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Last Updated: Aug 11, 2026
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| Section | Weight | Objectives |
|---|---|---|
| Error Handling and Best Practices | 10% | - Code portability and maintainability - CUDA error checking |
| CUDA Programming Model | 25% | - Kernel launch syntax and execution flow - Heterogeneous computing architecture - Grid, block, thread hierarchy and SIMT execution |
| Memory Management | 30% | - Memory allocation and data transfer - Global, shared, constant, texture, local memory - Memory coalescing and access optimization |
| Performance Optimization | 15% | - Kernel optimization techniques - Profiling tools and bottleneck identification - Concurrency and stream usage |
| CUDA Hardware and Architecture | 20% | - Compute capability and feature support - Streaming Multiprocessors (SM) and warp scheduling |
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