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Enhancing the Role of Inlining in Effective Interprocedural Parallelization

Enhancing the Role of Inlining in Effective Interprocedural Parallelization. Jichi Guo, Mike Stiles Qing Yi, Kleanthis Psarris. Problem. Inter-procedural parallelization Parallel after inlining Gain more parallelizable loops Lost of parallelized loops

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Enhancing the Role of Inlining in Effective Interprocedural Parallelization

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  1. Enhancing the Role of Inlining in Effective Interprocedural Parallelization Jichi Guo, Mike Stiles Qing Yi, KleanthisPsarris

  2. Problem • Inter-procedural parallelization • Parallel after inlining • Gain more parallelizable loops • Lost of parallelized loops • Inlining messes up caller / callee • Missed parallel opportunities • Inlining increases code complexity

  3. Goal • Keep the gain parallelizable loops • Prevent the lost parallelism • Discover the missed opportunities

  4. Solution • Summarize the code using annotation • Express the underlying information • Inline the annotation before parallelization • Pass the summarized information to the compiler • Reverse-inline after parallelization • Revert inlining side effects • Maintain equivalence

  5. Outline • Innovations • Problems of parallel + inline strategy • Annotation language • Annotation-based inlining technique • Experiments • Summary

  6. Outline • Innovations • Problems of parallel + inline strategy • Annotation language • Annotation-based inlining technique • Experiments • Summary

  7. Problems of parallel + inlining • Parallel + inlining • Conventional inlining with heuristics and pre-transformations • Heuristics: code size • Transformations: linearization, forward substitution • Intra-procedural loop parallelization • Fortran do-all loop • Goal • Gain loops in caller • Problems • Lost loops in caller / callee • Missed loops in caller

  8. Problems of parallel + inlining • Lost of parallelizable loops in caller/callee • Transformations that cause the lost • Forward substitution • Linearization • Forward substitution of non-linear subscripts • Create indirect array references • Linearization of array dimensions • Mess up array shapes

  9. Problems of parallel + inlining • Forward substitution of non-linear subscripts • Create indirect array references X2(I) ⇒ T(IX(7) + I) Y2(I) ⇒ T(IX(8) + I) Z2(I) ⇒ T(IX(9) + I)

  10. Problems of parallel + inlining • Linearization of array dimensions • Mess up array shapes PP(i, j, k) ⇒ PP(i + j*4 + k*16)

  11. Problems of parallel + inlining • Missed parallelizable loops in caller • Coding styles that cause the lost • Opaque compositional subroutines • A calls B, B calls C, C calls D, … • Array access • When it is difficult to determine which part is killed • Debugging and Error Checking • Statement that breaks the dependency is never executed • I/O statements • Indirect array references • ID=IDX(I), X = A(ID)

  12. Problems of parallel + inlining • Opaque compositional subroutines • A calls B, B calls C, C calls D, …

  13. Problems of parallel + inlining • Array access • Difficult to determine which part is killed CTR computed at runtime

  14. Problems of parallel + inlining • Debugging and Error Checking • Statement that breaks the dependency is never executed • I/O statements

  15. Problems of parallel + inlining • Indirect array references IN=>NODE NODE=>IREL IREL=>RHSB

  16. Outline • Innovations • Problems of parallel + inline strategy • Annotation language • Annotation-based inlining technique • Experiments • Summary

  17. The annotation language • Goal • Summarize information • Avoid ambiguity

  18. The annotation language • Restricted grammar • Special operators • Writing annotations

  19. The annotation language • Restricted grammar • Do-all loop only • No goto

  20. The annotation language • Special operators y = operator(x1, x2, …, xn) Purpose: abstract relation • Unknown operator • Relation is unknown • Generic functions • Unique operator • Relation is one-to-one, from X to Y

  21. The annotation language • Writing annotations • Eliminating adverse side effects • Preserve caller and callee if inlining breaks the dependency • Summarize opaque subroutines • Eliminate nested function calls • Array access • Specify exact range get read/modified • Debugging and error handling • Aggressive strategy: ignore checking statements • Indirect array references • Discover unique relation

  22. The annotation language • Summarize opaque subroutines • Eliminate nested function calls

  23. The annotation language • Array access • Specify exact range get read/modified

  24. The annotation language • Debugging and error handling • Aggressive strategy: ignore checking statements

  25. The annotation language • Indirect array references • Discover unique relation

  26. Outline • Innovations • Problems of parallel + inline strategy • Annotation language • Annotation-based inlining technique • Experiments • Summary

  27. Annotation-based inlining • Goal • Pass annotated information to the compiler • Eliminate inlining side effects • Flow • Inline before parallelization • Reverse-inlining after parallelization • Verify and evaluate at last • Implementation • POLARIS compiler for parallelization • ROSE compiler for parsing • POET transformer • PERFECT benchmark

  28. Annotation-based inlining • Workflow • Annotation inlining⇒ Parallelization ⇒ Reverse-inlining

  29. Annotation-based inlining • Inlining annotation • Steps • Annotation ⇒ source language • Translating special operators • Inlinining generated source language • Avoiding linearization • Translating special operators • Unknown: using uninitialized global arrays • Unique: using linear expression • Avoiding linearization

  30. Annotation-based inlining • Inlining annotation

  31. Annotation-based inlining • Parallelize do-all loops

  32. Annotation-based inlining • Reverse inlining

  33. Annotation-based inlining • Reverse inlining is indispensible • Inlinining is restored to function call • Avoid lost of parallelism in caller / callee • Enable abstraction operators (unknown, unique)

  34. Annotation-based inlining • Verification and evaluation • Correctness, Efficiency, and Generality

  35. Outline • Innovations • Problems of parallel + inline strategy • Annotation language • Annotation-based inlining technique • Experiments • Summary

  36. Experiment • Purpose • What does conventional lining bring to parallelization • Gain? • Lost? • Missed? • How good is annotation-based inlining to avoid above issues • Design • PERFECT benchmarks (except SPEC77) • Two machines • 8 cores Intel Mac • 4 cores AMD Operon • End compiler • GFortran 4.2.1 • IFort 11.1 • Result • Count of Loops • Performance

  37. Experiment • Result: Loops • Conventional inlining • Having loss • Annotation-based inlining • No loss, more gain

  38. Experiment • Result: Performance • Average speedup limited • Annot-based inlining always better

  39. Summary • Inter-procedural parallelization • Summarize effects of conventional inlining • Gain • Lost • Missed • Propose annotation-based inlining • Annotation summary • Enhanced inlining strategy • Reverse inlining

  40. Thanks! Questions?

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