modelverse/kernel/modelverse_jit/jit.py

import modelverse_kernel.primitives as primitive_functions
import modelverse_jit.bytecode_ir as bytecode_ir
import modelverse_jit.bytecode_parser as bytecode_parser
import modelverse_jit.bytecode_to_tree as bytecode_to_tree
import modelverse_jit.tree_ir as tree_ir
import modelverse_jit.runtime as jit_runtime
import keyword

# Import JitCompilationFailedException because it used to be defined
# in this module.
JitCompilationFailedException = jit_runtime.JitCompilationFailedException

def map_and_simplify_generator(function, instruction):
    """Applies the given mapping function to every instruction in the tree
       that has the given instruction as root, and simplifies it on-the-fly.

       This is at least as powerful as first mapping and then simplifying, as
       maps and simplifications are interspersed.

       This function assumes that function creates a generator that returns by
       raising a primitive_functions.PrimitiveFinished."""

    # First handle the children by mapping on them and then simplifying them.
    new_children = []
    for inst in instruction.get_children():
        new_inst, = yield [("CALL_ARGS", [map_and_simplify_generator, (function, inst)])]
        new_children.append(new_inst)

    # Then apply the function to the top-level node.
    transformed, = yield [("CALL_ARGS", [function, (instruction.create(new_children),)])]
    # Finally, simplify the transformed top-level node.
    raise primitive_functions.PrimitiveFinished(transformed.simplify_node())

def expand_constant_read(instruction):
    """Tries to replace a read of a constant node by a literal."""
    if isinstance(instruction, tree_ir.ReadValueInstruction) and \
        isinstance(instruction.node_id, tree_ir.LiteralInstruction):
        val, = yield [("RV", [instruction.node_id.literal])]
        raise primitive_functions.PrimitiveFinished(tree_ir.LiteralInstruction(val))
    else:
        raise primitive_functions.PrimitiveFinished(instruction)

def optimize_tree_ir(instruction):
    """Optimizes an IR tree."""
    return map_and_simplify_generator(expand_constant_read, instruction)

def create_function(
        function_name, parameter_list, param_dict,
        body_param_dict, function_body):
    """Creates a function from the given function name, parameter list,
       variable-to-parameter name map, variable-to-local name map and
       function body."""
    # Write a prologue and prepend it to the generated function body.
    prologue_statements = []
    # Create a LOCALS_NODE_NAME node, and connect it to the user root.
    prologue_statements.append(
        tree_ir.create_new_local_node(
            jit_runtime.LOCALS_NODE_NAME,
            tree_ir.LoadIndexInstruction(
                tree_ir.LoadLocalInstruction(jit_runtime.KWARGS_PARAMETER_NAME),
                tree_ir.LiteralInstruction('user_root')),
            jit_runtime.LOCALS_EDGE_NAME))
    for (key, val) in param_dict.items():
        arg_ptr = tree_ir.create_new_local_node(
            body_param_dict[key],
            tree_ir.LoadLocalInstruction(jit_runtime.LOCALS_NODE_NAME))
        prologue_statements.append(arg_ptr)
        prologue_statements.append(
            tree_ir.CreateDictionaryEdgeInstruction(
                tree_ir.LoadLocalInstruction(body_param_dict[key]),
                tree_ir.LiteralInstruction('value'),
                tree_ir.LoadLocalInstruction(val)))

    constructed_body = tree_ir.create_block(
        *(prologue_statements + [function_body]))

    # Optimize the function's body.
    constructed_body, = yield [("CALL_ARGS", [optimize_tree_ir, (constructed_body,)])]

    # Shield temporaries from the GC.
    constructed_body = tree_ir.protect_temporaries_from_gc(
        constructed_body, tree_ir.LoadLocalInstruction(jit_runtime.LOCALS_NODE_NAME))

