- Hands-On GPU Programming with Python and CUDA
- Dr. Brian Tuomanen
- 171字
- 2021-06-10 19:25:35
Questions
- There are three for statements in this chapter's Mandelbrot example; however, we can only parallelize over the first two. Why can't we parallelize over all of the for loops here?
- What is something that Amdahl's Law doesn't account for when we apply it to offloading a serial CPU algorithm to a GPU?
- Suppose that you gain exclusive access to three new top-secret GPUs that are the same in all respects, except for core counts—the first has 131,072 cores, the second has 262,144 cores, and the third has 524,288 cores. If you parallelize and offload the Mandelbrot example onto these GPUs (which generates a 512 x 512 pixel image), will there be a difference in computation time between the first and second GPU? How about between the second and third GPU?
- Can you think of any problems with designating certain algorithms or blocks of code as parallelizable in the context of Amdahl's Law?
- Why should we use profilers instead of just using Python's time function?
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