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submitted 2 years ago by [email protected] to c/[email protected]

Good explanation of the difference between work efficiency and step efficiency when talking about parallel algorithms.

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[-] [email protected] 0 points 2 years ago

Yes. In the end it is usually total wall time of the critical path that matters unless there are special considerations like power consumption or heat generation, etc.

Not the same thing, but CPUs are designed to optimize different things too. I know I have often had laptops that were faster for single threaded tasks, but my engineering workstation has typically had way higher throughput for a parallel work load. Say nothing about compute clusters. Lot of these things about single threaded and parallel fairly common.

There also tends to be fairly expensive setup and sync steps related to highly parallel stuff like MPI or GPUs, though sometimes less so in the case of say vectorization or threading.

Thanks, interesting.

[-] [email protected] 0 points 2 years ago

It is interesting, isn't it? This is why I love computing as a field; the whole "spectrum" from theory to practice is just super fascinating.

[-] [email protected] 1 points 2 years ago* (last edited 2 years ago)

Yes. Took my first computer class in 1978. Fortran of all things. Hooked immediately. Considered CS, but actually went the Science side of things doing a combination of design, simulation, instrument control, and machine control. Whatever was needed. Lot of changes in hardware, software, languages, etc. on one hand but on the other hand not so much. At some level it has all been the same.

this post was submitted on 28 Jun 2023
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