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Apsara File Storage NAS:Getting started (PAI-DSW)

Last Updated:Jun 13, 2024

Apsara File Storage NAS (NAS) is seamlessly integrated with Alibaba Cloud Platform For AI (PAI). You can configure a NAS file system as a dataset to persistently store data during deployment and training. This topic describes how to deploy a NAS file system on a Data Science Workshop (DSW) instance in the console.

Prerequisites

Step 1: Create a file system

If you have created a file system, go to the next step.

  1. Log on to the NAS console.

  2. In the lower part of the Overview page, click Create General-purpose NAS File System.

  3. On the General-purpose NAS (Pay-as-you-go) page, configure the parameters described in the following table.

    Parameter

    Description

    Region

    The file system and the DSW instance must reside in the same region. In this example, select the China (Hangzhou) region.

    Zone

    Select the zone where the vSwitch resides to prevent cross-zone latency. In this example, select Hangzhou Zone G.

    Storage Class

    Capacity

    Protocol Type

    NFS

    Recycle Bin

    We recommend that you enable the recycle bin feature. After you enable the feature, deleted files or directories are temporarily stored in the recycle bin to prevent accidental deletion.

    Lifecycle Management

    Configure the lifecycle management feature based on your business scenario. We recommend that you disable this feature.

    Encryption Type

    Select Not Encrypted.

    Data Backup

    Select Disable.

    Network Type

    Select VPC.

    VPC

    Select the VPC that you created from the drop-down list.

    vSwitch

    Select a vSwitch that resides in the VPC.

  4. Click Buy Now and follow the instructions to complete the payment.

Step 2: Create a DSW instance

This topic describes how to create a DSW instance in a shared resource group.

  1. Log on to the PAI console.

  2. On the Overview page, select a region in the top navigation bar.

  3. In the left-side navigation pane, click Workspaces. On the Workspace page, click the name of the workspace.

  4. In the left-side navigation pane of the workspace page, choose Model Training > Data Science Workshop (DSW) to go to the DSW page.

  5. Click New Instance.

  6. In the Configure Instance step, configure the key parameters described in the following table. Retain the default settings of other parameters. For more information, see Create a DSW instance.

    Parameter

    Description

    Region and Zone

    In this example, select China (Hangzhou).

    Instance Name

    You can customize the instance name. In this example, enter test_01.

    Resource Type

    In this example, select GPU Specifications and set the specification name to ecs.gn7i-c8g1.2xlarge.

    Storage

    In the Shared Datasets section, click Create Dataset. In the From Alibaba Cloud Create Dataset panel, configure the following parameters. Retain the default settings of other parameters. For more information about datasets, see Create and manage datasets.

    • Select Data Storage: Select General-purpose NAS file system.

    • Select File System: Select the file system whose name contains NAS. In this example, select the NAS file system created in the preceding step.

    Select Image

    In this example, select stable-diffusion-webui-develop:1.0.0-pytorch2.01-gpu-py310-cu117-ubuntu22.04 in Alibaba Cloud Image.

  7. In the Confirm step, check the parameter configurations, read and select Machine Learning DSW Terms of Service, and then click Create Instance.

    Creating a DSW instance requires about 10 minutes. After the DSW instance is created, it is in the Running state.

Step 3: Verify the mounting

  1. Return to the DSW page and click Open in the Actions column of the created DSW instance.

  2. On the DSW Instances page, click the Terminal tab in the top navigation bar. Then, follow the instructions to open the terminal.

  3. On the Terminal page, run the following command to check whether the NAS dataset is mounted:

    mount | grep nas

    If an output similar to the following example appears, the dataset is mounted.

    image.png

    In the command output, /mnt/data is the mount path that you specify when you create the DSW instance. Then, data and code can be stored persistently on condition that your NAS file system runs properly.

References