GPU上的分支预测 [英] Branch predication on GPU

问题描述

我有一个关于GPU中分支预测的问题。据我所知，在GPU中，他们做分支的预测。

I have a question about branch predication in GPUs. As far as I know, in GPUs, they do predication with branches.

例如，我有一个这样的代码：

For example I have a code like this:

if (C)
 A
else
 B

40个周期，B需要50个周期来完成执行，如果假设一个翘曲，A和B都被执行，那么总共需要90个周期来完成这个分支吗？或者它们与A和B重叠，即，当A的一些指令被执行时，然后等待存储器请求，然后执行B的一些指令，然后等待存储器，等等？
感谢

so if A takes 40 cycles and B takes 50 cycles to finish execution, if assuming for one warp, both A and B are executed, so does it take in total 90 cycles to finish this branch? Or do they overlap A and B, i.e., when some instructions of A are executed, then wait for memory request, then some instructions of B are executed, then wait for memory, and so on? Thanks

推荐答案

迄今为止发布的所有支持CUDA的架构都像SIMD机器。当在warp内存在分支发散时，两个代码路径由warp中的所有线程执行，而不跟在活动路径之后的线程执行NOP的功能等同（我想我记得有条件执行

All of the CUDA capable architectures released so far operate like an SIMD machine. When there is branch divergence within a warp, both code paths are executed by all the threads in the warp, with the threads which are not following the active path executing the functional equivalent of a NOP (I think I recall that there is a conditional execution flag attached to each thread in a warp which allows non executing threads to be masked off).

所以在你的例子中，90个周期的答案可能是一个更好的近似的真的发生比替代。

So in your example, the 90 cycles answer is probably a better approximation of what really happens than the alternative.

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