Chapter 4: External Argument and Comparisons

In this chapter we extend the language grammar with following features:

• The program receives a single argument named arg of integer type from external environment.
• Expressions support comparison operators.
• We introduce a scope sensitive name binding $ctrl for the current incoming control node. Thus, our Return is no longer hard-wired to Start, instead it tracks the in scope $ctrl binding.

Here is the complete language grammar for this chapter.

You can also read this chapter in a linear Git revision history on the linear branch and compare it to the previous chapter.

Extensions to Intermediate Representation

In this chapter we add some new nodes and revise some existing nodes. Following are revised or new nodes

Node Name	Type	Description	Inputs	Value
MultiNode	Abstract class	A node that has a tuple result		A tuple
Start	Control	Start of function, now a MultiNode		A tuple with a ctrl token and an arg data node
Proj	Data	Projection nodes extract values from MultiNode	A MultiNode and index	Result is the extracted value from the input MultiNode at offset index
Bool	Data	Represents results of a comparison operator	Two data nodes	Result is a comparison, represented as integer value where 1=true, 0=false
Not	Data	Logical not	One data node	Result converts 0 to 1 and vice versa

Below is our list of Nodes from Chapter 3:

Node Name	Type	Description	Inputs	Value
Return	Control	End of function	Predecessor control node, Data node value	Return value of the function
Constant	Data	Constants such as integer literals	None, however Start node is set as input to enable graph walking	Value of the constant
Add	Data	Add two values	Two data nodes, values are added, order not important	Result of the add operation
Sub	Data	Subtract a value from another	Two data nodes, values are subtracted, order matters	Result of the subtract
Mul	Data	Multiply two values	Two data nodes, values are multiplied, order not important	Result of the multiply
Div	Data	Divide a value by another	Two data nodes, values are divided, order matters	Result of the division
Minus	Data	Negate a value	One data node, value is negated	Result of the unary minus
Scope	Symbol Table	Represents scopes in the graph	All nodes that define variables	None

Projection Nodes

We add projection nodes that are used to extract a specific tuple member from a multi-valued node. Each projection node contains an index of the field to extract from its input node. Projection nodes allow us to maintain labeled use-def edges as simple Node references.

In the visuals, projection nodes are shown as rectangular boxes inside the node to which they are attached.

Visualisation

In the visual above, the projection nodes have been tagged by the names associated with the outputs of the Start node. Both MultiNode that contain Control and Control nodes are yellow. $ctrl and arg are outputs(users) of StartNode(START) and have their MultiNode as their only input in slot 0. The label has no semantics and is used during debug printing.

public ProjNode(MultiNode ctrl, int idx, String label) {
    super(ctrl);

_scope.define(ScopeNode.CTRL, new ProjNode(START, 0, ScopeNode.CTRL).peephole());
_scope.define(ScopeNode.ARG0, new ProjNode(START, 1, ScopeNode.ARG0).peephole());

These projection nodes are going to extract the types for CTRL and ARG0 from the START MultiNode. The MultiNode holds the types as a TypeTuple:

public StartNode(Type[] args) {
    super();
    _args = new TypeTuple(args);

Extracting the types is based on the _idx:

return t instanceof TypeTuple tt ? tt._types[_idx] : Type.BOTTOM;

Initial values

An argument is always provided, and defaults to TypeInteger.BOT. Individual tests can (and do) pass in other integer values by calling new Parser with an argument:

Parser parser = new Parser("return arg; #showGraph;", TypeInteger.constant(2));

The graph:

• $ctrl and arg are both defined in the outermost symbol table, at lexical depth 0.
• There is an empty global-scope symbol table created at depth 1; in the future global variables will be defined here.
• There is no line for the scope $ctrl because control is dead after the return. It is manually set to null, which calls setDef to kill the node (and killed nodes are not part of the program and not visualized).

    ctrl(null);             // Kill control

• The arg projection node is not included in the cluster because arg is a constant. The arg was originally defined by a ProjNode; but when peephole is called the computed type is a constant, and the ProjNode gets replaced with a ConstantNode:

public final Node peephole( ) {
    Type type = _type = compute(); 
    /*   type = {TypeInteger@1527} "2"  */

    if (_disablePeephole)
        return this;
    
    // ProjNode is not a constant unlike its type.
    if (!(this instanceof ConstantNode) && type.isConstant())
        /* Create Constant(2) */
        return deadCodeElim(new ConstantNode(type).peephole());
    
    /* won't get called */
    ...

