Question: Problem 3 : You experiment with a GPU to compute the following multiplication C = A x B , where m = n = l
Problem : You experiment with a GPU to compute the following multiplication CA x B where the elements of and are all with the same bitwidth of Bytes. When implementing on GPU, each thread is in charge of computing for one element in C Please answer the following questions please show detailed steps. pts
and
a From the hardware standpoint, the GPU has Streaming Multiprocessors SMs each with exclusive L and L caches, and warp schedulers managing warps per scheduler. Each warp consists of cores. From the software perspective, threads within the same block can share data directly, while threads across different blocks cannot. What is the maximum block size that matches the GPU hardware architecture? pts
b Following the result from a how many blocks should we have for computing the entire matrix C Please use dim we have learned to initialize the threading. pts dim block dim thread
c After applying tiling, with the tile size of houmany tiles can cover the entire matrix? Given the block size calculated in a how many titles can cover thejentire block?
d Following the block and tile sizes in c what is the proper size of shared memory that we need to request Hint: threads within the same block can share data directly, while threads across different blocks cannot Please explain your answer. pts
Just c & d
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