1. Introduction to Advanced Topics Chapter 1 Mooly Sagiv Schrierber 317 03-640-7606 www.math.tau.ac.il/~sagiv/courses/acd.html

2. Outline Course requirements Review of compiler structure Advanced issues in elementary topics The importance of optimizations Structure of optimizing compilers Placement of optimizations Advanced topics

3. Course Requirements Prepare course notes 10% Theoretical assignments 30% Final home exam 60%

4. Compiler Structure Symbol table and access routines OS Interface String of characters Scanner tokens Semantic analyzer Parser Code Generator IR AST Object code

5. Advanced Issues in Elementary Topics Symbol table management(3) –Efficiency –Overloading Type Inference Intermediate Language Selection(4) Run-Time Support(5) Producing Code Generators (6)

6. procedure BACH is procedure put (x: boolean) is begin null; end; procedure put (x: float) is begin null; end; procedure put (x: integer) is begin null; end; package x is type boolean is (false, true); function f return boolean; -- (D1) end x; package body x is function f return boolean is begin null; end; end x; function f return float is begin null; end; -- (D2) use x; begin put (f); -- (A1) A: declare f: integer; -- (D3) begin put (f); -- (A2) B: declare function f return integer is begin null; end; -- (D4) begin put (f); -- (A3) end B; end A; end BACH;

7. Advanced Issues in Elementary Topics Symbol table management(3) –Efficiency –Overloading Type Inference Intermediate Language Selection(4) Run-Time Support(5) Producing Code Generators (6)

8. Advanced Issues in Elementary Topics Symbol table management(3) –Efficiency –Overloading Type Inference Intermediate Language Selection(4) Run-Time Support(5) Producing Code Generators (6)

9. Intermediate Language Selection Low Vs. High level control flow structures Flat Vs. Hierarchical (tree) Machine Vs. High level of instructions (Symbolic) Registers Vs. Stack Normal forms (SSA) Intermediate forms: Control Flow Graph, Call Graph, Program Dependence Graph Issues: Engineering, efficiency, portability, optimization level

10. HIR for v  v1 by v2 to v3 do a[i] :=2 endfor MIR v  v1 t2  v2 t3  v3 L1: if v >t3 goto L2 t4  addr a t5  4*i t6  t4+t5 *t6  2 v  v + t2 goto L1 L2: LIR s2  s1 s4  s3 s6  s5 L1: if s2 >s6 goto L2 s7  addr a s8  4*s9 s10  s7+s8 [s10]  2 s2  s2 + s4 goto L1 L2: IRs in the Book

11. Single Static Assignment Form (SSA) s2  s1 s4  s3 s6  s5 L1: if s2 >s6 goto L2 s7  addr a s8  4*s9 s10  s7+s8 [s10]  2 s2  s2 + s4 L2: B2 s2 1  s1 s4  s3 B1 s2 2   (s2 1, s2 3 ) s2 2 >=s6 N s7  addr a s8  4*s9 s10  s7+s8 [s10]  2 s2 3  s2 2 + s4 Y B3

12. Advanced Issues in Elementary Topics Symbol table management(3) –Efficiency –Overloading Type Inference Intermediate Language Selection(4) Run-Time Support(5) Producing Code Generators (6)

13. Run-Time Support Data representation and instructions Register usage Stack frames (activation records) Parameter passing disciplines Symbolic and polymorphic language support Garbage Collection

14. Advanced Issues in Elementary Topics Symbol table management(3) –Efficiency –Overloading Type Inference Intermediate Language Selection(4) Run-Time Support(5) Producing Code Generators (6)

15. The Importance of Optimizations One pass compilers produce slow code Much of the time spent in loops –optimize loops Machines can be simpler and faster if optimizing compilers are used (RISC, VLIW) Programs are complex and general Compilers need to be modular

