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Chapter: Principles of Compiler Design - Code optimization

Code Improvig Transformations

Algorithms for performing the code improving transformations rely on data-flow information. Here we consider common sub-expression elimination, copy propagation and transformations for moving loop invariant computations out of loops and for eliminating induction variables. Global transformations are not substitute for local transformations; both must be performed.

CODE IMPROVIG TRANSFORMATIONS

 

Algorithms for performing the code improving transformations rely on data-flow information. Here we consider common sub-expression elimination, copy propagation and transformations for moving loop invariant computations out of loops and for eliminating induction variables. Global transformations are not substitute for local transformations; both must be performed.

 

Elimination of global common sub expressions:

• The available expressions data-flow problem discussed in the last section allows us to determine if an expression at point p in a flow graph is a common sub-expression. The following algorithm formalizes the intuitive ideas presented for eliminating common sub-expressions.

 

ALGORITHM: Global common sub expression elimination.

 

INPUT: A flow graph with available expression information. OUTPUT: A revised flow graph.

 

METHOD: For every statement s of the form x := y+z6 such that y+z is available at the beginning of block and neither y nor r z is defined prior to statement s in that block, do the following.

 

1.     To discover the evaluations of y+z that reach s’s block, we follow flow graph edges, searching backward from s’s block. However, we do not go through any block that evaluates y+z. The last evaluation of y+z in each block encountered is an evaluation of y+z that reaches s.

2.     Create new variable u.

3.     Replace each statement w: =y+z found in (1) by

a.     u : = y + z

b.     w : = u

4.     Replace statement s by x:=u.

 

Some remarks about this algorithm are in order:

 The search in step(1) of the algorithm for the evaluations of y+z that reach statement s can also be formulated as a data-flow analysis problem. However, it does not make sense to solve it for all expressions y+z and all statements or blocks because too much irrelevant information is gathered.

 

1.     Not all changes made by algorithm are improvements. We might number of different evaluations reaching s found in step (1), probably to one.

2.     Algorithm will miss the fact that a*z and c*z must have the same value in

a :=x+y c :=x+y

vs

b :=a*zd :=c*z

 

Because this simple approach to common sub expressions considers only the literal expressions themselves, rather than the values computed by expressions.

 

Copy propagation:

Various algorithms introduce copy statements such as x :=copies may also be generated directly by the intermediate code generator, although most of these involve temporaries local to one block and can be removed by the dag construction. We may substitute y for x in all these places, provided the following conditions are met every such use u of x.

 

1.     Statement s must be the only definition of x reaching u.

 

2.     On every path from s to including paths that go through u several times, there are no assignments to y.

 

Condition (1) can be checked using ud-changing information. We shall set up a new data-flow analysis problem in which in[B] is the set of copies s: x:=y such that every path from initial node to the beginning of B contains the statement s, and subsequent to the last occurrence of s, there are no assignments to y.

 

 

ALGORITHM: Copy propagation.

 

INPUT: a flow graph G, with ud-chains giving the definitions reaching block B, and with c_in[B] representing the solution to equations that is the set of copies x:=y that reach block B along every path, with no assignment to x or y following the last occurrence of x:=y on the path. We also need ud-chains giving the uses of each definition.

 

OUTPUT: A revised flow graph.

METHOD: For each copy s : x:=y do the following:

 

1.     Determine those uses of x that are reached by this definition of namely, s: x: =y.

 

2.     Determine whether for every use of x found in (1) , s is in c_in[B], where B is the block of this particular use, and moreover, no definitions of x or y occur prior to this use of x within B. Recall that if s is in c_in[B]then s is the only definition of x that reaches B.

 

3.     If s meets the conditions of (2), then remove s and replace all u by y.

 

Detection of loop-invariant computations:

 

Ud-chains can be used to detect those computations in a loop that are loop-invariant, that is, whose value does not change as long as control stays within the loop. Loop is a region consisting of set of blocks with a header that dominates all the other blocks, so the only way to enter the loop is through the header.

 

If an assignment x := y+z is at a position in the loop where all possible definitions of y and z are outside the loop, then y+z is loop-invariant because its value will be the same each time x:=y+z is encountered. Having recognized that value of x will not change, consider v:= x+w, where w could only have been defined outside the loop, then x+w is also loop-invariant.

 

ALGORITHM: Detection of loop-invariant computations.

 

INPUT: A loop L consisting of a set of basic blocks, each block containing sequence of three-address statements. We assume ud-chains are available for the individual statements.

 

OUTPUT: the set of three-address statements that compute the same value each time executed, from the time control enters the loop L until control next leaves L.

METHOD: we shall give a rather informal specification of the algorithm, trusting that the principles will be clear.

 

1.     Mark “invariant” those statements whose operands are all either constant or have all their reaching definitions outside L.

 

2.     Repeat step (3) until at some repetition no new statements are marked “invariant”.

3.     Mark “invariant” all those statements not previously so marked all of whose operands either are constant, have all their reaching definitions outside L, or have exactly one reaching definition, and that definition is a statement in L marked invariant.

 

Performing code motion:

 

Having found the invariant statements within a loop, we can apply to some of them an optimization known as code motion, in which the statements are moved to pre-header of the loop. The following three conditions ensure that code motion does not change what the program computes. Consider s: x: =y+z.

 

1.     The block containing s dominates all exit nodes of the loop, where an exit of a loop is a node with a successor not in the loop.

