UiPath Documentation
ai-center
2022.4
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AI Center Installation Guide

Requirements

Overview

Note:

Before choosing your deployment profile, see Supported use cases for single-node and multi-node installations.

What you needRequirementsConfigurationInstallation

One Linux machine

(RHEL 8.2, 8.3, 8.4, 8.5, 8.6)

Single-node machine requirementsConfiguring the machines

SQL Server

(MS SQL 2016, 2017, 2019 - Enterprise and Standard)

-Configuring MS SQL Server-
DNS- -

Single-node machine requirements

This configuration is supported only for evaluation and demo scenarios.

BundleMinimumRecommended
(v-)CPU total16 (v-)CPU32 (v-)CPU
RAM52 GiB96 GiB
Cluster disk for each node256 GiB SSD

Min IOPS: 1100
256 GiB SSD

Min IOPS: 1100
Data disk512 GiB SSD for online

1 TiB SSD for offline

Min IOPS 1100
2 TiB SSD

Min IOPS 1100
etcd disk16 GiB SSD

Min IOPS: 240
16 GiB SSD

Min IOPS: 240
UiPath Bundle Disk

(For offline installation only, on the first server node)
512 GiB SSD

Min IOPS: 1100
512 GiB SSD

Min IOPS: 1100
Note:

Following the requirements above is enough for three skills and one pipeline running in parallel with the default configuration.

Additional agent node with GPU support for Document Understanding

BundleRequirement
(v-)CPU8 (v-)CPU
RAM52 GiB
Cluster disk256 GiB SSD

Min IOPS: 1100
Data diskN/A
GPU RAM11 GiB
Note:

Trainable Document Understanding ML Packages provided by UiPath will work on both CPU or GPU for datasets up to 500 images in size. GPU is strongly recommended to achieve faster training times and better model performance. Validation Station retraining loop is not supported on deployments without a GPU, due to the fact that dataset sizes increase too fast and may hit a compute wall with CPU very quickly. If you run UiPath Document OCR Local Server on AI Center to process more than 2 million pages of documents a year, GPU is strongly recommended for a better product experience.

  • Overview
  • Single-node machine requirements
  • Additional agent node with GPU support for Document Understanding

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