Optimizing Compilers CISC 673 Spring 2009 Data flow analysis

1. Optimizing CompilersCISC 673Spring 2009Data flow analysis John Cavazos University of Delaware

2. Data flow analysis • Solving set of equations posed over graph representation (e.g., CFG) • Based on any or all paths through program • “Any path” or “All path” problems

3. Includes Infeasible Paths a = 1; if (a == 0) { a = 1; } if (a == 0) { a = 2; } • Infeasible paths never actually taken by program, regardless of input • Undecidable to distinguish from feasible

4. Data Flow-Based Optimizations • Dead variable elimination • a = 3; print a; x = 12; halt) a = 3; print a; halt • Copy propagation • x = y; … use of x ) …use of y • Partial redundancy • a = 3*c + d; b = 3*c) b = 3*c; a=b+d • Constant propagation • a = 3; b = 2; c = a+b) a = 3; b = 2; c = 5

5. Example: Redundancy Elimination • Expression e at point p redundant iff every path from procedure’s entry to p contains evaluation of e and value(s) of e’s operands do not change between those earlier evaluations and p • Evaluating e at p always produces the same value as those earlier evaluations

6. A m  a + b n  a + b C q  a + b r  c + d B p  c + d r  c + d Example

7. Redundancy Elimination • If the compiler can prove expression redundant • Replace redundant evaluation with reference • Problem • Proving x+y is redundant • Eliminate redundant evaluation • Can use value numbering

8. Value Numbering • Key notion • Assign a number, V(n), to each expression • V(x+y) = V(j) • iff x+y and j have same value  inputs • Hash value numbers to make efficient • Use numbers to improve the code

9. Local Value Numbering Local  one block at a time • The algorithm • For each expression e in the block • Get value numbers for operands o1 and o2 from hash lookup • Hash <operator,VN(o1),VN(o2)> to get value number for e • If e already had a value number, replace e with a reference • If o1 & o2 are constant, evaluate it & use a “load immediate”

10. Original Code a0 x0 + y0  b0  x0 + y0 a1  17  c0  x0 + y0 Rewritten a03 x01 + y02  b03  a03 a14  17  c03  a03 • 1. Renaming: • Give each value a unique name • While complex, the meaning is clear • 2. Result: • a03 is available • rewriting works Local Value Numbering Example With VNs a03 x01 + y02  b03  x01 + y02 a14  17  c03  x01 + y02

11. D u  e + f E u  e + f F x  e + f e+f is redundant Global Redundancy Elimination Find common subexpressions whose range spans basic blocks, and eliminate unnecessary re-evaluations

12. Expression “available” is as follows: • Expression defined at point p if value computed at p • Expression killed at point p if one or more operands defined at point p • e available at p if every path leading to p contains a prior definition of e and e is not killed between definition and p

13. “Available” Expressions for GCSE Mechanism • System of simultaneous equations over the CFG • Solve the equations to produce a set for each CFG node • Contains names of every expression available on entry • Use these sets, AVAIL(n), for redundancy elimination Safety • x+y  AVAIL(n) proves earlier value x+y is same • Transformation provides name for each value • Several schemes for this mapping

14. Copies are inexpensive • Many copies coalesce away “Available” Expressions for GCSE • Profitability • Don’t add any evaluations • Add some copy operations

15. Computing Available Expressions • For each block b • Let AVAIL(b) be the set of expressions available on entry to b • AVAIL constructed from local sets • Let EXPRKILL(b) be the set of expression killedin b • Let DEEXPR(b) be the set of downward exposed expressions • x  DEEXPR(b)  x defined in b & not subsequently killed in b

16. Computing Available Expressions • Now, AVAIL(b) can be defined as: • AVAIL(b) = ppred(b)(DEEXPR(p) (AVAIL(p)  EXPRKILL(p) )) • AVAIL(n0) = Ø • where preds(b) is the set of b’s predecessors in the CFG • This system of simultaneous equations forms a data-flow problem • Solve it with a data-flow algorithm Entry node in CFG is n0

17. Computing Available Expressions AVAIL(b) = ppred(b)(DEEXPR(p) (AVAIL(p)  EXPRKILL(p) )) Basic Block p … … … DEEXPR (p) Downward exposed expressions And not later killed

18. Computing Available Expressions AVAIL(b) = ppred(b)(DEEXPR(p) (AVAIL(p)  EXPRKILL(p) )) Available upon entry AVAIL(p) Basic Block p … … … EXPRKILL(p) Any expresssions killed AVAIL(p)  EXPRKILL(p) Expressions that Pass through unscathed

19. Available Expressions for GCSE The Big Picture  block b, compute AVAIL(b) Assign unique global names to expressions in AVAIL(b)  block b, value number b starting with AVAIL(b)

20. } Compute DEExpr } Compute ExprKill Compute Local Sets for each Block b assume a block b with operations o1, o2, …, ok VARKILL Ø DEEXPR(b)  Ø for i = k to 1 // from last to first insts assume oi is “x  y + z” add x to VARKILL if (y  VARKILL) and (z  VARKILL) then add “y + z” to DEEXPR(b) EXPRKILL(b)  Ø For each expression e in procedure for each variable v  e if v  VARKILL(b) then EXPRKILL(b)  EXPRKILL(b)  {e}

