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A Framework for Unrestricted Whole-Program Optimization

A Framework for Unrestricted Whole-Program Optimization. Spyridon Triantafyllis, Matthew J. Bridges , Easwaran Raman, Guilherme Ottoni, David I. August The Liberty Research Group Department of Computer Science Princeton University. Procedure-Based Compilation. Procedure-Based Compilation

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A Framework for Unrestricted Whole-Program Optimization

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  1. A Framework for UnrestrictedWhole-Program Optimization Spyridon Triantafyllis, Matthew J. Bridges, Easwaran Raman, Guilherme Ottoni, David I. August The Liberty Research Group Department of Computer Science Princeton University

  2. Procedure-Based Compilation Procedure-Based Compilation Pros: • Well Known Cons: • Can not exploit opportunities that cross procedures g() f(a,b,c) h() if (EOB) z=x*y f(x,y,5) f(1,2,3) fill B d=a*b …=z ret

  3. Interprocedural Analysis Interprocedural Analysis [Sharir’78] [Morel’78] [Reps’95] Pros: • Increases available information • Enables some optimization across procedure boundaries Cons: • Has to analyze the entire program • Optimizations need to respect the procedure boundary g() f(a,b,c) h() if (EOB) z=x*y f(x,y,5) f(1,2,3) fill B d=a*b …=z ret

  4. Interprocedural Analysis & Interprocedural Opti Interprocedural Analysis [Sharir’78] [Morel’78] [Reps’95] Pros: • Increases available information • Enables some optimization across procedure boundaries Cons: • Has to analyze the entire program • Optimizations need to respect the procedure boundary • Most optimizations will still be intraprocedural g() f(a,b,c,z) h() if (EOB) z=x*y f(x,y,5,z) f(1,2,3,2) fill B d=z …=z ret

  5. Inlining Inlining [Scheifler ‘77] [Hwu’89] [Chang’92] Pros: • Increases optimization scope • Enables specialization • Doesn’t require opti to understand interprocedural concerns Cons: • Hard limit on procedure size • Unnecessary code growth g’() z=x*y if (EOB) fill B f(a,b,c) if (EOB) d=z fill B h() d=a*b jump f(1,2,3) …=z ret

  6. Partial Inlining Partial Inlining [Suganuma’03][Way’00] Pros: • Can alleviate some code growth Cons: • Gains are limited g() z=x*y f’() fill B if (EOB) f’() return f(a,b,c) if (EOB) d=z h() fill B d=a*b jump f(1,2,3) ret …=z

  7. g() f(a,b,c) h() z=x*yf(x,y,5) f(1,2,3) Why Procedures? Procedures • Calling convention boundary • Single-Entry, Single-Exit Pros: • Implicit correlated edges - context sensitivity • Natural unit for divide & conquer compilation Cons: • Optimized for software-engineering • Restricts optimization if (EOB) z=x*y fill B d=a*b d=z …=z ret We don’t have to use procedures!

  8. The Whole-Program CFG Retain useful traits of procedures • Correlated edges • Compilation unit Goal: Obtain an optimizable whole-program representation • Increase optimization scope • Allow all opti to operate on increased scope without change • Targeted code growth if (EOB) z=x*y fill B d=a*b …=z jump

  9. B (1 (2 A G D C The Whole-Program CFG F H )1 )2 E Retain useful traits of procedures • Correlated edges • Compilation unit Goal: Obtain an optimizable whole-program representation • Increase optimization scope • Allow all opti to operate on increased scope without change • Targeted code growth Represent calls and returns as special control-flow transitions [Sharir’78]

  10. Whole-Program Optimizations Optimization destroys the program’s procedural structure! • Example: Superblock Formation [Hwu’92] Unconventional call structures! • Many-to-many call <-> return relation • Must rediscover structure for summary edges A (1 B B (2 G D C’ C H )2 E’ E )1 )1 F’ F

  11. Analyzing the Whole-Program CFG (BE) B’ C’ E’ (BF’) B’ C E D (B’F’) B C E D Context-Sensitive Interprocedural Analysis[Sharir‘78] meet over all realizable paths Identify Entry-Exit Pairs (EEP): • Correlated call & return arcs • Allows use of summary edges • Blocks may belong to more than one EEP A (1 B’ B (2 G D C’ C H )2 E’ E )1 )1 F’ F

  12. Determining a Compilation Unit: Region Formation Region Formation [Hank’95] • arbitrarily shaped, compiler-selected compilation unit A (1 B’ Region Selection • Select seed & add neighbors (profile, structure, dataflow …) B (2 G D Success Criteria • Optimizability vs.compile time • Few too small or too big regions • Intra-region transitions » inter-region transitions Encapsulation • Make regions independently optimizable C’ C H )2 E’ E )1 )1 F’ F Compiler is free to select its own optimization units!

  13. Evaluation Framework: The Velocity Compiler Frontend Frontend Frontend • Evaluation: • Inliner & Opti. ported from IMPACT • Targeting Itanium 2 Procedures Procedures Procedures Inlining WCFG DetermineCompilation Unit Region Form. Procedures Regions Superblock Superblock Superblock Classical & ILP Optimizer Classical & ILP Optimizer Classical & ILP Optimizer Optimize Compilation Unit Scheduling Scheduling Scheduling Executable Executable Executable Baseline Inlining PBE

  14. Code Growth 1.45 1.23 Code Size

  15. Speedup - Train Input 1.07

  16. Conclusion Procedure boundaries restrict optimization! Ways to deal with procedures exist, but limited • Interprocedural analysis & opti: Scales badly, not always possible • Inlining: Unnecessary Code growth • Procedures are not the right compilation unit PBE offers unrestricted and practical whole-program optimization • An expanded form of interprocedural analysis • New region formation framework and heuristics • An interprocedural region encapsulation method

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