Piggybacking also to say that I hope you succeed, as your work aligns closely with the type of runtime that I had hoped to write someday when I first used MATLAB in the early 2000s (now mostly GNU Octave for small hobby projects).

The loop fusion idea sounds amazing. Another point of friction which I ran into is that MATLAB uses 1-based offsets instead of 0-based offsets for matrices/arrays, which can make porting code examples from other languages tricky. I wish there was a way to specify the offset base with something like a C #define or compiler directive. Or a way to rewrite code in-place to use the other base, a bit like running Go's gofmt to format code. Apologies if something like this exists and I'm just too out of the loop.

I'd like to point out one last thing, which is that working at the fringe outside of corporate sponsorship causes good ideas to take 10 or 20 years to mature. We all suffer poor tooling because the people that win the internet lottery pull up the ladder behind them.

> I wish there was a way to specify the offset base with something like a C #define or compiler directive.

Julia has OffsetArrays.jl implementing arbitrary-base indexing: https://juliaarrays.github.io/OffsetArrays.jl/stable/

The experience with this has been quite mixed, creating a new surface for bugs to appear. Used well, it can be very convenient for the reasons you state.

  julia> A = collect(1:5)
  5-element Vector{Int64}:
   1
   2
   3
   4
   5

  julia> B = OffsetArray(A, -1)
  5-element OffsetArray(::Vector{Int64}, 0:4) with eltype Int64 with indices 0:4:
   1
   2
   3
   4
   5

  julia> A[1]
  1

  julia> B[0]
  1