Beyond multi-core parallelism: faster Mandelbrot with SIMD
Briefly

"Unfortunately, since I will only be selling freshly calculated and warm-from-the-CPU Mandelbrots, I can't rely on caching." This highlights the fundamental challenge of the business model, as caching is not an option for maximizing performance and costs.
"If we can figure out how to speed up calculations on a single core, this will contribute to both our goals." Optimizing single-core performance is crucial in achieving both faster results and reduced cloud computing costs.
"Trivially add on multi-core parallelism, using Rust's Rayon library." This demonstrates the ease of scaling performance by utilizing existing libraries, enhancing efficiency through multi-threaded processing.
"The faster I can return fractals, the happier my customers will be." This captures the essence of the service’s value proposition, emphasizing the direct link between speed and customer satisfaction.
Read at PythonSpeed
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