| It's not that simple. Amdahl's Law is about expected speedup/decrease in latency. That actually isn't strongly correlated to "saving the planet" afaik (where I interpret that as reducing direct energy usage, as well as embodied energy usage by reducing the need to upgrade hardware). If anything, increasing speed and/or decreasing latency of the whole system often involves adding some form of parallelism, which brings extra overhead and requires extra hardware. Note that prefetching/speculative execution kind of counts here as well, since that is essentially doing potentially wasted work in parallel. In the past boosting the clock rate the CPU was also a thing until thermodynamics said no. OTOH, letting your CPU go to sleep faster should save energy, so repeated single-digit perf improvements via wasting less instructions does matter. But then again, that could lead to Jevons Paradox (the situation where increasing the efficiency encourages more wasteful than the increase in efficiency saves - Wirth's Law but generalized and older, basically). So I'd say there's too many interconnected dynamics at play to really simply state "optimization good" or "optimization useless". I'm erring on the side of "faster Python probably good". [0] https://en.wikipedia.org/wiki/Jevons_paradox |