Amazon EC2 Hpc7a Instances
HPC-optimized instances powered by 4th Gen AMD EPYC processors
Amazon Elastic Compute Cloud (Amazon EC2) Hpc7a instances, powered by 4th Gen AMD EPYC processors, deliver up to 2.5x better performance compared to Amazon EC2 Hpc6a instances. Hpc7a instances feature 2x higher core density (up to 192 cores), 2.1x higher memory bandwidth throughput, 2x memory (768 GB), and 3x higher network bandwidth compared to Hpc6a instances. These instances offer 300 Gbps of Elastic Fabric Adapter (EFA) network bandwidth, powered by the AWS Nitro System, for fast and low-latency internode communications. Hpc7a instances feature Double Data Rate 5 (DDR5) memory, which provides 50% higher memory bandwidth compared to DDR4 memory to enable high-speed access to data in memory. These instances are ideal for compute-intensive, latency-sensitive HPC workloads, helping you scale more efficiently on fewer nodes when compared to Hpc6a instances.
Hpc7a instances are designed to run your tightly coupled HPC workloads such as computational fluid dynamics (CFD), weather forecasting, and multiphysics simulations with better performance.
Benefits
Fast results
With 300 Gbps EFA networking, you have access to a high-throughput, low-latency, low-jitter channel for tightly coupled workloads. EFA networking allows you to scale faster and reduce time-to-insight for your HPC workloads.
Operational flexibility and efficiency
Instance size options help you manage costs for your workloads that are licensed on a per-core basis. Right-size your workload resources by choosing the ideal cores per node while continuing to harness available memory and network bandwidth, regardless of the instance size that you select. Additionally, with AWS ParallelCluster, you can provision Hpc7a instances alongside other instance types within the same cluster. This gives you the flexibility to run different workloads optimized for different instances within your cluster.
Maximized resource efficiency
Hpc7a instances benefit from the Nitro System, a collection of building blocks that offloads many of the traditional virtualization functions to dedicated hardware and software. The Nitro System is used to deliver high performance, high availability, and increased security.
Features
High performance compute, networking, and storage
Hpc7a instances are powered by up to 192 cores of 4th Gen AMD EPYC processors with 768 GiB total memory (up to 8 GiB of memory per core) for the most demanding HPC workloads. It uses the latest-generation Nitro Cards and EFA, which deliver 300 Gbps of network throughput to interconnected nodes. EFA is designed to help applications get the lowest latency and highest throughput from the AWS network. You can also use Amazon FSx for Lustre for sub-millisecond latencies and up to hundreds of gigabytes per second of throughput for storage.
Instance sizing options and cluster management
Hpc7a instances offer 24-, 48-, 96-, and 192-core 4th Gen AMD EPYC processors. The larger 192-core size delivers greater efficiency when compared to Hpc6a instances powered by 3rd Gen AMD EPYC processors, while the ability to choose among multiple sizes helps you optimize cores per node for your specific workload. Additionally, ParallelCluster uses a simple graphical user interface (GUI) or text file to model and provision the resources needed for your HPC applications in an automated and secure manner.
Built on the Nitro System
The Nitro System can be assembled in multiple ways, giving AWS the flexibility to design and rapidly deliver EC2 instance types with an ever-broadening selection of compute, storage, memory, and networking options. Nitro Cards offload and accelerate I/O for functions, ultimately increasing overall system performance.
Product details
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Hpc7a
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Hpc7a
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Amazon EC2 Hpc7a instances deliver better performance compared to Hpc6a instances. Hpc7a instances feature 2x higher core density (up to 192 cores), 2.1x higher memory bandwidth throughput (768 GB of memory), and 3x higher network bandwidth compared to Hpc6a instances.
Instance Size Physical Cores Memory (GiB) Instance Storage EFA Network Bandwidth (Gbps) Network Bandwidth (Gbps) hpc7a.12xlarge
24
768
EBS-Only 300
25
hpc7a.24xlarge
48
768
EBS-Only 300
25
hpc7a.48xlarge
96
768
EBS-Only 300
25
hpc7a.96xlarge
192
768
EBS-Only 300
25
*500 Mbps network bandwidth outside the virtual private cloud (VPC) and Amazon Simple Storage Service (Amazon S3).
What's new
Customers and partners
"With Amazon EC2 Hpc7a instances, we speed our HPC workloads on AWS. Hpc7a instances provide Ferrari 30% performance improvement for our CFD workloads, 25% performance improvement for our finite element analysis (FEA) workloads, and lower costs when compared to previous-generation instances."
Silvia Gabrielli, Chief Digital & Data Officer, Ferrari
"To deliver high-level operational intelligence for weather-dependent industries, DTN deploys a suite of weather data and models that deliver sophisticated, high-resolution outputs and require continual processing of vast amounts of data from inputs across the globe. Our collaboration with AWS allows us to better serve our customers with the most up-to-date weather intelligence that feed those analytic engines. We are excited to see how the next generation of Amazon EC2 Hpc7a instances can potentially support our mission to provide customers with the insights they need at the moment they are needed."
Lars Ewe, Chief Technology Officer, DTN
"AWS is used in various divisions and competencies across the entire University of Michigan Solar Car team to accelerate and improve our simulation, analysis, and software development. We’ve been able to run 1,000 CFD simulations and increase our vehicle’s performance by 20% in the span of two months thanks to fast turnaround on high-fidelity simulations. The release of Amazon EC2 Hpc7a instances will help us to further experiment with ways to increase the number of CFD simulations we can run to accelerate our designs."
Thomas Capderou, Aerodynamics Division Lead, University of Michigan Solar Car Team
"Using AWS across the entire University of Michigan Solar Car team has helped us improve our processes associated with the simulation, analysis, and development projects we can run. Transitioning our team’s software and in-house simulation infrastructure to AWS has had a significant impact on our iteration speed and expanded the scope of several ongoing projects. The launch of Amazon EC2 Hpc7a instances will help us to investigate ways to further expand project scope and 300 Gbps interconnect using EFA introduces the potential for us to iterate our designs even faster."
Ibrahim Syed, Strategy Division Lead, University of Michigan Solar Car Team
"We're excited about how the launch of the Amazon EC2 Hpc7a instances, such as more cores and high-speed network bandwidth, can enable Syngene researchers to run large molecular dynamics simulations and virtual screening quickly to accelerate drug discovery for our customers over alternatives while being cost efficient with flexibility and resiliency."
Dr. Anand Kumar Raichurkar, Lead Investigator, Section Head: CADD, Computational Data Sciences, Syngene
"As an AWS HPC competency partner, TotalCAE can better serve our customers by enabling them to run engineering workloads on HPC-optimized Amazon EC2 instances. The release of Amazon EC2 Hpc7a instances is an exciting announcement from AWS that enables TotalCAE to meet and exceed our customer requirements for computer-aided engineering (CAE) workloads to accelerate digital product design. Hpc7a instances, based on 4th Gen AMD EPYC processors, combine 300 Gbps leading EFA interconnect technology with the powerful and secure AWS Nitro System, helping our customers solve critical challenges using CFD and multiphysics simulations."
Rod Mach, President, TotalCAE
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