If you don't pass an argument you get TypeInteger.BOT

    Parser parser = new Parser("return arg; #showGraph;");
    ...
    
public Parser(String source) {
    this(source, TypeInteger.BOT);
}
    

We clearly see this is not a constant:

public final static TypeInteger BOT = new TypeInteger(false, 1); 
   /* _is_con = false */

So the arg projection node remains in the cluster:

When Is Control Not-Null?

In later chapters, $ctrl will point to other control nodes, such as If and Region (and Loop), but for now with no other control flow it always gets set to null after a Return.

Note Regarding Visualizations

From this chapter onwards we omit the edges from Constants to Start node, mainly to reduce clutter and help draw reader's attention to the more important aspects of the graph.

Changes to Type System

In Chapter 2 we introduced the Type System.

We have annotated Nodes with Types and the Type annotation serves two purposes:

• It defines the set of operations allowed on the Node, and
• it defines the set of values the Node takes on.

We mentioned in Chapter 2 that the set of values associated with a Type at a specific Node can be conveniently represented as a lattice.

The type itself is identified by the Java class Type and subtypes. The type implementation uses Java classes as convenient to deal with a Types' internal structure - but the Java classes have no relation to a Type's place in the lattice.

In this chapter we extend the Type hierarchy as follows:

Type
+-- TypeControl             (New - represents control token)
+-- TypeInteger             (Enhanced - now has Top and Bottom types)
+-- TypeBot
+-- TypeTuple               (New - represents multi-valued result)

Our enhanced Lattice looks like this:

In this chapter we introduce the possibility of a program input variable named arg; all we know about this variable is that it is some integer value, but we do not know whether it is a constant or not.

To support the requirements for non-constant integer values, we enhance TypeInteger to allow it to represent IntTop and IntBot integer types in addition to the earlier constant value.

Now that integer values may be constants or non-constants, we need to introduce the "meet" operator in our lattice. The meet operator describes rules that define the resulting type when we combine integer values.

	IntBot	Con1	Con2	IntTop
IntBot	IntBot	IntBot	IntBot	IntBot
Con1	IntBot	Con1	IntBot	Con1
IntTop	IntBot	Con1	Con2	IntTop

In the table above Con1 and Con2 represent two distinct integer values, and serve to explain the rules below.

• The meet of IntTop with any integer constant is that constant.
• The meet of IntBot with any integer value is IntBot.
• The meet of any integer with itself is that integer.
• The meet of two unrelated integer constants is IntBot.

Currently, all our integer valued nodes are either a constant or a IntBot integer type. When we start optimizing loops, we will start seeing IntTop values.

$ctrl name binding

In previous chapters, we had a hard coded control input edge from Start to Return. In this chapter we no longer have such a hard-wired edge. Instead, we track the current in-scope control node via the name $ctrl. This means that when we need to create an edge to the predecessor control node, we simply look up this name in the current scope.

This introduces the idea that the control flow subgraph is a Petri net model.¹ The control token moves virtually from node to node as execution proceeds. The initial control token is in Start, it then moves via the Proj node to Return. In later chapters we will see how the token moves across branches.

More Peephole Optimizations

Now that we have non-constant integer values, we can do additional optimizations, rearranging algebraic expressions to enable constant folding. For example:

return 1 + arg + 2;

We would expect the compiler to output arg+3 here, but as it stands what we get is:

We need to perform some algebraic simplifications to enable better outcome. For example, we need to rearrange the expression as follows:

arg + (1 + 2)

This then enables constant folding and the final outcome is shown below. By canonicalizing expressions we fold common addressing math constants, remove algebraic identities and generally simplify the code.

