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Course Outline

Introduction to the Huawei Ascend Platform

  • Overview of the Ascend ecosystem and architecture
  • Insights into CANN and MindSpore
  • Industry relevance and use cases

Establishing the Development Environment

  • Installation of MindSpore and the CANN toolkit
  • Utilizing CloudMatrix and ModelArts for project orchestration
  • Validating the environment using sample models

Developing Models with MindSpore

  • Training and model definition in MindSpore
  • Data pipeline management and dataset formatting
  • Exporting models for Ascend compatibility

Performance Optimization on Ascend

  • AI Core scheduling and tiling strategies
  • Custom kernels and operator fusion
  • Profiling and benchmarking tools

Deployment Strategies

  • Trade-offs between edge and cloud deployment
  • Employing the MindX SDK for deployment
  • Integration with CloudMatrix workflows

Debugging and Monitoring

  • Utilizing AiD and Profiler for tracing
  • Resolving runtime failures
  • Tracking throughput and resource usage

Lab Integration and Case Study

  • Comprehensive pipeline development using MindSpore
  • Lab: Design, optimize, and deploy a model on Ascend
  • Performance comparison with alternative platforms

Summary and Next Steps

Requirements

  • Knowledge of AI workflows and neural networks
  • Proficiency in Python programming
  • Experience with deployment pipelines and model training

Target Audience

  • AI engineers
  • Data scientists working with the Huawei AI stack
  • ML developers utilizing MindSpore and Ascend
 21 Hours

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  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
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Price per private group, online live training, starting from 4800 € + VAT*

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