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Finally, with a complete ray tracing example, I walk you through the steps of using the Numba extension for PyOptiX and write an accelerated ray tracing kernel in Python. In this post, I provide an overview of the NVIDIA ray-tracing engine PyOptiX and explain how the Python JIT compiler, Numba, accelerates Python code. This extension enables graphics researchers and application developers to reduce the time from idea to implementation and shorten the development cycle on each iteration. To alleviate the difficulty and provide a familiar environment for writing ray tracing kernels, NVIDIA developed the Numba extension for PyOptiX.
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Often, the build process of these software toolchains poses significant challenges to Python developers. To leverage the hardware power for ray tracing, various toolchains and languages were invented to suit the need, such as openGL and the shading language. However, the ray-tracing algorithm is computationally intensive and requires hardware acceleration on the GPU to achieve real-time performance.
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Today, it is widely adopted to bring imagery to life in game development, film-making, and physics simulations. Ray tracing is a rendering algorithm that can generate photorealistic images by simulating how light transmits and interacts with different materials.