloads.
EC2 Capacity Blocks enable you to reserve GPU capacity up to eight weeks in advance for durations of one to 14 days in cluster sizes of one to 64 instances (512 GPUs), giving you the flexibility to run a broad range of ML workloads. They are ideal for short duration pre-training and fine-tuning workloads, rapid prototyping, and for handling surges in inference demand. EC2 Capacity Blocks deliver low-latency, high-throughput connectivity through colocation in Amazon EC2 UltraClusters.
With this expansion, EC2 Capacity Blocks for ML are available for the following instance types and AWS Regions: P5 instances in US East (N. Virginia) and US East (Ohio); P4d instances in US East (Ohio) and US West (Oregon).
To get started, visit the AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs. To learn more, see the Amazon EC2 Capacity Blocks for ML User Guide.