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https://github.com/monte-language/typhon

A virtual machine for Monte.
https://github.com/monte-language/typhon

compiler ocap python vm

Last synced: 4 months ago
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A virtual machine for Monte.

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README 

          
======

Typhon

======



Typhon is a virtual machine for Monte. It loads and executes Kernel-Monte from

Monte AST files.



Don't panic! We are in ``#monte`` on Libera.



How To Monte

============



You will need Nix, either by dint of being on NixOS or by installing

single-user Nix.



Once you have Nix, you can build a basic toolchain by building the ``monte``

target::



    $ nix-build -A monte



Note: Translation is not cheap. It will require approximately 0.5GiB memory

and 5min CPU time on a 64-bit x86 system to translate a non-JIT Typhon

executable, or 1GiB memory and 15min CPU time with the JIT enabled. It will

take another few minutes to build all of the Monte support libraries.



For only a bit more extra CPU time, one can build a toolchain which includes

Capn Proto support::



    $ nix-build -A fullMonte



The pure-Monte portions of the build are incremental, so after building

``monte``, the build of ``fullMonte`` should be relatively quick.



For development, it can be useful to build only the VM::



    $ nix-build -A typhonVm



And to run the VM untranslated, use a Nix shell::



    $ nix-shell default.nix -A typhonVm

    [nix-shell:~/typhon]$ pypy main.py ...



Contributing

============



Contributions are welcome. Please ensure that you're okay with the license!



Diffing Typhon Binaries

-----------------------



By default, git won't show diffs of binary files. I don't especially blame it.

However, with a bit of a filter, we can give git what it needs::



    $ nix-env -iA monte -f default.nix

    $ git config --replace-all diff.typhon.textconv 'monte dump-mast'



This configuration option, along with the ``.gitattributes`` in the

repository, will let git display textual diffs of the binary ASTs.



RPython Quirks

--------------



Here's what you need to know about RPython and things imported from

``rpython.rlib``.



Immutability

~~~~~~~~~~~~



Like Monte, RPython values immutable structures. Whenever a class is

immutable, adding the ``_immutable_ = True`` annotation will cause RPython to

enforce an immutability variant: The fields of an instance of that class can

only be assigned to once.



Don't use ``_immutable_`` unless the class is *totally* immutable. It's

possible to make only some fields immutable; just list all the immutable

fields in a tuple with ``_immutable_fields_ = "this", "that"``. To make a

field an immutable list with immutable elements, use a ``[*]``, as in

``_immutable_fields_ = "this", "that", "those[*]"``.



The JIT (``rpython.rlib.jit``)

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~



``r.r.jit`` is mostly about hints to inform the JIT about the behavior of code

paths. Some hints are safe and some are not safe.



The JIT colors all values as "red" or "green"; a red value is non-constant and

a green value is constant. ``promote`` accepts a red value and turns it into a

green value. The JIT will reflect this with a guard on the value of the given

object. When a value is expected to have a relatively small number of

possibilities, a ``promote`` can be very effective at improving the

performance of the code. ``promote`` is safe; it will never cause the JIT to

generate wrong code, although it can cause the JIT to perform too much

compilation.



``jit_debug()`` can print one string and up to four integers to the JIT log.

The computation which prepares the debug message is part of the JIT trace, so

it is ideal to have the inputs be green values.



``elidable`` functions must be referentially transparent. In return, the JIT

accepts the promise of referential transparency and will try to reorder or

remove the call to the ``elidable`` function when it can. The function need

not actually be pure; it is sufficient for it to appear pure in all cases. If

the function is not pure, then ``elidable`` is unsafe, since the JIT will not

second-guess a promise of elidability.



.. note::

    Do *not* mark ``elidable`` if you want the JIT to inline the function. The

    JIT will not enter an ``elidable`` function.



``elidable_promote`` changes a function so that it is ``elidable`` and all of

its arguments will be ``promote``'d before entering the function body. It is

unsafe, like ``elidable``.



``dont_look_inside`` forces the JIT to not inline calls to a function. It is

sometimes necessary to protect events like GIL handling or I/O. It can also be

a big improvement for calls to functions which don't inline well due to

recursive or other strange behavior. It should be safe.



``unroll_safe`` forces the JIT to consider inlining calls to functions which

were not inlinable due to containing loops. This is important because the JIT

will otherwise refuse to look inside those functions. Usage of ``unroll_safe``

is an informal promise to the JIT that the loops in the function are tightly

bounded in the number of iterations which will be performed. While not unsafe,

``unroll_safe`` can cause exponential amounts of overcompilation and

overtracing, so it should be used sparingly.



How are these used within the codebase? Values that are expected to be green

but aren't green-inferred by the JIT are ``promote``'d. Functions that do I/O

have ``dont_look_inside``. Functions which are pure and called often are

``elidable``. Lots of factoring has been done to make small chunks of code

``elidable``.



If a function has a loop that is conditionally called, it is useful to factor

the loop to a separate function and then consider whether to mark the new

function with ``unroll_safe``. Even if the function isn't actually safe to

unroll, merely the factorization of code is sufficient to allow the JIT to

look into the original function. This happens with every object which is

defined in RPython; the dispatch function, ``callAtom()`` or similar, is

factored to not have loops within it. Since atoms are (usually) green values

during execution, this means that ``callAtom()`` gets specialized for that

atom, and the actual work can usually be inlined.



Unicode (``rpython.rlib.unicodedata``)

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~



We use RPython's Unicode database. The magic incantation::



    from rpython.rlib.unicodedata import unicodedb_6_2_0 as unicodedb



``unicodedb`` will have plenty of useful functions, like ``islower()`` and

``isalpha()``. These functions are *not* available as methods on ``unicode``

objects.



.. _reference Monte: https://github.com/monte-language/monte



Documentation

-------------



If you create a new object by subclassing ``Object`` or calling ``@runnable``,

please give it a docstring. The docstrings will be reflected into Monte, so

please follow these guidelines:



* The first line should describe the object.

* Subsequent lines should describe specifics of the object's nature which

  might be helpful to somebody calling ``help()`` on the object.

* Docstrings should refer to their object as "this object".

* In-jokes are sometimes allowed. Ask on IRC.

* Dry language is always allowed.

* Unicode is encouraged; do not be afraid to use symbols which are generally

  available in Unicode fonts. Ask on IRC if unsure.



An example:



    ▲> help(Any)

    Result: Object type: AnyGuard

    A guard which admits the universal set.

    This object specializes to a guard which admits the union of its

    subguards: Any[X, Y, Z] =~ X ∪ Y ∪ Z



Also document objects and methods written in Monte. For methods:



* "this method" is the correct self-reference.

* To refer to names defined in the method specification, surround the name in

  backticks.

* To refer to methods, use atom syntax and backticks: A method with name

  "meth" and arity 2 would appear as \`meth/2\`.



Autohelp would like to remind you that subclasses of ``Object`` should

decorate themselves with ``@autohelp`` in order to maintain compliance and

safety.



To override pretty-printing for an object, add a ``toString()`` method which

should return a Unicode string.