The accelerator-optimized machine family is optimized for massively parallelized Compute Unified Device Architecture (CUDA) workloads, such as machine learning (ML) and high performance computing (HPC).
The accelerator-optimized machine family is available in A2 standard and ultra machine types, and the G2 standard machine type.
The accelerator-optimized machine family provides the following features:
- Next generation NVIDIA GPUs attached.
- For A2 accelerator-optimized machine types, NVIDIA A100 GPUs are attached. These are available in both A100 40GB and A100 80GB options.
- For G2 accelerator-optimized machine types, NVIDIA L4 GPUs are attached.
- High performance network bandwidth of up to 100 Gbps.
- Virtualization optimizations.
- Local SSD support— This can be used as fast scratch disks or for feeding
data into the A100 and L4 GPUs while preventing I/O bottlenecks.
- For the A2 and G2 standard machine types, you can add up to 3 TB of local SSD.
- For the A2 ultra machine types, local SSD is bundled with the machine.
You can also attach up to 257 TB of persistent disk storage to the machine types in this series for applications that require higher storage performance.
This machine family is built on the 2nd Generation Intel Xeon Platinum processor (Cascade Lake) and offers up to 3.7 GHz sustained single-core max turbo frequency.
| Machine | Workloads |
|---|---|
| A2 standard machine types |
|
| A2 ultra machine types |
|
| G2 standard machine types |
|
The A2 machine series
The A2 machine series is available in A2 standard and A2 ultra machine types. These machines have 12 to 96 vCPUs, and up to 1360 GB of memory.
The A2 machine series also provides the following features:
- Industry-leading NVLink scale that provides peak GPU to GPU NVLink bandwidth of 600 Gbps. For example, systems with 16 GPUs have an aggregate NVLink bandwidth of up to 9.6 Terabytes per second. These 16 GPUs can be used as a single high performance accelerator with unified memory space to deliver up to 10 petaFLOPS of compute power and up to 20 petaFLOPS of inference compute power that can be used for artificial intelligence, deep learning, and machine learning workloads.
- Next generation Computing speed— The attached NVIDIA A100 GPUs offer up to 10x improvements in computing speed when compared to previous generation NVIDIA V100 GPUs.
All A2 machine types are eligible for resource-based committed use discounts. A2 VMs are not eligible for sustained use discounts and flexible committed use discounts.
A2 standard machine series
These machine types have a fixed number of A100 40GB GPUs.
| Machine types | GPU count | vCPUs* | Memory (GB) | Max number of persistent disks (PDs)† | Max total PD size (TB) | Local SSD | Maximum egress bandwidth (Gbps)‡ |
|---|---|---|---|---|---|---|---|
a2-highgpu-1g |
1 | 12 | 85 | 128 | 257 | Yes | 24 |
a2-highgpu-2g |
2 | 24 | 170 | 128 | 257 | Yes | 32 |
a2-highgpu-4g |
4 | 48 | 340 | 128 | 257 | Yes | 50 |
a2-highgpu-8g |
8 | 96 | 680 | 128 | 257 | Yes | 100 |
a2-megagpu-16g |
16 | 96 | 1360 | 128 | 257 | Yes | 100 |
*A vCPU is implemented as a single hardware hyper-thread on one of
the available CPU platforms.
†Persistent disk usage is charged separately from
machine type pricing.
‡Maximum egress bandwidth cannot exceed the number given. Actual
egress bandwidth depends on the destination IP address and other factors.
See Network bandwidth.
A2 standard limitations
- You don't receive sustained use discounts for VMs that use A2 standard machine types.
- You can only use A2 standard machine types in certain regions and zones.
- The A2 standard machine types is only available on the Cascade Lake platform.
- You can't use regional persistent disks on VMs that use A2 standard machine types.
- You can't use the
a2-megagpu-16gA2 standard machine type on Windows operating systems. When using Windows operating systems, choose a different A2 standard machine type. - You can't do a quick format of the attached local SSDs on Windows VMs that use A2 standard
machine types. To format these local SSDs, you must do a full format by using the diskpart
utility and specifying
format fs=ntfs label=tmpfs.
A2 ultra machine series
These machine types have a fixed number of A100 80GB GPUs. Each A2 ultra machine also comes with up to 3 TB of local SSD attached.
| Machine types | GPU count | vCPUs* | Memory (GB) | Max number of persistent disks (PDs)† | Max total PD size (TB) | Bundled Local SSD | Maximum egress bandwidth (Gbps)‡ |
|---|---|---|---|---|---|---|---|
a2-ultragpu-1g |
1 | 12 | 170 | 128 | 257 | 375 GB | 24 |
a2-ultragpu-2g |
2 | 24 | 340 | 128 | 257 | 750 GB | 32 |
a2-ultragpu-4g |
4 | 48 | 680 | 128 | 257 | 1.5 TB | 50 |
a2-ultragpu-8g |
8 | 96 | 1360 | 128 | 257 | 3 TB | 100 |
*A vCPU is implemented as a single hardware hyper-thread on one of
the available CPU platforms.
