New – Amazon EC2 C7g Instances, Powered by AWS Graviton3 Processors
I am excited to announce that Amazon Elastic Compute Cloud (Amazon EC2) C7g instances powered by the latest AWS Graviton3 processors that have been available in preview since re:Invent last year are now available for all. Let’s decompose the name C7g: the “C” instance family is designed for compute-intensive workloads. This is the 7th generation…
Let’s decompose the name C7g: the “C” instance family is designed for compute-intensive workloads. This is the 7th generation of this instance family. And the “g” means it is based on AWS Graviton, the silicon designed by AWS. These instances are the first instances to be powered by the latest generation of AWS Graviton, the Graviton3 processors.
As you bring more diverse workloads to the cloud, and as your compute, storage, and networking demands increase at a rapid pace, you are asking us to push the price performance boundary even further so that you can accelerate your migration to the cloud and optimize your costs. Additionally, you are looking for more energy-efficient compute options to help you reduce your carbon footprint and achieve your sustainability goals. We do this by working back from your requests, and innovating at a rapid pace across all levels of the AWS infrastructure. Our Graviton chips offer better performance at lower cost along with enhanced capabilities. For example, AWS Graviton3 processors offer you enhanced security with always-on memory encryption, dedicated caches for every vCPU, and support for pointer authentication.
Let’s illustrate this with numbers. When we launched Graviton2-based instances, they provided up to 40 percent better price/performance for a wide variety of workloads over comparable fifth-generation x86-based instances. We now have 12 instance families (M6g, M6gd, C6g, C6gd, C6gn, R6g, R6gd, T4g, X2gd, Im4gn, Is4gen, and G5g) that are powered by AWS Graviton2 processors that provide significant price performance benefits for a wide range of workloads. In 2021, we saw tens of thousands of AWS customers take advantage of this innovation by using Graviton2-based EC2 instances.
Our next generation, Graviton3 processors, deliver up to 25 percent higher performance, up to 2x higher floating-point performance, and 50 percent faster memory access based on leading-edge DDR5 memory technology compared with Graviton2 processors.
Graviton3 also uses up to 60 percent less energy for the same performance as comparable EC2 instances, which helps you reduce your carbon footprint.
Snap Inc, known for its popular social media services such as Snapchat and Bitmoji, adopted AWS Graviton2-based instances to optimize their price performance on Amazon EC2. Aaron Sheldon, software engineer at Snap, told us: “We trialed the new AWS Graviton3-based Amazon EC2 C7g instances and found that they provide significant performance improvements on real workloads compared to previous generation C6g instances. We are excited to migrate our Graviton2-based workloads to Graviton3, including messaging, storage, and friend graph workloads.”
The C7g instances are available in eight sizes with 1, 2, 4, 8, 16, 32, 48, and 64 vCPUs. C7g instances support configurations up to 128 GiB of memory, 30 Gbps of network performance, and 20 Gbps of Amazon Elastic Block Store (EBS) performance. These instances are powered by the AWS Nitro System, a combination of dedicated hardware and a lightweight hypervisor.
The following table summarizes the key characteristics of each instance type in this family.
Instance Name
vCPUs
Memory
Network Bandwidth
EBS Bandwidth
c7g.medium
1
2 GiB
up to 12.5 Gbps
up to 10 Gbps
c7g.large
2
4 GiB
up to 12.5 Gbps
up to 10 Gbps
c7g.xlarge
4
8 GiB
up to 12.5 Gbps
up to 10 Gbps
c7g.2xlarge
8
16 GiB
up to 15 Gbps
up to 10 Gbps
c7g.4xlarge
16
32 GiB
up to 15 Gbps
up to 10 Gbps
c7g.8xlarge
32
64 GiB
15 Gbps
10 Gbps
c7g.12xlarge
48
96 GiB
22.5 Gbps
15 Gbps
c7g.16xlarge
64
128 GiB
30 Gbps
20 Gbps
C7g instances are initially available in US East (N. Virginia) and US West (Oregon) AWS Regions; other Regions will be added shortly after launch.
As usual, you can purchase C7g capacity on demand, as Reserved Instances, or as Spot instances, and use your Saving Plans. The pricing details are available on the EC2 pricing page.
I have the chance to talk with AWS customers on a daily basis, and many of my discussions are around price performance and the sustainability of their workloads. With more than 500 instance types to choose from, one question I often receive is: what are the workloads that would benefit from C7g?
You will find that C7g instances provide the best price performance within their instance families for a broad spectrum of compute-intensive workloads, including application servers, micro services, high-performance computing, electronic design automation, gaming, media encoding, or CPU-based ML inference. These instances are ideal for all Linux-based workloads, including containerized and micro service-based applications built using Amazon Elastic Kubernetes Service (EKS), Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Container Registry, Kubernetes, and Docker, and written in popular programming languages such as C/C++, Rust, Go, Java, Python, .NET Core, Node.js, Ruby, and PHP.
The next question I receive is: given that Graviton instances are based on Arm architecture, how difficult is it to migrate from x86?
Graviton3 instances are supported by a broad choice of operating systems, independent software vendors, container services, agents, and developer tools, enabling you to migrate your workloads with minimal effort.
Applications and scripts written in high-level programming languages such as Python, Node.js, Ruby, Java, or PHP will typically just require a redeployment. Applications written in lower-level programming languages such as C/C++, Rust, or Go will require a re-compilation.
For those of you building with serverless, we have also released Graviton support for AWS Fargate and AWS Lambda, extending the price, efficiency, and performance benefits of Graviton to serverless workloads. Lambda functions using Graviton2 can see up to 34 percent better price/performance.
We do our part in this shared responsibility model, and now, it is your turn. You can use our innovations and tools to help you optimize your workloads and only use the resources you need. Take the occasion to write clever code that uses fewer CPU cycles, less storage, or less network bandwidth. And be sure to select energy-efficient options, such as Graviton3-based instance types or managed services, when deploying your code.
If you’d like to get started with Graviton-based instances for free, we also just reintroduced the free trial on T4g.small instances for up to 750 hours/month until the end of this year (December 31, 2022).
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In this post, we provide a detailed, hands-on guide to implementing Fast Model Loader in your LLM deployments. We explore two approaches: using the SageMaker Python SDK for programmatic implementation, and using the Amazon SageMaker Studio UI for a more visual, interactive experience. Whether you’re a developer who prefers working with code or someone who…
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