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Huawei H13-324_V1.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| CANN-ATC Model Conversion | 12% | - ATC tool functions and parameters - CANN platform overview - Conversion from mainstream frameworks to Ascend OM model - Troubleshooting conversion errors |
| Ascend AI Processor | 8% | - Architecture and features of Ascend AI processor - Memory and storage system - Core components and computing units |
| CANN Inference Performance Tuning | 5% | - Memory and computing optimization - Common tuning strategies - Performance analysis tools |
| MindSpore Full-Process Development | 15% | - Model building, training and validation - MindSpore framework architecture - Model saving, exporting and deployment |
| CANN Inference Application Development | 15% | - Multi-thread and multi-device inference - Data preprocessing and postprocessing - AscendCL API and development flow |
| CANN Custom Operator Development | 7% | - Operator development specification - Operator implementation and compilation - Operator verification and integration |
| Atlas AI Computing Solutions | 13% | - System software and toolchain overview - Application scenarios and deployment modes - Atlas series hardware products |
| Neural Network Fundamentals | 25% | - Model compression and quantization basics - Model training and optimization methods - Common neural network structures - Basic deep learning theory |
