At AWS re:Invent 2022, Adam Selipsky, CEO of AWS, explained high performance computing (HPC) workloads typically can either be compute-intensive, compute- and networking-intensive, or data- and memory-intensive in his keynote.
Compute workloads include weather forecasting, computational fluid dynamics, and financial options pricing. To help with this, you have Amazon EC2 Hpc6a instances, which deliver up to 65 percent better price performance over comparable compute optimized x86-based instances.
Other HPC workloads require modeling the performance of complex structures—things like wind turbines, concrete buildings, and industrial equipment. Without enough data and memory, these models can take days or weeks to run in a cost-effective way. The Amazon EC2 Hpc6id instance is designed to deliver leading price performance for data and memory-intensive HPC workloads with higher memory bandwidth per core, faster local solid-state drive (SSD) storage, and enhanced networking with Elastic Fabric Adapter (EFA).
Announcing Amazon EC2 Hpc7g Instances
Compute-intensive HPC workloads such as weather forecasting, computational fluid dynamics, and financial options pricing also require more network performance, even better price performance, and greater energy efficiency.
Today we are announcing the general availability of Amazon EC2 Hpc7g instances, a new purpose-built instance type for tightly coupled compute and network-intensive HPC workloads.
Hpc7g instances are powered by AWS Graviton3E processors that provide up to two times better floating-point performance and 200 Gbps dedicated EFA bandwidth than EC2 C6gn instances powered by AWS Graviton2 processors and are up to 60 percent more energy efficient than comparable x86 instances. AWS Graviton3E-based EC2 instances also provide up to 35 percent higher vector instruction processing performance than Graviton3 processors.
Here’s a quick infographic that shows you how the Hpc7g instances and the Graviton3E processors compare to previous instances and processors:
Hpc7g instances feature sizes of up to 64 cores of the latest AWS custom Graviton3E CPUs with 128 GiB RAM. Here are the detailed specs:
| Instance Name |
CPUs | RAM (GiB) |
EFA Network Bandwidth (Gbps) |
Attached Storage |
| hpc7g.4xlarge | 16 | 128 | Up to 200 | EBS Only |
| hpc7g.8xlarge | 32 | 128 | Up to 200 | EBS Only |
| hpc7g.16xlarge | 64 | 128 | Up to 200 | EBS Only |
Hpc7g instances are the most cost-efficient option to scale your HPC clusters on AWS. If you are considering migrating your largest HPC workloads requiring tens of thousands of cores at scale to AWS, you can take advantage of up to 200 Gbps EFA bandwidth to reduce the latency and run message passing interface (MPI) applications on parallel computing architectures while ensuring minimized power consumption on Hpc7g instances.
You can choose to use smaller sizes of Hpc7g instances to pick a lower number of cores and evenly distribute memory and network resources across the remaining cores to increase per-core performance to help reduce software licensing costs.
Reminder: You can learn a lot from AWS HPC engineers by subscribing to the HPC Tech Short YouTube channel, and following the AWS HPC Blog channel.