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Now available: Graviton4-powered memory-optimized Amazon EC2 X8g instances

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Graviton-4-powered, memory-optimized X8g instances are now available in ten virtual sizes and two bare metal sizes, with up to 3 TiB of DDR5 memory and up to 192 vCPUs. The X8g instances are our most energy efficient to date, with the best price performance and scale-up capability of any comparable EC2 Graviton instance to date. With a 16 to 1 ratio of memory to vCPU, these instances are designed for Electronic Design Automation, in-memory databases & caches, relational databases, real-time analytics, and memory-constrained microservices. The instances fully encrypt all high-speed physical hardware interfaces and also include additional AWS Nitro System and Graviton4 security features.

Over 50K AWS customers already make use of the existing roster of over 150 Graviton-powered instances. They run a wide variety of applications including Valkey, Redis, Apache Spark, Apache Hadoop, PostgreSQL, MariaDB, MySQL, and SAP HANA Cloud. Because they are available in twelve sizes, the new X8g instances are an even better host for these applications by allowing you to choose between scaling up (using a bigger instance) and scaling out (using more instances), while also providing additional flexibility for existing memory-bound workloads that are currently running on distinct instances.

The Instances
When compared to the previous generation (X2gd) instances, the X8g instances offer 3x more memory, 3x more vCPUs, more than twice as much EBS bandwidth (40 Gbps vs 19 Gbps), and twice as much network bandwidth (50 Gbps vs 25 Gbps).

The Graviton4 processors inside the X8g instances have twice as much L2 cache per core as the Graviton2 processors in the X2gd instances (2 MiB vs 1 MiB) along with 160% higher memory bandwidth, and can deliver up to 60% better compute performance.

The X8g instances are built using the 5th generation of AWS Nitro System and Graviton4 processors, which incorporates additional security features including Branch Target Identification (BTI) which provides protection against low-level attacks that attempt to disrupt control flow at the instruction level. To learn more about this and Graviton4’s other security features, read How Amazon’s New CPU Fights Cybersecurity Threats and watch the re:Invent 2023 AWS Graviton session.

Here are the specs:

Instance Name vCPUs
Memory (DDR5)
EBS Bandwidth
Network Bandwidth
x8g.medium 1 16 GiB Up to 10 Gbps Up to 12.5 Gbps
x8g.large 2 32 GiB Up to 10 Gbps Up to 12.5 Gbps
x8g.xlarge 4 64 GiB Up to 10 Gbps Up to 12.5 Gbps
x8g.2xlarge 8 128 GiB Up to 10 Gbps Up to 15 Gbps
x8g.4xlarge 16 256 GiB Up to 10 Gbps Up to 15 Gbps
x8g.8xlarge 32 512 GiB 10 Gbps 15 Gbps
x8g.12xlarge 48 768 GiB 15 Gbps 22.5 Gbps
x8g.16xlarge 64 1,024 GiB 20 Gbps 30 Gbps
x8g.24xlarge 96 1,536 GiB 30 Gbps 40 Gbps
x8g.48xlarge 192 3,072 GiB 40 Gbps 50 Gbps
x8g.metal-24xl 96 1,536 GiB 30 Gbps 40 Gbps
x8g.metal-48xl 192 3,072 GiB 40 Gbps 50 Gbps

The instances support ENA, ENA Express, and EFA Enhanced Networking. As you can see from the table above they provide a generous amount of EBS bandwidth, and support all EBS volume types including io2 Block Express, EBS General Purpose SSD, and EBS Provisioned IOPS SSD.

X8g Instances in Action
Let’s take a look at some applications and use cases that can make use of 16 GiB of memory per vCPU and/or up to 3 TiB per instance:

Databases – X8g instances allow SAP HANA and SAP Data Analytics Cloud to handle larger and more ambitious workloads than before. Running on Graviton4 powered instances, SAP has measured up to 25% better performance for analytical workloads and up to 40% better performance for transactional workloads in comparison to the same workloads running on Graviton3 instances. X8g instances allow SAP to expand their Graviton-based usage to even larger memory bound solutions.

Electronic Design Automation – EDA workloads are central to the process of designing, testing, verifying, and taping out new generations of chips, including Graviton, Trainium, Inferentia, and those that form the building blocks for the Nitro System. AWS and many other chip makers have adopted the AWS Cloud for these workloads, taking advantage of scale and elasticity to supply each phase of the design process with the appropriate amount of compute power. This allows engineers to innovate faster because they are not waiting for results. Here’s a long-term snapshot from one of the clusters that was used to support development of Graviton4 in late 2022 and early 2023. As you can see this cluster runs at massive scale, with peaks as high as 5x normal usage:

You can see bursts of daily and weekly activity, and then a jump in overall usage during the tape-out phase. The instances in the cluster are on the large end of the size spectrum so the peaks represent several hundred thousand cores running concurrently. This ability to spin up compute when we need it and down when we don’t gives us access to unprecedented scale without a dedicated investment in hardware.

The new X8g instances will allow us and our EDA customers to run even more workloads on Graviton processors, reducing costs and decreasing energy consumption, while also helping to get new products to market faster than ever.

Available Now
X8g instances are available today in the US East (N. Virginia), US West (Oregon), and Europe (Frankfurt) AWS Regions in On Demand, Spot, Reserved Instance, Savings Plan, Dedicated Instance, and Dedicated Host form. To learn more, visit the X8g page.

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