    # Wrap the IR in a function definition, give it a unique name.
    constructed_function = tree_ir.DefineFunctionInstruction(
        function_name,
        parameter_list + ['**' + jit_runtime.KWARGS_PARAMETER_NAME],
        constructed_body)

    raise primitive_functions.PrimitiveFinished(constructed_function)

def print_value(val):
    """A thin wrapper around 'print'."""
    print(val)

class ModelverseJit(object):
    """A high-level interface to the modelverse JIT compiler."""
    def __init__(self, max_instructions=None, compiled_function_lookup=None):
        self.todo_entry_points = set()
        self.no_jit_entry_points = set()
        self.jitted_parameters = {}
        self.jit_globals = {
            'PrimitiveFinished' : primitive_functions.PrimitiveFinished,
            jit_runtime.CALL_FUNCTION_NAME : jit_runtime.call_function,
            jit_runtime.GET_INPUT_FUNCTION_NAME : jit_runtime.get_input
        }
        # jitted_entry_points maps body ids to values in jit_globals.
        self.jitted_entry_points = {}
        # global_functions maps global value names to body ids.
        self.global_functions = {}
        # global_functions_inv maps body ids to global value names.
        self.global_functions_inv = {}
        # bytecode_graphs maps body ids to their parsed bytecode graphs.
        self.bytecode_graphs = {}
        self.jit_count = 0
        self.max_instructions = max_instructions
        self.compiled_function_lookup = compiled_function_lookup
        # jit_intrinsics is a function name -> intrinsic map.
        self.jit_intrinsics = {}
        self.compilation_dependencies = {}
        self.jit_enabled = True
        self.direct_calls_allowed = True
        self.tracing_enabled = False
        self.input_function_enabled = False
        self.nop_insertion_enabled = True
        self.jit_success_log_function = None
        self.jit_code_log_function = None

    def set_jit_enabled(self, is_enabled=True):
        """Enables or disables the JIT."""
        self.jit_enabled = is_enabled

    def allow_direct_calls(self, is_allowed=True):
        """Allows or disallows direct calls from jitted to jitted code."""
        self.direct_calls_allowed = is_allowed

    def use_input_function(self, is_enabled=True):
        """Configures the JIT to compile 'input' instructions as function calls."""
        self.input_function_enabled = is_enabled

    def enable_tracing(self, is_enabled=True):
        """Enables or disables tracing for jitted code."""
        self.tracing_enabled = is_enabled

    def enable_nop_insertion(self, is_enabled=True):
        """Enables or disables nop insertion for jitted code. The JIT will insert nops at loop
           back-edges. Inserting nops sacrifices performance to keep the jitted code from
           blocking the thread of execution by consuming all resources; nops give the
           Modelverse server an opportunity to interrupt the currently running code."""
        self.nop_insertion_enabled = is_enabled

    def set_jit_success_log(self, log_function=print_value):
        """Configures this JIT instance with a function that prints output to a log.
           Success and failure messages for specific functions are then sent to said log."""
        self.jit_success_log_function = log_function

    def set_jit_code_log(self, log_function=print_value):
        """Configures this JIT instance with a function that prints output to a log.
           Function definitions of jitted functions are then sent to said log."""
        self.jit_code_log_function = log_function

    def mark_entry_point(self, body_id):
        """Marks the node with the given identifier as a function entry point."""
        if body_id not in self.no_jit_entry_points and body_id not in self.jitted_entry_points:
            self.todo_entry_points.add(body_id)

    def is_entry_point(self, body_id):
        """Tells if the node with the given identifier is a function entry point."""
        return body_id in self.todo_entry_points or \
               body_id in self.no_jit_entry_points or \
               body_id in self.jitted_entry_points

    def is_jittable_entry_point(self, body_id):
        """Tells if the node with the given identifier is a function entry point that
           has not been marked as non-jittable. This only returns `True` if the JIT
           is enabled and the function entry point has been marked jittable, or if
           the function has already been compiled."""
        return ((self.jit_enabled and body_id in self.todo_entry_points) or
                self.has_compiled(body_id))

    def has_compiled(self, body_id):
        """Tests if the function belonging to the given body node has been compiled yet."""
        return body_id in self.jitted_entry_points

    def get_compiled_name(self, body_id):
        """Gets the name of the compiled version of the given body node in the JIT
           global state."""
        return self.jitted_entry_points[body_id]

