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EtCepeyd | 1 year ago
The latter course (a) was built on a mathematical formalism that had been developed at the university proper and not used anywhere else, (b) used PVM: <https://www.netlib.org/pvm3/>, <https://en.wikipedia.org/wiki/Parallel_Virtual_Machine>, for labs.
Since then, I've repeatedly felt that I've seriously benefited from my formal languages courses, while the same couldn't be said about my parallel programming studies. PVM is dead technology (I think it must have counted as "nearly dead" right when we were using it). And the only aspect I recall about the formal parallel stuff is that it resembles nothing that I've read or seen about distributed and/or concurrent programming ever since.
A funny old memory regarding PVM. (This was a time when we used landlines with 56 kbit/s modems and pppd to dial in to university servers.) I bought a cheap second computer just so I could actually "distribute" PVM over a "cluster". For connecting both machines, I used linux's PLIP implementation. I didn't have money for two ethernet cards. IIRC, PLIP allowed for 40 kbyte/s transfers! <https://en.wikipedia.org/wiki/Parallel_Line_Internet_Protoco...>
bigmutant|1 year ago
- Consistency models (can I really count on data being there? What do I have to do to make sure that stale reads/write conflicts don't occur?)
- Transactions (this has really fallen off, especially in larger companies outside of BI/Analytics)
- Causality (how can I handle write conflicts at the App Layer? Are there Data Structures ie CDTs that can help in certain cases?)
Even basic things like "use system time/monotonic clocks to measure elapsed time instead of wall-clock time" aren't well known, I've personally corrected dozens of CRs for this. Yes this can be built in to libs, AI agents etc but it never seems to actually be, and I see the same issues repeated over-and-over. So something is missing at the education layer