The recommended formula for converting an RGB color picture into a grayscale picture is to take 0.21 of the red pixel, 0.72 of the green pixel, and 0.07 of the blue pixel and add them up together. This creates the luminance value which is used for the grayscale picture.
CUDA is used to program NVIDIA GPUs for maximum flexibility and to make them go super fast. It has a reputation of being very hard to get started with, but with some tricks, it can be relatively easy to use.
An SM (Streaming Multiprocessor) is like a separate CPU in an NVIDIA GPU, and each SM has multiple CUDA cores. These CUDA cores are able to operate at the same time, allowing for parallel processing of data. For example, an RTX 3090 card has 82 SMs and 10,500 CUDA cores in total.
The number of threads in a CUDA kernel is determined by the number of pixels divided by 256, rounded up to the nearest integer.
The guard or guard block in a CUDA kernel is used to ensure that the index being accessed does not go past the number of pixels in the kernel.
Shared memory in a CUDA kernel is a small amount of fast memory that is shared among all the threads in a block. It is used to improve the performance of the kernel.
The full image that the CUDA device can process has 1.7 million pixels.
The time taken to process the full image using the CUDA device is one millisecond.
The purpose of including the step of moving the data off the GPU and onto the CPU as part of what is being timed is to force it to complete the CUDA run and to put the data back onto the CPU. This ensures that the amount of time shown is not dramatically less because it hasn't finished synchronizing.
You call torch check, pass in the thing to check, and pass in the message to pop up if there's a problem.
The dim3 structure in CUDA code is used to specify the number of threads per block and the number of blocks. It is a tuple with three elements, where the third element is treated as being one if not specified.
The advantage of using shared memory in CUDA code is that it is a small memory space that is shared amongst the threads in a block, and it is much faster than global memory. It can be used to cache information and reuse it, rather than going back to the slower memory again and again.