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