Intel® Geti™ 1.3.0#

Release Summary#

Among further improvements, Intel® Geti™ 1.3.0 contains the following update:

Release Details#

This section covers additional details on the new functionality available with Intel® Geti™ 1.3.0.

Expanded support for Dataset Management Framework (Datumaro) format#

The Intel® Geti™ 1.2.0 release introduced a feature to export and import datasets in Datumaro format for segmentation, detection, and single-label classification tasks. Now, all anomaly tasks are also supported.

Learn more about Datumaro’s capabilities here.

System Requirements for Intel® Geti™ 1.3.0#

The platform can be installed on a machine with the following minimum hardware requirements:

  • CPU for workstations: Intel® Core™ i7, Intel® Core™ i9 or Intel® Xeon® scalable processors family capable of running 20 concurrent threads (in case of using the default K3s) or 48 concurrent threads (in case of using pre-installed K8s).

Note

From Intel® Core™ family, we recommend the following CPU series:

  • 13th gen (Raptor Lake): Intel® Core™ i7 13700 series and Intel® Core™ i9 13900 series

  • 12th gen (Alder Lake): Intel® Core™ i9 12900 series

  • CPU for cloud deployments: CPUs capable of running min. 24 concurrent threads for K3s or min. 48 concurrent threads for K8s (so for example, on AWS EC2 instances, this requirement would be translated to min. 24 vCPUs for K3s or min. 48 vCPUs for K8s).

  • GPU: min. one NVIDIA GPU with min. 16GB of memory (e.g. RTX 3090, RTX 6000, RTX 8000, Tesla A100, Tesla V100, Tesla P100, or Tesla T4), other NVIDIA GPUs in a similar series are likely also compatible if they meet minimum memory requirements. However, the full range of devices is not fully tested and not specifically supported. We recommend 24GB of memory for the stable training & optimization.

  • Memory: min. 64 GB RAM (128 GB recommended)

  • Disk Space: min. 500 GB (1 TB recommended) for a root partition

Installation of the platform on a multinode configuration of Kubernetes cluster is not supported.