 

2.     There is no other statement in the loop that assigns to x. Again, if x is a temporary assigned only once, this condition is surely satisfied and need not be changed.

3. No use of x in the loop is reached by any definition of x other than will be satisfied,

normally, if x is temporary.

 

ALGORITHM: Code motion.

INPUT: A loop L with ud-chaining information and dominator information.

 

OUTPUT: A revised version of the loop with a pre-header and some statements moved to the pre-header.

 

METHOD:

1.     Use loop-invariant computation algorithm to find loop-invariant statements.

2.     For each statement s defining x found in step(1), check:

i)       That it is in a block that dominates all exits of L,

ii)    That x is not defined elsewhere in L, and

iii)  That all uses in L of x can only be reached by the definition of x in statement s.

 

3.     Move, in the order found by loop-invariant algorithm, each statement s found in (1) and meeting conditions (2i), (2ii), (2iii) , to a newly created pre-header, provided any operands of s that are defined in loop L have previously had their definition statements moved to the pre-header.

 

To understand why no change to what the program computes can occur, condition (2i) and (2ii) of this algorithm assure that the value of x computed at s must be the value of x after any exit block of L. When we move s to a pre-header, s will still be the definition of x that reaches the end of any exit block of L. Condition (2iii) assures that any uses of x within L did, and will continue to, use the value of x computed by s.

 

Alternative code motion strategies:

 

The condition (1) can be relaxed if we are willing to take the risk that we may actually increase the running time of the program a bit; of course, we never change what the program computes. The relaxed version of code motion condition (1) is that we may move a statement s

assigning x only if:

 

1’. The block containing s either dominates all exists of the loop, or x is not used outside the loop. For example, if x is a temporary variable, we can be sure that the value will be used only in its own block.

 

If code motion algorithm is modified to use condition (1’), occasionally the running time will increase, but we can expect to do reasonably well on the average. The modified algorithm may move to pre-header certain computations that may not be executed in the loop. Not only does this risk slowing down the program significan an error in certain circumstances.

 

Even if none of the conditions of (2i), (2ii), (2iii) of code motion algorithm are met by an assignment x: =y+z, we can still take the computation y+z outside a loop. Create a new temporary t, and set t: =y+z in the pre-header. Then replace x: =y+z by x: =t in the loop. In many cases we can propagate out the copy statement x: = t.

 

Maintaining data-flow information after code motion:

 

The transformations of code motion algorithm do not change ud-chaining information, since by condition (2i), (2ii), and (2iii), all uses of the variable assigned by a moved statement s that were reached by s are still reached by s from its new position. Definitions of variables used by s are either outside L, in which case they reach the pre-header, or they are inside L, in which case by step (3) they were moved to pre-header ahead of s.

 

If the ud-chains are represented by lists of pointers to pointers to statements, we can maintain ud-chains when we move statement s by simply changing the pointer to s when we move it. That is, we create for each statement s pointer ps, which always points to s. We put the pointer on each ud-chain containing s. Then, no matter where we move s, we have only to change ps , regardless of how many ud-chains s is on.

 

The dominator information is changed slightly by code motion. The pre-header is now the immediate dominator of the header, and the immediate dominator of the pre-header is the node that formerly was the immediate dominator of the header. That is, the pre-header is inserted into the dominator tree as the parent of the header.

 

Elimination of induction variable:

 

A variable x is called an induction variable of a loop L if every time the variable x changes values, it is incremented or decremented by some constant. Often, an induction variable is incremented by the same constant each time around the loop, as in a loop headed by for i := 1 to 10. However, our methods deal with variables that are incremented or decremented zero, one, two, or more times as we go around a loop. The number of changes to an induction variable may even differ at different iterations.

A common situation is one in which an induction variable, say i, indexes an array, and some other induction variable, say t, whose value is a linear function of i, is the actual offset used to access the array. Often, the only use made of i is in the test for loop termination. We can then get rid of i by replacing its test by one on t. We shall look for basic induction variables, which are those variables i whose only assignments within loop L are of the form i := i+c or i-c, where c is a constant.

 

 

ALGORITHM: Elimination of Induction variable

 

INPUT: A loop L with reaching definition information, loop-in information and live variable information.

 

OUTPUT: A revised loop. METHOD:

 

1.     Consider each basic induction variable i whose only uses are to compute other induction variables in its family and in conditional branches. Take some j in i’s family, preferably one such that c and d in its triple are as simple as possible and modify each test that i appears in to use j instead. We assume in the following that c is positive. A test of the form ‘if i relop x goto B’, where x is not an induction variable, is replaced by

 


where, r is a new temporary. The case ‘if x relop i goto B’ is handled analogously. If there are two induction variables i1 and i2 in the test if i1 relop i2 goto B, then we check if both i1 and i2 can be replaced. The easy case is when we have j1 with triple and j2 with triple, and c1=c2 and d1=d2. Then, i1 relop i2 is equivalent to j1 relop j2.

 

2.     Now, consider each induction variable j for which a statement j: =s was introduced. First check that there can be no assignment to s between the introduced statement j:=s and any use of j. In the usual situation, j is used in the block in which it is defined, simplifying this check; otherwise, reaching definitions information, plus some graph analysis is needed to implement the check. Then replace all uses of j by uses of s and delete statement j: =s.

 

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