In our very first chapter, we emphasized that computing is application-specific and is a technique to calculate any measurable entity across multi-disciplinary fields. These calculations are meant to solve actual computational problems in a real-world scenario, which is why our focus is on computational problem solving, catering to the prime objective of computing.
Computing: The answer to every computational problem lies in its computed solution.
Accelerated computing: A computationally intensive problem requires an accelerated solution.
Let's understand how PyCUDA can help us solve a myriad of computational problems based on GPU computations via Python, with or without CUDA-C/C++ code.
Following our first C++ versus CUDA example, we will now look into a very simple Python versus PyCUDA example with a similar approach, hands-on with...
