Dataflow support for GPUs

This page provides background information on how GPUs work with Dataflow, including information about prerequisites and supported GPU types.

Using GPUs in Dataflow jobs lets you accelerate some data processing tasks. GPUs can perform certain computations faster than CPUs. These computations are usually numeric or linear algebra, often used in image processing and machine learning use cases. The extent of performance improvement varies by the use case, type of computation, and amount of data processed.

Prerequisites for using GPUs in Dataflow


Jobs using GPUs incur charges as specified in the Dataflow pricing page.


The following GPU types are supported with Dataflow:

GPU type worker_accelerator string
NVIDIA® L4 nvidia-l4
NVIDIA® A100 40 GB nvidia-tesla-a100
NVIDIA® A100 80 GB nvidia-a100-80gb
NVIDIA® Tesla® T4 nvidia-tesla-t4
NVIDIA® Tesla® P4 nvidia-tesla-p4
NVIDIA® Tesla® V100 nvidia-tesla-v100
NVIDIA® Tesla® P100 nvidia-tesla-p100

For more information about each GPU type, including performance data, see Compute Engine GPU platforms.

For information about available regions and zones for GPUs, see GPU regions and zones availability in the Compute Engine documentation.

Recommended workloads

The following table provides recommendations for which type of GPU to use for different workloads. The examples in the table are suggestions only, and you need to test in your own environment to determine the appropriate GPU type for your workload.

For more detailed information about GPU memory size, feature availability, and ideal workload types for different GPU models, see the General comparison chart on the GPU platforms page.

Workload A100 L4 T4
Model fine tuning Recommended
Large model inference Recommended Recommended
Medium model inference Recommended Recommended
Small model inference Recommended Recommended

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