- Memory allocations are automatically synchronized in CUDA.
- The lockstep property only holds in single blocks of size 32 or less. Here, the two blocks would properly diverge without any lockstep.
- The same thing would happen here. This 64-thread block would actually be split into two 32-thread warps.
- Nvprof can time individual kernel launches, GPU utilization, and stream usage; any host-side profiler would only see CUDA host functions being launched.
- Printf is generally easier to use for small-scale projects with relatively short, inline kernels. If you write a very involved CUDA kernel with thousands of lines, then probably you would want to use the IDE to step through and debug your kernel line by line.
- This tells CUDA which GPU we want to use.
- cudaDeviceSynchronize will ensure that interdependent kernel launches and mem copies...
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