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Đề cương khóa học
Introduction to Huawei Ascend Platform
- Overview of Ascend architecture and ecosystem
- MindSpore and CANN overview
- Use cases and industry relevance
Setting Up the Development Environment
- Installing the CANN toolkit and MindSpore
- Using ModelArts and CloudMatrix for project orchestration
- Testing the environment with sample models
Model Development with MindSpore
- Model definition and training in MindSpore
- Data pipelines and dataset formatting
- Exporting models to Ascend-compatible format
Performance Optimization on Ascend
- Operator fusion and custom kernels
- Tiling strategy and AI Core scheduling
- Benchmarking and profiling tools
Deployment Strategies
- Edge vs cloud deployment tradeoffs
- Using the MindX SDK for deployment
- Integration with CloudMatrix workflows
Debugging and Monitoring
- Using Profiler and AiD for tracing
- Debugging runtime failures
- Monitoring resource usage and throughput
Case Study and Lab Integration
- Full pipeline development using MindSpore
- Lab: Build, optimize, and deploy a model on Ascend
- Performance comparison with other platforms
Summary and Next Steps
Requirements
- An understanding of neural networks and AI workflows
- Experience with Python programming
- Familiarity with model training and deployment pipelines
Audience
- AI engineers
- Data scientists working with Huawei AI stack
- ML developers using Ascend and MindSpore
21 Hours
