cuda #pragma

引用此外，CUDA编程中还可以利用其他的特殊变量和函数，如blockIdx、threadIdx和atomicAdd等，用于获取线程号和实现原子操作等功能。另外，可以使用共享内存进行数据传输和优化，例如在求矩阵转置时，可以利用共享内存进行交叉内存访问，从而提高访存效率。<em>1</em><em>2</em><em>3</em>
#### 引用[.reference_title]
- *1* [CUDA——性能优化之循环展开](https://blog.csdn.net/weixin_44444450/article/details/104469278)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT0_1"}} ] [.reference_item]
- *2* [CUDA学习之原子操作](https://blog.csdn.net/yangjinyi1314/article/details/125476118)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT0_1"}} ] [.reference_item]
- *3* [CUDA基本优化方法](https://blog.csdn.net/nn1997729/article/details/118181359)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT0_1"}} ] [.reference_item]
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