I wrote a ray tracer in Brainfuck
After noticing a CMake tutorial mention that ray-tracers had been written in CMake, I decided to write one in Brainfuck. I implemented fixed-point arithmetic (Q16.16), square root via long division, and a pseudo-random generator. The resulting 23MB program renders a 400x225 image at one pixel per minute, proving that a simple language doesn't guarantee a simple codebase.
The program was finally 23MB, which is larger than the image itself [which was about 0.9MB], which makes it a rather poor choice for a compression technique.
- throwaway99e2
Isn't this just a ray tracer in python/c that spits out brainfuck? By this logic gcc writes all my programs in assembly lol
- shoo
brainfuck is unpleasant to write directly - e.g. the language doesn't have variables, so you need to manually do the bookkeeping of which memory offset is storing what 'variable'. & if you need to refactor your program slightly, in a way that changes the memory layout, maybe you need to manually rework the absolute & relative offsets. So I can appreciate why the author didn't roll up their sleeves to directly write BF - that's neither a productive nor interesting exercise.
Interesting to see how the author decomposed the problem:
- C raytracer https://github.com/mTvare6/rayfuck/blob/master/ray.c
~~ LLM refactor of the C code ~~>
- SSA-style C raytracer code https://github.com/mTvare6/rayfuck/blob/master/ray_ssa.c
~~ c2dsl.py helper script (compiler) ~~>
- DSL raytracer https://github.com/mTvare6/rayfuck/blob/master/ray.dsl
~~ dsl2bf.py helper script (another compiler) ~~>
BF raytracer https://github.com/mTvare6/rayfuck/blob/master/ray.bf (~22 mb of unreadable nonsense)
The dsl2bf compiler has a bunch of examples of implementing slightly higher level abstractions atop BF primitives. E.g. "go" to move the pointer to a different offset, destructive & non-destructive copies, all the way up to things like division -- BF only natively offers unary addition/subtraction.
If we have a read of the code of the final compiler, dsl2bf.py, the abstractions used in that code are relatively simple: global variables, local variables, lists, dicts, for loops, function definitions & function […]