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    <p>Ok, so there are few things related to a kernel, one is number of multiprocessors (associated with blocks) and number of cores (associated with cores), blocks are scheduled to run on a multiprocessor (which is 8 for you), threads are scheduled to run on multiple cores on a single multiprocessor. Ideally you would like to have enough number of blocks and threads so that all you multi-processors and all cores in each multi-processor are occupied. It is advisable to have larger number of blocks and threads when compared to multi-processors and cores as coalescing of threads/blocks can be done. </p> <p>multiple dimensions make programming easier (for eg: 2D/3D images, you could divide the image into sub-parts and give it to different blocks and then process those sub-images on multiple threads), it is more intuitive to use multiple dimensions (x, y, z) for accessing blocks and threads. In some cases, it helps you to have more dimensions if there is a restriction in maximum number of blocks in one dimension (for example if you had a large image, you may hit a limit on maximum number of blocks if you just use one dimension).</p> <p>I am not sure if I understand what you mean in your third question, I can tell a bit about shared memory. Shared memory is present on a single multi-processor, it is shared by cores on the processor. For you, the amount of shared memory is 16KB, most modern GPUs have 64KB of shared memory on a processor and you can chose how much you want to have for your application, 16KB in the 64KB is generally reserved for cache and you can use the remaining 48KB for you or increase the cache size and lower your shared memory size. Shared memory is much faster than global memory, so incase you have some data which will be accessed frequently, it would be wise to transfer it to shared memory. The number of threads is not at all related to shared memory. Also, global memory and shared memory are separate.</p> <p>If you can see, each block dimension is less than 512, you cannot have more than 512 threads per block (limit has been changed to 1024 in newer CUDA versions on better architectures). Till Fermi each processor had 32 or 48 cores so it didn't make much sense to have more than 512 threads. The new Kepler architecture has 192 cores per multi-processor.</p> <p>Threads are executed in a warp, which is generally 16 threads clubbed together and executed on the cores in a multi-processor simultaneously. If you assume that there is always a miss in the shared memory, depending on the number of cores you have per multiprocessor and the memory clock rate, you can calculate how may threads would be processed each second (you would need to take into account the number of instructions which are processed per thread also, there would also be some time involved for processing operations on registers etc).</p> <p>I hope that answers your questions to some extent.</p>
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