The problem is that there are so many layers between someone's code and the bare metal that optimization often gets completely lost. The mentality is that comp

The problem is that there are so many layers between someone's code and the bare metal that optimization often gets completely lost. The mentality is that computing is cheap and developer time is expensive. Write an inefficient function that wastes several thousand compute cycles but saves an hour of developer time is given priority in most cases. This mentality works great when the function is only run a few million times (or much less) over its lifetime. But when it gets added to some popular library; distributed across millions of machines; and used thousands of times each hour on each machine; those wasted cycles can really add up. What percentage of worldwide compute (with its associated wasted electricity and heat) can be attributed to inefficient code? Spending a few hours optimizing some popular code might actually do more to help the environment that driving an EV for an entire year.