CUDA: Avoid conditional statement in kernel

 

http://stackoverflow.com/a/1645126/2041023

From section 6.1 of the CUDA Best Practices Guide:

Any flow control instruction (if, switch, do, for, while) can significantly affect the instruction throughput by causing threads of the same warp to diverge; that is, to follow different execution paths. If this happens, the different execution paths must be serialized, increasing the total number of instructions executed for this warp. When all the different execution paths have completed, the threads converge back to the same execution path.

http://stackoverflow.com/a/13397496/2041023

The thread warp is a hardware group of threads that execute on the same Streaming Multiprocessor (SM). Threads of a warp can be compared to sharing a common program counter between the threads, hence all threads must execute the same line of program code. If the code has some brancing statements such as if ... then ... else the warp must first execute the threads that enter the first block, while the other threads of the warp wait, next the threads that enter the next block will execute while the other threads wait and so on. Because of this behaviour conditional statements should be avoided in GPU code if possible. When threads of a warp follow different lines of execution it is known as having divergent threads. While conditional blocks should be kept to a minimum inside CUDA kernels, it is sometimes possible to reorder statements so that all threads of the same warp follow only a single path of execution in an if ... then ... else block and mitigate this limitation.

The while and for statements are branching statements, so it is not limited to if.