16. C code int a, b, c, d; c = a + b; d = c + 1; SPARC code ldw a, r1 ldw b, r2 add r1, r2, r3 stw r3, c ldw c, r3 add r3, 1, r4 stw r4, d Optimized SPARC code add r1, r2, r3 add r3, 1, r4 10 cycles 2 cycles

17. Application Dependent Optimizations Functional programs –replacement of recursion by loops (tail-calls elimination) –replacement of heap by stack Object Oriented Programs –Dead member elimination –Replacement of virtual by static function Numeric Code Database Code

18. String Object Scanner Parser Semantic LIR generator Optimizer Fin. assembly Tokens AST LIR Object String Scanner Parser Semantic IR generator Optimizer Code generator Tokens AST MIR LIR Post. optimizer

19. Mixed vs. Low Level Optimizers Mixed –Sun-SPARC, Dec. Alpha, SGI-MIPS, Intel’s 386 Easier to port More efficient compilation? Supports CISC Low Level HP-PA-RISC/IBM-Power PC More efficient code Conceptually simpler (in RISC) Used for multiple programming languages

20. Translation by Preprocessing Some programming languages are translated into C –Elimination of includes, C++(cfront), Haskel Quick and portable solution C supports some indirect source level debugging Other examples: Fortran into “vector” Fortran program

21. Data-Cache Optimizations(20) String Object Scanner Parser Semantic Data-cache optimizer Tokens AST HIR MIR 

22. IBM PowerPC compiler String Object Scanner Parser Semantic LIR generator Optimizer Fin. assembly Tokens AST LIR=XIL LIR Data-cache optimizer Low-to-High High-to-Low HIR=YIL

23. Outline Review of compiler structure Advanced issues in elementary topics The importance of optimizations Structure of optimizing compilers Placement of optimizations Advanced Topics

24. Scalar replacement of array references Data-cache optimizations Procedure integration Tail-call elimination Scalar replacement of aggregates Sparse constant propagation Interprocedural constant propagation Procedure specialization and cloning Sparse conditional constant propagation Global value numbering Local and global copy propagation Sparse conditional constant propagation Dead code elimination Common Subexpression Elimination Loop invariant code motion Partial redundency Elimination Inline expansion Leaf-routine optimizations Instruction Scheduling 1 Register allocation Instruction Scheduling 2 Intraprocedural I-cache optimizations Instruction prefetching Data prefertching Branch predication Interprocedural register allocation Interprocedural I-cache optimization

25. Scalar replacement after constant propagation a  1 a= 1 Y N B.x  1.0 B.y  1.0 read B.x read B.y B.x = 1.0 Y N c c c  B.x

26. Scalar replacement before constant propagation B.x  1.0 c  2 read B.y B.x = 1.0 Y N B.x  B.x + c d d d d d  B.x

27. Theoretically Open Questions Picking the “right” order Combining optimizations Proving correctness

28. Tentative Schedule 30/3 Introduction(1) 13/4 No class (read Chapter 2 and solve Homework #1) 20/4 Yom Hazikaron 24/4 9am, Intermediate Representations(4) 27/4 Control Flow Analysis (7) 4/5 Data Flow Analysis (8) 11/5 Dependence Analysis and Dependence Graphs(9) 18/5 Introduction to Optimization(11) 25/5 Early Optimizations (12) 1/6 Redundancy Elimination (13) 8/6 Loop Optimizations (14) 7/6 Interprocedural Analysis and Optimizations (19) 14/6 Optimizations for memory hierarchy (20) 21/6 Case Studies of Compilers and Future Trends (21)

29. Uncovered Chapters Symbol tables(3) Run-time support(5) Producing code generators automatically (6) Alias analysis(10) Procedure optimizations (15) Register allocation (16) Code scheduling (17) Control-Flow and Low-Level Optimizations (18)

30. Uncovered Topics Code profiling Source level debugging Parallelization and vectorization Just in time compilation

31. Advanced Topics Code Profiling Parallelization and vectorization Just in time compilation Optimize for Power Trusted compilers