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
- Try rewriting the Monte Carlo integration examples (in the __main__ function in monte_carlo_integrator.py) to use the CUDA instrinsic functions. How does the accuracy compare to before?
- We only used the uniform distribution in all of our cuRAND examples. Can you name one possible use or application of using the normal (Gaussian) random distribution in GPU programming?
- Suppose that we use two different seeds to generate a list of 100 pseudo-random numbers. Should we ever concatenate these into a list of 200 numbers?
- In the last example, try adding __host__ before __device__ in the definition of our operator() function in the multiply_functor struct. Now, see if you can directly implement a host-side dot-product function using this ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.