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A comment on Julia: Dynamism and Performance Reconciled by Design (2018). Parent comment

Re:Julia: Dynamism and Performance Reconciled by Design (2018) by oivey on Monday October 26, 2020 @05:46PM (#24901870)
I just tried it, and it took 13 seconds to load and plot some random numbers. It could be better but it’s an acceptable trade off for my usage. Not as good as Python in this regard, but much better than Matlab.
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Re:Julia: Dynamism and Performance Reconciled by Design (2018) by ChrisRackauckas on Monday October 26, 2020 @05:52PM (#24901922)
It's approximately halved in Julia v1.6 BTW. It's not perfect but continually getting better.
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Re:Julia: Dynamism and Performance Reconciled by Design (2018) by jjoonathan on Monday October 26, 2020 @05:49PM (#24901897)
Is 13 seconds a build cache hit or miss?
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Re:Julia: Dynamism and Performance Reconciled by Design (2018) by oivey on Monday October 26, 2020 @06:02PM (#24902029)
It’s a precompilation hit, but it requires some compilation every time. Thinking about Julia like you might think about incremental C++ builds isn’t exactly right. A somewhat useful analogy though is that Julia is kind of like C++ template code. This is why it is so flexible, but also why compilation isn’t very cacheable. This is also why it is tricky (but possible) to do ahead of time Julia builds.
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