21. Example v  a + b a  c + d x  e + f DEExpr = {c+d,e+f } VarKill = {y,a,x} ExprKill = {a+b}

22. Compute Available Expressions for all blocks b compute DEExpr(b) and EXPRKILL(b) Changed=truewhile (Changed) Changed=false for all blocks b OldValue = AVAIL(b) AVAIL(b) = ppred(b)(DEEXPR(p) (AVAIL(p)  EXPRKILL(p) )) if AVAIL(b) != OldValue Changed=true

23. C q  a + b r  c + d A m  a + b n  a + b B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f y  a + b z  c + d G Example: Compute DEEXPR assume a block b with operations o1, o2, …, ok VARKILL  Ø DEEXPR(b)  Ø for i = k to 1 // from last to first insts assume oi is “x  y + z” add x to VARKILL if (y  VARKILL) and (z  VARKILL) then add “y + z” to DEEXPR(b) =

24. C q  a + b r  c + d A m  a + b n  a + b B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f y  a + b z  c + d G Example: Compute EXPRKILL EXPRKILL(b)  Ø For each expression e in procedure for each variable v  e if v  VARKILL(b) then EXPRKILL(b)  EXPRKILL(b)  {e }

25. A m  a + b n  a + b C q  a + b r  c + d B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f G y  a + b z  c + d Example ppred(b)(DEEXPR(p) (AVAIL(p)  EXPRKILL(p) )) AVAIL(A) = Ø AVAIL(B) = {a+b}  (Ø  all) = {a+b} AVAIL(C) = {a+b} AVAIL(D) = {a+b,c+d}  ({a+b}  all) = {a+b,c+d} AVAIL(E) = {a+b,c+d} AVAIL(F) = [{b+18,a+b,e+f}  ({a+b,c+d}  {all - e+f})]  [{a+17,c+d,e+f}  ({a+b,c+d}  {all - e+f})] = {a+b,c+d,e+f} AVAIL(G)= [ {c+d}  ({a+b}  all)]  [{a+b,c+d,e+f} ({a+b,c+d,e+f}  all)] = {a+b,c+d}

26. A m  a + b n  a + b C q  a + b r  c + d B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f G y  a + b z  c + d Example  AVAILsets in blue { a+b } { a+b } { a+b,c+d } { a+b,c+d } { a+b,c+d,e+f } { a+b,c+d }

27. Remember Big Picture The Big Picture  block b, compute AVAIL(b) Assign unique global names to expressions in AVAIL(b)  block b, value number b starting with AVAIL(b) We’ve done step 1.

28. Global CSE (replacement step) • Compute a static mapping from expression to name • After analysis & before transformation •  b,e  AVAIL(b), assign e a global name by hashing on e

29. A m  a + b n  a + b C q  a + b r  c + d Assigning unique names to global CSEs a+b  t1 c+d  t2 e+f  t3 B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f G y  a + b z  c + d Example  { a+b } { a+b } { a+b,c+d } { a+b,c+d } { a+b,c+d,e+f } { a+b,c+d }

30. Remember the Big Picture The Big Picture  block b, compute AVAIL(b) Assign unique global names to expressions in AVAIL(b)  block b, value number b starting with AVAIL(b) We’ve done steps 1 & 2.

31. Value Numbering • To perform replacement, value numbering each block b • Initialize hash table with AVAIL(b) • Replace an expression in AVAIL(b) means copy from its name • At each evaluation of a global name, copy new value to its name • Otherwise, value number as in last lecture

32. Net Result • Catches local redundancies with value numbering • Catches nonlocal redundancies because of AVAIL sets • Not quite same effect, but close • Local redundancies found by value • Global redundancies found by spelling

33. A m  a + b t1 m n  t1 B C p  c + d t2  p r  t2 q  t1 r  c + d t2  r D E e  b + 18 s  t1 u  e + f t3 u e  a + 17 t  t2 u  e + f t3 u F v  t1 w  t2 x  t3 G y  t1 z  t2 Example After replacement & local value numbering

34. A m  a + b t1 m n  t1 m m r m m m p B C p  c + d t2  p r  t2 q  t1 r  c + d t2  r D E e  b + 18 s  t1 u  e + f t3 u e  a + 17 t  t2 u  e + f t3 u F v  t1 w  t2 x  t3 r u r G y  t1 z  t2 Example In practice, most of these copies will be folded into subsequent uses…

35. wa+b t1w xa+b t1x wa+b xa+b ya+b Cannot write “w or x” yt1 Some Copies Serve a Purpose • In the example, all the copies coalesce away. • Sometimes, the copies are needed. • Copies into t1 create a common name along two paths • Makes the replacement possible 

36. A m  a + b n  a + b C q  a + b r  c + d B p  c + d r  c + d D e  b + 18 s  a + b u  e + f E e  a + 17 t  c + d u  e + f F v  a + b w  c + d x  e + f G y  a + b z  c + d Example LVN GRE LVN GRE GRE GRE GRE GRE GRE GRE

37. Next Time • More Data Flow