Actual post from Dec. 15 from one of the streams. This is a real topic. As far as promoting women and minorities even if their qualifications are not as good as the white male scientists, I am all for it. We need diversity at the lab and if that is what it takes, so be it. Quit your whining. Look around the lab, what do you see? White male geezers. How many African Americans do you see at the lab? Virtually none. LLNL is one of the MOST undiverse places you will see. Face it folks, LLNL is an institution of white male privilege and they don't want to give up their privileged positions. California, a state of majority Hispanics has the "crown jewel" LLNL nestled in the middle of it with very FEW Hispanics at all!
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Of course, many scientific codes involve computations such as modeling events in several dimensions or in the quantum domain, and suffer from unfavorable scaling in any case, so the algorithm in use may play a greater role in changing the scaling power law or exponent, it may not be that important to lower the prefactor.
Better operating systems, languages, and compilers and scheduling algorithms can help performance though, and this could be part of the answer.
In real code environments, code maintenance and refactoring can also be an issue, code can be bloated or intentionally obfuscated by developers, and of course in high performance computing there can be perverse incentives to utilize more resources rather than less, and so on. Code features also become bloated and obfuscated, as in Microsoft office and Windows, as a way of generating a technological moat, driving ever-greater computing needs for basic tasks.
Maybe AI coding tools will cut this Gordian knot and lead to more efficient and maintainable code, it could also erode some of the power of entrenched platforms and operating systems at the big tech companies, leading to a new wave of innovative and performant software.