array VS PDP_11_Simulator

I wrote a library in C++ (I know, probably a non-starter for most reading this) that I think does most of what you want, as well as some other requests in this thread (generalized to more than just multiply-add): https://github.com/dsharlet/array?tab=readme-ov-file#einstei....

A matrix multiply written with this looks like this:

    enum { i = 2, j = 0, k = 1 };

I should have mentioned somewhere, I disabled threading for OpenBLAS, so it is comparing one thread to one thread. Parallelism would be easy to add, but I tend to want the thread parallelism outside code like this anyways.

As for the inner loop not being well optimized... the disassembly looks like the same basic thing as OpenBLAS. There's disassembly in the comments of that file to show what code it generates, I'd love to know what you think is lacking! The only difference between the one I linked and this is prefetching and outer loop ordering: https://github.com/dsharlet/array/blob/master/examples/linea...

If you are looking for something like this in C++, here's my attempt at implementing it: https://github.com/dsharlet/array#einstein-reductions

It doesn't do any automatic optimization of the loops like some of the projects linked in this thread, but, it provides all the tools needed for humans to express the code in a way that a good compiler can turn it into really good code.

I can offer you the contrary opinion: why I would not use these kind of languages.

A couple of years ago I worked on a non-trivial APL application with one of my university professors and another student. We were trying to build a CPU simulator flexible enough to handle stuff ranging from PDP-11 up to Intel x86. The goal was to run some analysis on memory accesses performed by the x86 architecture. Quite an interesting project in which I worked on for around two year.

The code is still available if you're interested: https://github.com/emlautarom1/PDP_11_Simulator

The first implementation was done in APL using a book which I don't remember as reference. We had a couple of meetings where we learned APL and the general idea behind the design. Pretty soon we started to deal with a lot of issues like:

- We only found two implementations for the APL interpreter: GNU and Dyalog. GNU is free but pretty much abandoned. Support for Windows was (is?) nonexistent. Dyalogs version is proprietary so we couldn't use that (even when a "student" version was available).