Here is a list of peepholes introduced in this Chapter, more will be introduced in later chapters:

Before	After	Description
(arg + 0 )	arg	Add of zero identity
(arg * 1 )	arg	Multiple of one identity
(con + arg)	(arg + con)	Move constants to right, to encourage folding
(con * arg)	(arg * con)	Move constants to right, to encourage folding
(con1 + (arg + con2))	(arg + (con1 + con2))	Move constants to right, to encourage folding
((arg1 + con) + arg2)	((arg1 + arg2) + con)	Move constants to right, to encourage folding
(arg + arg)	(arg * 2)	Sum-of-products form
(arg - arg)	0	Sub of same is 0
(con / 1)	con	Division by one
(arg == arg)	1	Compare of same
(arg != arg)	0	Compare of same
(arg < arg)	0	Compare of same
(arg > arg)	0	Compare of same
(arg <= arg)	1	Compare of same
(arg >= arg)	1	Compare of same

Peephole Walkthrough

The peephole optimizations introduced in this chapter are local. They are triggered during parsing as new nodes are created, before the newly created node has any uses.

For example, when we parse a unary expression, and create a Node for the parsed expression, peephole() is invoked on the newly created MinusNode:

private Node parseUnary() {
    if (match("-")) return new MinusNode(parseUnary()).peephole();
    return parsePrimary();
}

As another example, here is the parsing of comparison operators, also introduced in this chapter:

private Node parseComparison() {
    var lhs = parseAddition();
    if (match("==")) return new BoolNode.EQNode(lhs, parseComparison()).peephole();
    if (match("!=")) return new BoolNode.NENode(lhs, parseComparison()).peephole();
    if (match("<=")) return new BoolNode.LENode(lhs, parseComparison()).peephole();
    if (match("<" )) return new BoolNode.LTNode(lhs, parseComparison()).peephole();
    if (match(">=")) return new BoolNode.GENode(lhs, parseComparison()).peephole();
    if (match(">" )) return new BoolNode.GTNode(lhs, parseComparison()).peephole();
    return lhs;
}

The implementation of peephole() is in the main Node class, and is thus shared by all subclasses of Node.

public final Node peephole( ) {
    // Compute initial or improved Type
    Type type = _type = compute();

    // Replace constant computations from non-constants with a constant node
    if (!(this instanceof ConstantNode) && type.isConstant())
        return deadCodeElim(new ConstantNode(type).peephole());

    // Ask each node for a better replacement
    Node n = idealize();
    if( n != null )         // Something changed
        // Recursively optimize
        return deadCodeElim(n.peephole());

    return this;            // No progress
}

The peephole method does following:

• Compute a Type for the node.
• If the Type is a Constant and the node is not a ConstantNode, replace with a ConstantNode, recursively invoking peephole on the new constant.
• Otherwise, ask the Node for a better replacement via a call to idealize(). The "better replacement" is things like (1+2) becomes 3 and 1+(x+2)) becomes (x+(1+2)).
• • Each Node subtype is responsible for deciding what the idealize() step should do. If there is a better replacement then the node returns a non null value.
• • If we see a non null value, something changed, so we invoke peephole() again and then also run dead code elimination on the (now dead and replaced) this node.

peephole() calls deadCodeElim() which is shown below.

Dead Code Elimination(DCE)

We call kill every time a Node makes the 1-user-to-0-users transition during graph editing. This commonly happens when replacing via peeps and exiting scopes. This recursive kill amounts to Dead Code Elimination in many other compilers; here we call it in a very fine-grained way. Many Nodes will be created by the parser, only to be killed before the very next lexeme is parsed.

For more information please read the appendix section on dead code elimination.

The suggestively called deadCodeElim function is a thin wrapper over kill used by peepholeOpt to avoid prematurely killing a Node which only briefly makes the 1->0 users transition.

// m is the new Node, self is the old.
// Return 'm', which may have zero uses but is alive nonetheless.
// If self has zero uses (and is not 'm'), {@link #kill} self.
private Node deadCodeElim(Node m) {
    // If self is going dead and not being returned here (Nodes returned
    // from peephole commonly have no uses (yet)), then kill self.
    if( m != this && isUnused() ) {
        // Killing self - and since self recursively kills self's inputs we
        // might end up killing 'm', which we are returning as a live Node.
        // So we add a bogus extra null output edge to stop kill().
        m.addUse(null); // Add bogus null use to keep m alive
        kill();            // Kill self because replacing with 'm'
        m.delUse(null);    // Remove bogus null.
    }
    return m;
}

Note the temporary add of a bogus user to the Node m. The reason this is done is that we know m is the new replacement and is alive, but since it is not yet hooked into the graph, it has no users yet. By adding a bogus user we prevent it being mistaken for dead and being killed.

Footnotes

1. Click, C. (1995). Combining Analyses, Combining Optimizations, 131. ↩