Compute
Elastic Cloud Server
Huawei Cloud Flexus
Bare Metal Server
Auto Scaling
Image Management Service
Dedicated Host
FunctionGraph
Cloud Phone Host
Huawei Cloud EulerOS
Networking
Virtual Private Cloud
Elastic IP
Elastic Load Balance
NAT Gateway
Direct Connect
Virtual Private Network
VPC Endpoint
Cloud Connect
Enterprise Router
Enterprise Switch
Global Accelerator
Management & Governance
Cloud Eye
Identity and Access Management
Cloud Trace Service
Resource Formation Service
Tag Management Service
Log Tank Service
Config
OneAccess
Resource Access Manager
Simple Message Notification
Application Performance Management
Application Operations Management
Organizations
Optimization Advisor
IAM Identity Center
Cloud Operations Center
Resource Governance Center
Migration
Server Migration Service
Object Storage Migration Service
Cloud Data Migration
Migration Center
Cloud Ecosystem
KooGallery
Partner Center
User Support
My Account
Billing Center
Cost Center
Resource Center
Enterprise Management
Service Tickets
HUAWEI CLOUD (International) FAQs
ICP Filing
Support Plans
My Credentials
Customer Operation Capabilities
Partner Support Plans
Professional Services
Analytics
MapReduce Service
Data Lake Insight
CloudTable Service
Cloud Search Service
Data Lake Visualization
Data Ingestion Service
GaussDB(DWS)
DataArts Studio
Data Lake Factory
DataArts Lake Formation
IoT
IoT Device Access
Others
Product Pricing Details
System Permissions
Console Quick Start
Common FAQs
Instructions for Associating with a HUAWEI CLOUD Partner
Message Center
Security & Compliance
Security Technologies and Applications
Web Application Firewall
Host Security Service
Cloud Firewall
SecMaster
Anti-DDoS Service
Data Encryption Workshop
Database Security Service
Cloud Bastion Host
Data Security Center
Cloud Certificate Manager
Edge Security
Situation Awareness
Managed Threat Detection
Blockchain
Blockchain Service
Web3 Node Engine Service
Media Services
Media Processing Center
Video On Demand
Live
SparkRTC
MetaStudio
Storage
Object Storage Service
Elastic Volume Service
Cloud Backup and Recovery
Storage Disaster Recovery Service
Scalable File Service Turbo
Scalable File Service
Volume Backup Service
Cloud Server Backup Service
Data Express Service
Dedicated Distributed Storage Service
Containers
Cloud Container Engine
SoftWare Repository for Container
Application Service Mesh
Ubiquitous Cloud Native Service
Cloud Container Instance
Databases
Relational Database Service
Document Database Service
Data Admin Service
Data Replication Service
GeminiDB
GaussDB
Distributed Database Middleware
Database and Application Migration UGO
TaurusDB
Middleware
Distributed Cache Service
API Gateway
Distributed Message Service for Kafka
Distributed Message Service for RabbitMQ
Distributed Message Service for RocketMQ
Cloud Service Engine
Multi-Site High Availability Service
EventGrid
Dedicated Cloud
Dedicated Computing Cluster
Business Applications
Workspace
ROMA Connect
Message & SMS
Domain Name Service
Edge Data Center Management
Meeting
AI
Face Recognition Service
Graph Engine Service
Content Moderation
Image Recognition
Optical Character Recognition
ModelArts
ImageSearch
Conversational Bot Service
Speech Interaction Service
Huawei HiLens
Video Intelligent Analysis Service
Developer Tools
SDK Developer Guide
API Request Signing Guide
Terraform
Koo Command Line Interface
Content Delivery & Edge Computing
Content Delivery Network
Intelligent EdgeFabric
CloudPond
Intelligent EdgeCloud
Solutions
SAP Cloud
High Performance Computing
Developer Services
ServiceStage
CodeArts
CodeArts PerfTest
CodeArts Req
CodeArts Pipeline
CodeArts Build
CodeArts Deploy
CodeArts Artifact
CodeArts TestPlan
CodeArts Check
CodeArts Repo
Cloud Application Engine
MacroVerse aPaaS
KooMessage
KooPhone
KooDrive
Help Center/ ModelArts/ Model Development (To Be Offline)/ Performing a Training/ Viewing the Resource Usage of a Training Job

Viewing the Resource Usage of a Training Job

Updated on 2024-05-07 GMT+08:00

Operations

  1. On the ModelArts console, choose Training Management > Training Jobs from the navigation pane.
  2. In the training job list, click the name of the target job to go to the training job details page.
  3. On the training job details page, click the Resource Usages tab to view the resource usage of the compute nodes. The data of at most the last three days can be displayed. When the resource usage window is opened, the data is loading and refreshed periodically.

    Operation 1: If a training job uses multiple compute nodes, choose a node from the drop-down list box to view its metrics.

    Operation 2: Click cpuUsage, gpuMemUsage, gpuUtil, memUsage, npuMemUsage, or npuUtil to show or hide the usage chart of the parameter.

    Operation 3: Hover the cursor on the graph to view the usage at the specific time.

    Figure 1 Resource Usages
    Table 1 Parameters

    Parameter

    Description

    cpuUsage

    CPU usage

    gpuMemUsage

    GPU memory usage

    gpuUtil

    GPU usage

    memUsage

    Memory usage

    npuMemUsage

    NPU memory usage

    npuUtil

    NPU usage

Alarms of Job Resource Usage

You can view the job resource usage on the training job list page. If the average GPU/NPU usage of the job's worker-0 instance is lower than 50%, an alarm is displayed in the training job list.

Figure 2 Job resource usage in the job list

The job resource usage here involves only GPU and NPU resources. The method of calculating the average GPU/NPU usage of a job's worker-0 instance is: Summarize the usage of each GPU/NPU accelerator card at each time point of the job's worker-0 instance and calculate the average value.

Improving Job Resource Utilization

  • Increasing the value of batch_size increases GPU and NPU usage. You must decide the batch size that will not cause a memory overflow.
  • If the time for reading data in a batch is longer than the time for GPUs or NPUs to calculate data in a batch, GPU or NPU usage may fluctuate. In this case, optimize the performance of data reading and data augmentation. For example, read data in parallel or use tools such as NVIDIA Data Loading Library (DALI) to improve the data augmentation speed.
  • If a model is large and frequently saved, GPU or NPU usage is affected. In this case, do not save models frequently. Similarly, make sure that other non-GPU/NPU operations, such as log printing and training metric saving, do not affect the training process for too much time.

We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out more

Feedback

Feedback

Feedback

0/500

Selected Content

Submit selected content with the feedback