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That’s funny. I remember the wake up after doing all the complexity analysis and such of academia, that once you’re engineering for performance, it’s often very
by klabb3 3y ago
That’s funny. I remember the wake up after doing all the complexity analysis and such of academia, that once you’re engineering for performance, it’s often very different from theory. For instance, a lot of heap-allocations and the resulting memory fragmentation can really tank performance on real hardware. Naive linked lists for instance, is a good example of something that looks super useful in CS class, but turns out is quite niche in practice, and also quite differently implemented.
- taeric 3y agoTo be fair, it is largely the Big O analysis that is very different. And that is easily understood as a case of Goodhart's Law. It remains a good way of comparing the growth of algorithms, of course; but a full analysis would include more than only the top end growth numbers.