    def mark_no_jit(self, body_id):
        """Informs the JIT that the node with the given identifier is a function entry
           point that must never be jitted."""
        self.no_jit_entry_points.add(body_id)
        if body_id in self.todo_entry_points:
            self.todo_entry_points.remove(body_id)

    def generate_name(self, infix, suggested_name=None):
        """Generates a new name or picks the suggested name if it is still
           available."""
        if suggested_name is not None \
            and suggested_name not in self.jit_globals \
            and not keyword.iskeyword(suggested_name):
            self.jit_count += 1
            return suggested_name
        else:
            function_name = 'jit_%s%d' % (infix, self.jit_count)
            self.jit_count += 1
            return function_name

    def generate_function_name(self, body_id, suggested_name=None):
        """Generates a new function name or picks the suggested name if it is still
           available."""
        if suggested_name is None:
            suggested_name = self.get_global_name(body_id)

        return self.generate_name('func', suggested_name)

    def register_global(self, body_id, global_name):
        """Associates the given body id with the given global name."""
        self.global_functions[global_name] = body_id
        self.global_functions_inv[body_id] = global_name

    def get_global_name(self, body_id):
        """Gets the name of the global function with the given body id.
           Returns None if no known global exists with the given id."""
        if body_id in self.global_functions_inv:
            return self.global_functions_inv[body_id]
        else:
            return None

    def get_global_body_id(self, global_name):
        """Gets the body id of the global function with the given name.
           Returns None if no known global exists with the given name."""
        if global_name in self.global_functions:
            return self.global_functions[global_name]
        else:
            return None

    def register_compiled(self, body_id, compiled_function, function_name=None):
        """Registers a compiled entry point with the JIT."""
        # Get the function's name.
        actual_function_name = self.generate_function_name(body_id, function_name)
        # Map the body id to the given parameter list.
        self.jitted_entry_points[body_id] = actual_function_name
        self.jit_globals[actual_function_name] = compiled_function
        if function_name is not None:
            self.register_global(body_id, function_name)
        if body_id in self.todo_entry_points:
            self.todo_entry_points.remove(body_id)

    def import_value(self, value, suggested_name=None):
        """Imports the given value into the JIT's global scope, with the given suggested name.
           The actual name of the value (within the JIT's global scope) is returned."""
        actual_name = self.generate_name('import', suggested_name)
        self.jit_globals[actual_name] = value
        return actual_name

    def __lookup_compiled_body_impl(self, body_id):
        """Looks up a compiled function by body id. Returns a matching function,
           or None if no function was found."""
        if body_id is not None and body_id in self.jitted_entry_points:
            return self.jit_globals[self.jitted_entry_points[body_id]]
        else:
            return None

    def __lookup_external_body_impl(self, global_name, body_id):
        """Looks up an external function by global name. Returns a matching function,
           or None if no function was found."""
        if self.compiled_function_lookup is not None:
            result = self.compiled_function_lookup(global_name)
            if result is not None and body_id is not None:
                self.register_compiled(body_id, result, global_name)

            return result
        else:
            return None

    def lookup_compiled_body(self, body_id):
        """Looks up a compiled function by body id. Returns a matching function,
           or None if no function was found."""
        result = self.__lookup_compiled_body_impl(body_id)
        if result is not None:
            return result
        else:
            global_name = self.get_global_name(body_id)
            return self.__lookup_external_body_impl(global_name, body_id)

    def lookup_compiled_function(self, global_name):
        """Looks up a compiled function by global name. Returns a matching function,
           or None if no function was found."""
        body_id = self.get_global_body_id(global_name)
        result = self.__lookup_compiled_body_impl(body_id)
        if result is not None:
            return result
        else:
            return self.__lookup_external_body_impl(global_name, body_id)

    def get_intrinsic(self, name):
        """Tries to find an intrinsic version of the function with the
           given name."""
        if name in self.jit_intrinsics:
            return self.jit_intrinsics[name]
        else:
            return None

    def register_intrinsic(self, name, intrinsic_function):
        """Registers the given intrisic with the JIT. This will make the JIT replace calls to
           the function with the given entry point by an application of the specified function."""
        self.jit_intrinsics[name] = intrinsic_function

