How does a stackless language work?

The modern operating systems we have (Windows, Linux) operate with what I call the “big stack model”. And that model is wrong, sometimes, and motivates the need for “stackless” languages.

The “big stack model” assumes that a compiled program will allocate “stack frames” for function calls in a contiguous region of memory, using machine instructions to adjust registers containing the stack pointer (and optional stack frame pointer) very rapidly. This leads to fast function call/return, at the price of having a large, contiguous region for the stack. Because 99.99% of all programs run under these modern OSes work well with the big stack model, the compilers, loaders, and even the OS “know” about this stack area.

One common problem all such applications have is, “how big should my stack be?”. With memory being dirt cheap, mostly what happens is that a large chunk is set aside for the stack (MS defaults to 1Mb), and typical application call structure never gets anywhere near to using it up. But if an application does use it all up, it dies with an illegal memory reference (“I’m sorry Dave, I can’t do that”), by virtue of reaching off the end of its stack.

Most so-called called “stackless” languages aren’t really stackless. They just don’t use the contiguous stack provided by these systems. What they do instead is allocate a stack frame from the heap on each function call. The cost per function call goes up somewhat; if functions are typically complex, or the language is interpretive, this additional cost is insignificant. (One can also determine call DAGs in the program call graph and allocate a heap segment to cover the entire DAG; this way you get both heap allocation and the speed of classic big-stack function calls for all calls inside the call DAG).

There are several reasons for using heap allocation for stack frames:

  1. If the program does deep recursion dependent on the specific problem it is solving,
    it is very hard to preallocate a “big stack” area in advance because the needed size isn’t known. One can awkwardly arrange function calls to check to see if there’s enough stack left, and if not, reallocate a bigger chunk, copy the old stack and readjust all the pointers into the stack; that’s so awkward that I don’t know of any implementations.
    Allocating stack frames means the application never has to say its sorry until there’s
    literally no allocatable memory left.

  2. The program forks subtasks. Each subtask requires its own stack, and therefore can’t use the one “big stack” provided. So, one needs to allocate stacks for each subtask. If you have thousands of possible subtasks, you might now need thousands of “big stacks”, and the memory demand suddenly gets ridiculous. Allocating stack frames solves this problem. Often the subtask “stacks” refer back to the parent tasks to implement lexical scoping; as subtasks fork, a tree of “substacks” is created called a “cactus stack”.

  3. Your language has continuations. These require that the data in lexical scope visible to the current function somehow be preserved for later reuse. This can be implemented by copying parent stack frames, climbing up the cactus stack, and proceeding.

The PARLANSE programming language I implemented does 1) and 2). I’m working on 3). It is amusing to note that PARLANSE allocates stack frames from a very fast-access heap-per-thread; it costs typically 4 machine instructions. The current implementation is x86 based, and the allocated frame is placed in the x86 EBP/ESP register much like other conventional x86 based language implementations. So it does use the hardware “contiguous stack” (including pushing and poppping) just in chunks. It also generates “frame local” subroutine calls the don’t switch stacks for lots of generated utility code where the stack demand is known in advance.

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