A very compact stack machine (Forth) bytecode
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README.md

NibbleForth - A very compact stack machine (Forth) bytecode

This is just an idea at this point. I don't have time to work on it further at this point. Posting my notes on GitHub for the record.

We'd been struggling with code size issues on one of our projects. We're using one microcontroller with 32KB of flash (program memory), only 15KB of which we have allocated to code size. So it was pretty tight, and gcc even with -Os wasn't producing very tight code.

So I started thinking about the smallest possible instruction set. I'm pretty familiar with Forth and stack-based virtual machines, so that's where my thoughts went. My basic ideas were:

Use variable-length instruction opcodes, and assign the most frequently-used opcodes the lowest numbers so they can be encoded in the smallest instructions. Kind of like UTF-8, or the base 128 varints used in Google protocol buffers -- but using nibbles instead of bytes.

Taken to the extreme, this is Huffman coding, which uses a variable number of bits to encode each symbol, with the most frequently-used symbols getting the shortest bit codes. However, I suspect Huffman decoding would be too slow for an embedded virtual machine.

My hunch was that the most common instructions are used way more than the majority, meaning that encoding the most common opcodes in 4 bits and the slightly less common ones in 8 bits would be a huge gain.

And my hunch was correct -- I analyzed a bunch of Forth programs that come with Gforth using nibbleforth.py, and exit is by far the most common in most programs, with jz and jmp often close behind, and then the others usually varied from program to program.

Perhaps even more importantly, is to use Forth-like token threading on top of this, so it's not just primitive opcodes that can be encoded small, but any user-defined word too. So instruction 0 might be "return", instruction 1 might be "jump-if-zero", instruction 2 might be "user-function-1", etc. And there's be a tiny VM interpreter that looked up these numbers in a table (of 16-bit pointers) to get their actual address.

And your compiler would do this frequency tokenization globally on each program, so for each program you compiled you'd get the best results for the instructions/words it used.

On top of that, you could combine common sequences of instructions into their own words (i.e., calls to a function). Pretty much like dictionary-based compression algorithms like LZW uses -- in fact, you might use the greedy LZW algorithm to find them.

C compilers do common subexpression elimination, but it's only ever done within a single function, and we could do it globally, making it much more powerful and compressive. You'd have to be careful and use a few heuristics so you didn't actually make it bigger by factoring too much, or factor so much it was too too slow.

Note that Forth programmers factor into tiny words in any case, so this may not gain as much for folks who already program in a heavily-factored style with tiny words/functions. Have you ever considered that when programmers factor things into functions, they're basically running a dictionary compression algorithm manually?

Also you could inline any Forth "words" that were only used once, as it wouldn't help code size to have them as separate words. C compilers do this, but only on a file-local basis.

In fact, that's a common pattern with C compilers -- they can only optimize local to a function, or at most, local to a file. The linker can remove unused functions, but it can't really do any further optimization.

In any case, it would be a fun project to work on at some stage. :-)

References