    def register_binary_intrinsic(self, name, operator):
        """Registers an intrinsic with the JIT that represents the given binary operation."""
        self.register_intrinsic(name, lambda a, b: tree_ir.CreateNodeWithValueInstruction(
            tree_ir.BinaryInstruction(
                tree_ir.ReadValueInstruction(a),
                operator,
                tree_ir.ReadValueInstruction(b))))

    def register_unary_intrinsic(self, name, operator):
        """Registers an intrinsic with the JIT that represents the given unary operation."""
        self.register_intrinsic(name, lambda a: tree_ir.CreateNodeWithValueInstruction(
            tree_ir.UnaryInstruction(
                operator,
                tree_ir.ReadValueInstruction(a))))

    def register_cast_intrinsic(self, name, target_type):
        """Registers an intrinsic with the JIT that represents a unary conversion operator."""
        self.register_intrinsic(name, lambda a: tree_ir.CreateNodeWithValueInstruction(
            tree_ir.CallInstruction(
                tree_ir.LoadGlobalInstruction(target_type.__name__),
                [tree_ir.ReadValueInstruction(a)])))

    def jit_signature(self, body_id):
        """Acquires the signature for the given body id node, which consists of the
           parameter variables, parameter name and a flag that tells if the given function
           is mutable."""
        if body_id not in self.jitted_parameters:
            signature_id, = yield [("RRD", [body_id, jit_runtime.FUNCTION_BODY_KEY])]
            signature_id = signature_id[0]
            param_set_id, is_mutable = yield [
                ("RD", [signature_id, "params"]),
                ("RD", [signature_id, jit_runtime.MUTABLE_FUNCTION_KEY])]
            if param_set_id is None:
                self.jitted_parameters[body_id] = ([], [], is_mutable)
            else:
                param_name_ids, = yield [("RDK", [param_set_id])]
                param_names = yield [("RV", [n]) for n in param_name_ids]
                param_vars = yield [("RD", [param_set_id, k]) for k in param_names]
                self.jitted_parameters[body_id] = (param_vars, param_names, is_mutable)

        raise primitive_functions.PrimitiveFinished(self.jitted_parameters[body_id])

    def jit_parse_bytecode(self, body_id):
        """Parses the given function body as a bytecode graph."""
        if body_id in self.bytecode_graphs:
            raise primitive_functions.PrimitiveFinished(self.bytecode_graphs[body_id])

        parser = bytecode_parser.BytecodeParser()
        result, = yield [("CALL_ARGS", [parser.parse_instruction, (body_id,)])]
        self.bytecode_graphs[body_id] = result
        raise primitive_functions.PrimitiveFinished(result)

    def check_jittable(self, body_id, suggested_name=None):
        """Checks if the function with the given body id is obviously non-jittable. If it's
           non-jittable, then a `JitCompilationFailedException` exception is thrown."""
        if body_id is None:
            raise ValueError('body_id cannot be None')
        elif body_id in self.jitted_entry_points:
            # We have already compiled this function.
            raise primitive_functions.PrimitiveFinished(
                self.jit_globals[self.jitted_entry_points[body_id]])
        elif body_id in self.no_jit_entry_points:
            # We're not allowed to jit this function or have tried and failed before.
            raise JitCompilationFailedException(
                'Cannot jit function %s at %d because it is marked non-jittable.' % (
                    '' if suggested_name is None else "'" + suggested_name + "'",
                    body_id))
        elif not self.jit_enabled:
            # We're not allowed to jit anything.
            raise JitCompilationFailedException(
                'Cannot jit function %s at %d because the JIT has been disabled.' % (
                    '' if suggested_name is None else "'" + suggested_name + "'",
                    body_id))

    def jit_recompile(self, user_root, body_id, function_name):
        """Replaces the function with the given name by compiling the bytecode at the given
           body id."""
        self.check_jittable(body_id, function_name)

        # Generate a name for the function we're about to analyze, and pretend that
        # it already exists. (we need to do this for recursive functions)
        self.jitted_entry_points[body_id] = function_name
        self.jit_globals[function_name] = None

