The compute accelerator is optimized for graphics-intensive applications and machine learning inference.
This article originally appeared on ZDNet.
The Google Cloud Platform is adding the Nvidia Tesla P4 to its list of supported GPU offerings. The P4 is optimized for graphics-intensive applications and machine learning inference.
The low-latency accelerator is a good fit for machine learning inference use cases like visual search, interactive speech and video recommendations, Google said. As GPUs become increasingly important for running AI workloads, public cloud providers like Google, IBM, and Oracle have been competing to offer the latest from Nvidia on their cloud infrastructure.
SEE: Cloud migration decision tool (Tech Pro Research)
To support graphics-intensive applications, Google is also adding support for virtual workstations with Nvidia GRID on the P4 and the P100. GCP is also partnering with Teradici to deliver virtual workstations running on Google Compute Engine. Enabling virtual workstations should help customers that need to run cloud-based, compute-intensive tools, such as entertainment studios producing 3D content or industries like oil & gas.
GCP customers can attach one or multiple P4s to any machine type. P4s are now available in zones in us-central1 (Iowa), us-east4 (N. Virginia), Montreal (northamerica-northeast1) and europe-west4 (Netherlands), with more regions coming soon.
- Cloud v. data center decision (ZDNet special report) | Download the report as a PDF (TechRepublic)
- Google Cloud Platform breaks into leader category in Gartner's Magic Quadrant (ZDNet)
- Google Cloud Platform: A cheat sheet (TechRepublic)
- Google Cloud Next postmortem: The enterprise journey continues (ZDNet)
- Google Cloud Composer makes it simple to build cloud workflows with Python (TechRepublic)