Transpose操作是在两个share memory buffer上进行的,虽然说仍然存在bank conflict的问题,但是代价相较global memory的uncoalesced access来说还是低得多的。 (Also see : An Efficient Matrix Transpose in CUDA C/C++ | NVIDIA Technical Blog ) Shared memory是分成若干个bank的, 上善若水:「CUDA ON ARM」如何...
In many cases all of the inputs are available at the start of the RNN computation. This means that the matrix operations working on these inputs can be started immediately. It also means that they can be combined into larger GEMMs. While at first this may seem like a good thing (there...
There are many ways to address this problem, but two methods relied on in this MLPerf round were ensuring the use of well-optimized, low-overhead CPU-side code, as well as enabling the CUDA 10 feature called CUDA Graphs. Graphs enable the construction of a dependency graph of GPU work on...