Thus, it is important to reduce branch divergence to improve the efficiency of GPU programs. On the other hand, branch divergence may be increased by some ...
Thus, it is important to reduce branch divergence to improve the efficiency of GPU programs. On the other hand, branch divergence may be increased by some ...
The experimental results show that it can improve the efficiency about 40% in the best case in comparison with traditional techniques. Keywords: GPU, branch ...
Thus, it is important to reduce branch divergence to improve the efficiency of GPU programs. On the other hand, branch divergence may be increased by some ...
Fingerprint. Dive into the research topics of 'Scalar Replacement Considering Branch Divergence'. Together they form a unique fingerprint.
GPU with the Single Instruction Multiple Data (SIMD) execution model enables a program to work efficiently. However, the efficiency may decrease because of ...
Scalar Replacement Considering Branch Divergence. Resource URI: https://dblp.l3s.de/d2r/resource/publications/journals/jip/FukuharaT22. Home | Example ...
Jul 30, 2023 · I'd say divergence happens on a predicated branch if not all threads in a warp go the same way (branch taken or not taken). Simple predication isn't suitable ...
We propose two novel software-based optimizations, called iteration delaying and branch distribution that aim to reduce branch divergence.
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We propose a demand-driven scalar replacement (DDSR) that is essentially an extension of partial redun- dancy elimination (PRE), which is an optimization ...