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Huawei H13-324_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: CANN - Custom Operator Development | 8% | - Development, compilation and deployment of custom operators - Operator performance analysis and tuning - Operator development framework and specifications |
| Topic 2: Atlas AI Computing Solution | 13% | - Atlas hardware product series and application scenarios - System composition and deployment modes - Software stack and development environment |
| Topic 3: MindSpore Full-Process Development | 20% | - Model saving, loading and deployment - Network construction, training and inference - MindSpore framework features and installation - Automatic differentiation and parallel computing |
| Topic 4: CANN - Inference Application Performance Tuning | 5% | - Performance indicators and analysis methods - Data transmission and computing efficiency improvement - System configuration and resource optimization |
| Topic 5: Neural Network Basics | 25% | - Mathematical foundation for AI development - Model training, optimization and evaluation - Common neural network structures and algorithms - Basic principles of deep learning |
| Topic 6: CANN - ATC Model Conversion | 8% | - ATC tool usage and parameter configuration - Model optimization and accuracy comparison - Conversion from mainstream frameworks to Ascend OM model - CANN architecture and functions |
| Topic 7: Comprehensive Experiment and Application Practice | 5% | - End-to-end AI application development based on Ascend - Deployment and testing of actual projects - Problem analysis and solution design |
| Topic 8: Ascend AI Processor | 8% | - Memory management and data flow - Hardware specifications and computing resources - Architecture and features of Ascend AI processor |
| Topic 9: CANN - Inference Application Development Process | 8% | - Data preprocessing and postprocessing - Multi-thread and batch processing design - Application development workflow - Inference engine and API introduction |
