November 2018
Intermediate to advanced
310 pages
7h 54m
English
Content preview from Hands-On GPU Programming with Python and CUDA
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Questions
- Change the random vector in simple_scalar_multiply_kernel.py so that it is of a length of 10,000, and modify the i index in the definition of the kernel so that it can be used over multiple blocks in the form of a grid. See if you can now launch this kernel over 10,000 threads by setting block and grid parameters to something like block=(100,1,1) and grid=(100,1,1).
- In the previous question, we launched a kernel that makes use of 10,000 threads simultaneously; as of 2018, there is no NVIDIA GPU with more than 5,000 cores. Why does this still work and give the expected results?
- The naive parallel prefix algorithm has time complexity O(log n) given that we have n or more processors for a dataset of size n. Suppose that we use a ...
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