Novetta has hosted annual internal hackathons where employees create prototypes focused on technologies relevant to our customers. In our most recent hackathon, I utilized NVIDIA’s CuPy library for GPU-accelerated fractal generation and searching. I used a feature of CuPy that allows you to write raw CUDA C++ code in a Python project without needing to create a C++ project or interact directly with a C++ compiler. This gives users access to much of the power of CUDA C++ without needing to be experts in CUDA or C++. Fractals serve as a good example of a custom computation that can be GPU-accelerated with CuPy with minimal C++ experience.

In this report I will discuss how to generate fractals with CuPy and compare it to the more traditional CPU-based approach, demonstrate interactive fractal-searching, and (most importantly) generate an appealing wallpaper for your desktop.

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