Now shipping: Compute Engine machine types with up to 96 vCPUs and 624GB of memory
Hanan Youssef, Sami Iqram and Scott Van Woudenberg
Product Managers, Google Compute Engine
Got compute- and memory-hungry applications? We’ve got you covered, with new machine types that have up to 96 vCPUs and 624 GB of memory—a 50% increase in compute resources per Google Compute Engine VM. These machine types run on Intel Xeon Scalable processors (codenamed Skylake), and offer the most vCPUs of any cloud provider on that chipset. Skylake in turn provides up to 20% faster compute performance, 82% faster HPC performance, and almost 2X the memory bandwidth compared with the previous generation Xeon.1
96 vCPU VMs are available in three predefined machine types:
- Standard: 96 vCPUs and 360 GB of memory
- High-CPU: 96 vCPUs and 86.4 GB of memory
- High-Memory: 96 vCPUs and 624 GB of memory
You can also use custom machine types and extended memory with up to 96 vCPUs and 624GB of memory, allowing you to better create exactly the machine shape you need, avoid wasted resources, and pay for only what you use.
The new 624GB Skylake instances are certified for SAP HANA scale-up deployments. And if you want to run even larger HANA analytical workloads, scale-out configurations of up to 9.75TB of memory with 16 n1-highmem-96 nodes are also now certified for data warehouses running BW4/HANA.
You can use these new 96-core machines in beta today in four GCP regions: Central US, West US, West Europe, and East Asia. To get started, visit your GCP Console and create a new instance. Or check out our docs for instructions on creating new virtual machines using the gcloud command line tool.
Need even more compute power or memory? We’re also working on a range of new, even larger VMs, with up to 4TB of memory. Tell us about your workloads and join our early testing group for new machine types.
1 Based on comparing Intel Xeon Scalable Processor codenamed "Skylake" versus previous generation Intel Xeon processor codenamed "Broadwell." 20% based on SpecINT. 82% based on on High Performance Linpack for 4 node cluster with AVX512. Performance improvements include improvements from use of Math Kernel Library and Intel AVX512. Performance tests are measured using specific computer systems, components, software, operations and functions, and may have been optimized for performance only on Intel microprocessors. Any change to any of those factors may cause the results to vary. You should consult other information to assist you in fully evaluating your contemplated purchases. For more information go to http://www.intel.com/benchmarks↩