There seems to be a trend toward using MORE computing power, if it saves on programmers. Continuous integration, fuzzing, other high volume automated testing techniques, all the various applications of machine learning.

If a programmer costs $200K/year, that salary could support about 300KW continuous power use at average US industrial electricity rates (about $0.07/KWh). So if you could spend (say) 20 KW to increase programmer productivity by (say) 10% you'd be coming out ahead.