3 ms·
This does read kind of odd. Reads as if the algorithms don't work anymore. Which... is at sharp odds for my understanding of why folks still use the basic lin
by taeric 4y ago
This does read kind of odd. Reads as if the algorithms don't work anymore. Which... is at sharp odds for my understanding of why folks still use the basic linear algebra subprograms.
If anything, my understanding is that too many of the newer languages and runtimes are made with the idea that they must have the full tooling in the language and runtime. As opposed to in the past, where many of these subprograms would be written to be called from whatever software was being written for the machines.
- tomrod 4y agoI can think of a few ways: - Hardware dies, logical or physical storage needs to be reloaded - Algorithm is challenged as incorrect, needs to be tested - Underlying hardware infrastructure adjusts to 64-bit hardware, and returns different values - Intel decides to muck with the sine function near 0 (https://news.ycombinator.com/item?id=8434128 https://news.ycombinator.com/item?id=8434128, https://www.cs.earlham.edu/~dusko/cs63/fdiv.html https://www.cs.earlham.edu/~dusko/cs63/fdiv.html, https://github.com/torvalds/linux/blob/v5.9/arch/x86/kernel/fpu/bugs.c https://github.com/torvalds/linux/blob/v5.9/arch/x86/kernel/...) and so on
- taeric 4y agoI don't want this to get distracted by chasing examples. If any of these are systemic, I'm curious. That said, my assertion was that evidence is the algorithms in question are still valid. Usually, they are still champions in speed. Certainly, folks have had to port and maintain the fortran compilers. Especially so to add targets. But the very stability of fortran, the language, is a big boon to those implementations not having bit rot. And while I know they could be reimplemented, in what language? And to what real advantage?