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GPU Programming with C++ and CUDA
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So far, we've learned why parallelism matters, considered the various GPU device components, and compared GPUs with CPUs. Now it's time to understand how GPUs can enhance the performance of our solutions and how to overcome the challenges that come with these benefits.Since we've already talked about some of the benefits, let's start with the challenges that come with GPU programming.
The most obvious challenge is that we can't change the device’s components, so we can't upgrade its memory, for example. Hardware limitations will directly restrict what we can do and how we'll need to break down our data for processing.We also talked about memory transfers, something that can easily become an overhead if we have to move data to and from the device constantly. Typically, we try to move data to the device and compute as much as possible before having...