5 ms·
Parallelization makes a program get to its result faster sure but thats not the same as faster computing. It seems like it takes the same amount of computing ti
by dangerface 4y ago
Parallelization makes a program get to its result faster sure but thats not the same as faster computing. It seems like it takes the same amount of computing time just done in parallel, I think thats misleading.
> No matter the performance benefits — if you promise to make something run in a second instead of a year — if there is any chance of returning incorrect results, no one is going to use your method
This isn't particularly true depending on your definition of incorrect, often it doesn't need to be correct just close enough. As an example the fast inverse square root function in quake give results that are incorrect but close enough and is 10x faster than getting the correct result.
- phoe-krk 4y ago> Parallelization makes a program get to its result faster sure but thats not the same as faster computing. True. A better description would be something like "an auto-parallelizing compiler/runtime for Unix shell scripts" which accepts standard shell scripts and performs automatic parallelization wherever it can.
- deleted 4y ago[deleted]
- kazinator 4y agoIf something is parallelized that must not be, the result typically won't be something "close enough", which is the point in the article. Not correctness as in numerical accuracy, where we can establish tolerances. However, the irony here is that the specific target audience for this tool actually will cheerfully accept incorrect parallelization for a speedup. Evidence for this is the use of parallel make, which does nothing to assure correctness; correctness is up to the Makefile rules expressing the correct, complete dependency graph. It's a fairly common practice to unleash parallel make on Makefiles that were written by other people (e.g. authors of free software), where those authors provided not a shred of documented assurance that their Makefiles were designed and tested for parallel use.