†Persistent disk usage is charged separately from
machine type pricing.
‡Maximum egress bandwidth cannot exceed the number given. Actual
egress bandwidth depends on the destination IP address and other factors.
See Network bandwidth.
A2 ultra limitations
- You don't receive sustained use discounts for VMs that use A2 ultra machine types.
- You can only use A2 ultra machine types in certain regions and zones.
- The A2 ultra machine types is only available on the Cascade Lake platform.
- You can't use regional persistent disks on VMs that use A2 ultra machine types.
- You can't do a quick format of the attached local SSDs on Windows VMs that use A2 ultra
machine types. To format these local SSDs, you must do a full format by using the diskpart
utility and specifying
format fs=ntfs label=tmpfs. - You can't change the machine type for a VM that uses the A2 ultra machine family. If you need to use a different A2 ultra machine type, or any other machine family, you must create a new VM.
- You can't change any other machine type to an A2 ultra machine type. If you need to create a VM that uses an A2 ultra machine type, you must create a new VM.
The G2 machine series
The G2 machine series are available in standard machine types and have 4 to 96 vCPUs, and up to 432 GB of memory. This machine series is optimized for inference and graphics workloads.
The G2 machine series also provides the following features:
- Support for the FP8 (8-bit floating point) datatype which speeds up ML inference rates and reduces memory requirements.
- Next generation graphics performance— The attached NVIDIA L4 GPUs provide up to 3x improvements in graphics performance by using third-generation RT cores and NVIDIA DLSS 3 (Deep Learning Super Sampling) technology.
All G2 machine types are eligible for resource-based committed use discounts. G2 VMs are not eligible for sustained use discounts and flexible committed use discounts.
G2 standard machine series
Each G2 machine type has a fixed number of NVIDIA L4 GPUs and vCPUs attached. Each G2 machine type also has a default memory and a custom memory range. The custom memory range defines the amount of memory that you can allocate to your VM for each machine type. You can specify your custom memory during VM creation.
| Machine types | GPU count | vCPUs* | Default memory (GB) | Custom memory range (GB) | Max number of persistent disks (PDs)† | Max total PD size (TB) | Max local SSD supported (GB) | Maximum egress bandwidth (Gbps)‡ |
|---|---|---|---|---|---|---|---|---|
g2-standard-4 |
1 | 4 | 16 | 16 - 32 | 128 | 257 | 375 | 10 |
g2-standard-8 |
1 | 8 | 32 | 32 - 54 | 128 | 257 | 375 | 16 |
g2-standard-12 |
1 | 12 | 48 | 48 - 54 | 128 | 257 | 375 | 16 |
g2-standard-16 |
1 | 16 | 64 | 54 - 64 | 128 | 257 | 375 | 32 |
g2-standard-24 |
2 | 24 | 96 | 96 - 108 | 128 | 257 | 750 | 32 |
g2-standard-32 |
1 | 32 | 128 | 96 - 128 | 128 | 257 | 375 | 32 |
g2-standard-48 |
4 | 48 | 192 | 192 - 216 | 128 | 257 | 1500 | 50 |
g2-standard-96 |
8 | 96 | 384 | 384 - 432 | 128 | 257 | 3000 | 100 |
*A vCPU is implemented as a single hardware hyper-thread on one of
the available CPU platforms.
†Persistent disk usage is charged separately from
machine type pricing.
‡Maximum egress bandwidth cannot exceed the number given. Actual
egress bandwidth depends on the destination IP address and other factors.
See Network bandwidth.
G2 standard limitations
- You don't receive sustained use discounts for VMs that use G2 standard machine types.
- You can only use G2 standard machine types in certain regions and zones.
- The G2 standard machine types is only available on the Cascade Lake platform.
- You can't use regional persistent disks on VMs that use G2 standard machine types.
- Standard persistent disks (
pd-standard) are not supported on VMs that use G2 standard machine types. For supported disk types, see G2 standard VMs. - You can't create Multi-Instance GPUs on G2 standard machine types.
- You can't use Deep Learning VM Images as boot disks for your VMs that use G2 standard machine types.
- The current default driver for Container-Optimized OS, don't support L4 GPUs running on
G2 machine types. Container-Optimized OS also only support a select set of drivers.
If you want to use Container-Optimized OS on G2 machine types, review the following notes:
- Use a Container-Optimized OS version that supports the minimum recommended
NVIDIA driver version
525.60.13or later. For more information, review the Container-Optimized OS release notes. - When you install the driver,
specify the latest available version that works for the L4 GPUs.
For example,
sudo cos-extensions install gpu -- -version=525.60.13.
- Use a Container-Optimized OS version that supports the minimum recommended
NVIDIA driver version
- You need to use the Google Cloud CLI or the Compute Engine API to
create G2 VMs
for the following scenarios:
- You want to specify custom memory values.
- You want to customize the number of visible CPU cores.