Higher network bandwidths can improve the performance of distributed workloads. On Compute Engine, network bandwidth depends on machine type and the number of CPUs. For virtual machine (VM) instances that have attached GPUs, the configuration of your GPU count, CPU, and memory impacts the network bandwidth as well. For more information about GPUs, see GPUs on Compute Engine.
The maximum available bandwidth per attached GPUs on Compute Engine is as follows
- For VMs that have P100, P4, and K80 GPUs attached, a maximum bandwidth of 32 Gbps is available. This is similar to the maximum rate available to VMs that do not have GPUs attached. For more information about network bandwidths, see maximum egress data rate.
- For VMs that have V100, T4, and A100 GPUs attached, you can now get a maximum bandwidth of up to 50 or 100 Gbps, based on the GPU count. To create VM instances with V100, T4, and A100 GPUs that use up to 100 Gbps, see using network bandwidths of up to 100 Gbps.
Bandwidth configurations
The following tables summarize the maximum available network bandwidth for different VM configurations of A100, T4, and V100 GPU types.
V100 VM configuration
V100 VM configuration | Network bandwidth | ||
---|---|---|---|
GPU count | vCPUs | Memory | |
1 | 12 | 78 GB | 24 Gbps |
2 | 24 | 156 GB | 32 Gbps |
4 | 48 | 312 GB | 50 Gbpsbeta |
8 | 96 | 624 GB | 100 Gbpsbeta |
T4 VM configuration
T4 VM configuration | Network bandwidth | ||
---|---|---|---|
GPU count | vCPUs | Memory | |
1 | 24 | 156 GB | 32 Gbps |
2 | 48 | 312 GB | 50 Gbpsbeta |
4 | 96 | 624 GB | 100 Gbpsbeta |
A100 VM configuration
A100 VM configuration | Network bandwidth | ||
---|---|---|---|
Machine type (GPU count) | vCPUs | Memory | |
a2-highgpu-1g (1) | 12 | 85 GB | 24 Gbps |
a2-highgpu-2g (2) | 24 | 170 GB | 32 Gbps |
a2-highgpu-4g (4) | 48 | 340 GB | 50 Gbpsbeta |
a2-highgpu-8g (8) | 96 | 680 GB | 100 Gbpsbeta |
a2-megagpu-16 (16) | 96 | 1360 GB | 100 Gbpsbeta |
What's next?
- Learn more about GPUs on Compute Engine.
- Learn how to create VMs with attached GPUs.
- Learn about Optimizing GPU performance.
- Learn about GPU pricing.