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0 points20k28d ago0 comments

The C++ way to do it currently would be:

    std::array<std::array<T, N>, M> data;

Which is contiguous

    int data[M][N];

also works fine and is contiguous in C++

Edit:

For the stack at least. On the heap, you'd need to use a single std::vector<int> and do the indices manually, or use mdspan

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3 comments · 1 top-level

uecker28d ago· 2 in thread

I does not work fine in C++ when N and M are not compile-time constants, which is basically always the case in any interesting numerical algorithm. Also not in Rust.

It works fine in C though, or FORTRAN, or Ada, or ALGOL 60, ...

pjmlp27d ago

Which is why std::mdspan exists, and std::linalg.

NVidia has pivoted to design CUDA hardware with focus on C++ back in , and seems to be doing quite well for them.

CppCon 2017: "Designing (New) C++ Hardware”

https://www.youtube.com/watch?v=86seb-iZCnI

They were also the ones sponsoring the ISO work on mdspan, while HPC research labs are pushing for linalg on top.

I would rather be using Ada today, but that isn't how the world moves.

uecker27d ago

I see that they spend time making their hardware run general software, but I can't see anything specific in GPU hardware to std::mdspan.

I respect Ada but I would not want to use it. But I have a choice between C++ with hmdspan and C99's arrays, I choose C99 any time.

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