CUDA ---- Branch Divergence and Unrolling Loop
Avoiding Branch Divergence 有時，控制流依賴於thread索引。同一個warp中，一個條件分支可能導致很差的性能。通過重新組織數據獲取模式可以減少或避免warp divergence（該問題的解釋請查看warp解析篇）。 The Parallel Reduction Problem 我們現在要計算一個數組N個元素的和。這個過程用CPU編程很容易實現： int sum =
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相關文章
- 1. [Git] Remote Branch and Tag
- 2. CUDA系列學習（二）CUDA memory variables - different memory and va
- 3. CUDA ---- Stream and Event
- 4. Ch02: Game Class and Loop
- 5. Your branch and 'XXX' have diverged
- 6. Your branch and 'origin/master' have diverged
- 7. Your branch and 'origin/master' have diverged,
- 8. Git Tutorial 5 - Branch and Merge - Local
- 9. Kullback-Leibler Divergence Explained
- 10. Phi-divergence