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NVIDIA NVD-001 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| CUDA Hardware and Architecture | 20% | - Streaming Multiprocessors (SM) and warp scheduling - Compute capability and feature support |
| CUDA Programming Model | 25% | - Kernel launch syntax and execution flow - Heterogeneous computing architecture - Grid, block, thread hierarchy and SIMT execution |
| Error Handling and Best Practices | 10% | - CUDA error checking - Code portability and maintainability |
| Memory Management | 30% | - Memory coalescing and access optimization - Global, shared, constant, texture, local memory - Memory allocation and data transfer |
| Performance Optimization | 15% | - Concurrency and stream usage - Profiling tools and bottleneck identification - Kernel optimization techniques |