        (parameter_ids, parameter_list, is_mutable), = yield [
            ("CALL_ARGS", [self.jit_signature, (body_id,)])]

        param_dict = dict(zip(parameter_ids, parameter_list))
        body_param_dict = dict(zip(parameter_ids, [p + "_ptr" for p in parameter_list]))
        dependencies = set([body_id])
        self.compilation_dependencies[body_id] = dependencies

        def handle_jit_exception(exception):
            # If analysis fails, then a JitCompilationFailedException will be thrown.
            del self.compilation_dependencies[body_id]
            for dep in dependencies:
                self.mark_no_jit(dep)
                if dep in self.jitted_entry_points:
                    del self.jitted_entry_points[dep]

            failure_message = "%s (function '%s' at %d)" % (
                exception.message, function_name, body_id)
            if self.jit_success_log_function is not None:
                self.jit_success_log_function('JIT compilation failed: %s' % failure_message)
            raise JitCompilationFailedException(failure_message)

        # Try to analyze the function's body.
        yield [("TRY", [])]
        yield [("CATCH", [JitCompilationFailedException, handle_jit_exception])]
        if is_mutable:
            # We can't just JIT mutable functions. That'd be dangerous.
            raise JitCompilationFailedException(
                "Function was marked '%s'." % jit_runtime.MUTABLE_FUNCTION_KEY)
        body_bytecode, = yield [("CALL_ARGS", [self.jit_parse_bytecode, (body_id,)])]
        state = bytecode_to_tree.AnalysisState(
            self, body_id, user_root, body_param_dict,
            self.max_instructions)
        constructed_body, = yield [("CALL_ARGS", [state.analyze, (body_bytecode,)])]
        yield [("END_TRY", [])]
        del self.compilation_dependencies[body_id]

        # Wrap the tree IR in a function definition.
        constructed_function, = yield [
            ("CALL_ARGS",
             [create_function,
              (function_name, parameter_list, param_dict, body_param_dict, constructed_body)])]

        # Convert the function definition to Python code, and compile it.
        compiled_function = self.jit_define_function(function_name, constructed_function)

        if self.jit_success_log_function is not None:
            self.jit_success_log_function(
                "JIT compilation successful: (function '%s' at %d)" % (function_name, body_id))

        raise primitive_functions.PrimitiveFinished(compiled_function)

    def jit_define_function(self, function_name, function_def):
        """Converts the given tree-IR function definition to Python code, defines it,
           and extracts the resulting function."""
        # The comment below makes pylint shut up about our (hopefully benign) use of exec here.
        # pylint: disable=I0011,W0122

        # Convert the function definition to Python code, and compile it.
        exec(str(function_def), self.jit_globals)

        if self.jit_code_log_function is not None:
            self.jit_code_log_function(function_def)

        # Extract the compiled function from the JIT global state.
        return self.jit_globals[function_name]

    def jit_delete_function(self, function_name):
        """Deletes the function with the given function name."""
        del self.jit_globals[function_name]

    def jit_compile(self, user_root, body_id, suggested_name=None):
        """Tries to jit the function defined by the given entry point id and parameter list."""
        # Generate a name for the function we're about to analyze, and pretend that
        # it already exists. (we need to do this for recursive functions)
        function_name = self.generate_function_name(body_id, suggested_name)
        yield [("TAIL_CALL_ARGS", [self.jit_recompile, (user_root, body_id, function_name)])]

    def jit_thunk(self, get_function_body, global_name=None):
        """Creates a thunk from the given IR tree that computes the function's body id.
           This thunk is a function that will invoke the function whose body id is retrieved.
           The thunk's name in the JIT's global context is returned."""
        # The general idea is to first create a function that looks a bit like this:
        #
        # def jit_get_function_body(**kwargs):
        #     raise primitive_functions.PrimitiveFinished(<get_function_body>)
        #
        get_function_body_name = self.generate_name('get_function_body')
        get_function_body_func_def, = yield [
            ("CALL_ARGS",
             [create_function,
              (get_function_body_name, [], {}, {}, tree_ir.ReturnInstruction(get_function_body))])]
        get_function_body_func = self.jit_define_function(
            get_function_body_name, get_function_body_func_def)

