为什么访问两个连续元素的线程会导致“银行冲突”？

https://developer.nvidia.com/blog/using-shared-memory-cuda-cc/

共享内存库冲突

To achieve high memory bandwidth for concurrent accesses, shared memory is divided into equally sized memory modules (banks) that can be accessed simultaneously. Therefore, any memory load or store of n addresses that spans b distinct memory banks can be serviced simultaneously, yielding an effective bandwidth that is b times as high as the bandwidth of a single bank.

However, if multiple threads’ requested addresses map to the same memory bank, the accesses are serialized. The hardware splits a conflicting memory request into as many separate conflict-free requests as necessary, decreasing the effective bandwidth by a factor equal to the number of colliding memory requests. An exception is the case where all threads in a warp address the same shared memory address, resulting in a broadcast. Devices of compute capability 2.0 and higher have the additional ability to multicast shared memory accesses, meaning that multiple accesses to the same location by any number of threads within a warp are served simultaneously.

Let's assume that there are 8 memory banks of size 4 bytes for your example of parallel reduction. Element i is served by bank i % 8.

然后，在第一个示例中，bank 0、2、4、6 需要处理两个请求。

在第二个例子中，每家银行只需要处理一个请求。