        # Next, we want to create a thunk that invokes said function, and then replaces itself.
        def __jit_thunk(**kwargs):
            # Compute the body id, and delete the function that computes the body id; we won't
            # be needing it anymore after this call.
            body_id = yield [("CALL_KWARGS", [get_function_body_func, kwargs])]
            self.jit_delete_function(get_function_body_name)

            # Try to associate the global name with the body id, if that's at all possible.
            if global_name is not None:
                self.register_global(body_id, global_name)

            compiled_function = self.lookup_compiled_body(body_id)
            if compiled_function is not None:
                # Replace this thunk by the compiled function.
                self.jit_globals[get_function_body_name] = compiled_function
            else:
                def __handle_jit_exception(_):
                    # Replace this thunk by a different thunk: one that calls the interpreter
                    # directly, without checking if the function is jittable.
                    (_, parameter_names, _), = yield [
                        ("CALL_ARGS", [self.jit_signature, (body_id,)])]
                    def __interpreter_thunk(**new_kwargs):
                        named_arg_dict = {name : new_kwargs[name] for name in parameter_names}
                        return jit_runtime.interpret_function_body(
                            body_id, named_arg_dict, **new_kwargs)

                    self.jit_globals[get_function_body_name] = __interpreter_thunk

                yield [("TRY", [])]
                yield [("CATCH", [JitCompilationFailedException, __handle_jit_exception])]
                compiled_function, = yield [
                    ("CALL_ARGS",
                     [self.jit_recompile, (kwargs['user_root'], body_id, "jit_thunk")])]
                yield [("END_TRY", [])]

            # Call the compiled function.
            yield [("TAIL_CALL_KWARGS", [compiled_function, kwargs])]

        thunk_name = self.generate_name('thunk', global_name)
        self.jit_globals[thunk_name] = __jit_thunk
        raise primitive_functions.PrimitiveFinished(thunk_name)

    def jit_thunk_constant(self, body_id):
        """Creates a thunk from given body id.
           This thunk is a function that will invoke the function whose body id is given.
           The thunk's name in the JIT's global context is returned."""
        # We might have compiled the function with the given body id already. In that case,
        # we need not bother with constructing the thunk; we can return the compiled function
        # right away.
        if self.lookup_compiled_body(body_id) is not None:
            raise primitive_functions.PrimitiveFinished(self.get_compiled_name(body_id))

        # Looks like we'll just have to build that thunk after all.
        yield [
            ("TAIL_CALL_ARGS",
             [self.jit_thunk, (tree_ir.LiteralInstruction(body_id),)])]

    def jit_thunk_global(self, global_name):
        """Creates a thunk from given global name.
           This thunk is a function that will invoke the function whose body id is given.
           The thunk's name in the JIT's global context is returned."""
        # We might have compiled the function with the given name already. In that case,
        # we need not bother with constructing the thunk; we can return the compiled function
        # right away.
        body_id = self.get_global_body_id(global_name)
        if body_id is not None and self.lookup_compiled_body(body_id) is not None:
            raise primitive_functions.PrimitiveFinished(self.get_compiled_name(body_id))

        # Looks like we'll just have to build that thunk after all.
        # We want to look up the global function like so
        #
        #     _globals, = yield [("RD", [kwargs['user_root'], "globals"])]
        #     global_var, = yield [("RD", [_globals, global_name])]
        #     function_id, = yield [("RD", [global_var, "value"])]
        #     body_id, = yield [("RD", [function_id, jit_runtime.FUNCTION_BODY_KEY])]
        #
        yield [
            ("TAIL_CALL_ARGS",
             [self.jit_thunk,
              (tree_ir.ReadDictionaryValueInstruction(
                  tree_ir.ReadDictionaryValueInstruction(
                      tree_ir.ReadDictionaryValueInstruction(
                          tree_ir.ReadDictionaryValueInstruction(
                              tree_ir.LoadIndexInstruction(
                                  tree_ir.LoadLocalInstruction(jit_runtime.KWARGS_PARAMETER_NAME),
                                  tree_ir.LiteralInstruction('user_root')),
                              'globals'),
                          global_name),
                      'value'),
                  tree_ir.LiteralInstruction(jit_runtime.FUNCTION_BODY_KEY)),
               global_name)])]