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Collaboration of Parafrase-2 and NaraView for Effective Parallelization Supports

Collaboration of Parafrase-2 and NaraView for Effective Parallelization Supports. Background. According to parallelizing compiler development, necessity of parallelization support tools increases. We developed NaraView that visualizes program

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Collaboration of Parafrase-2 and NaraView for Effective Parallelization Supports

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  1. Collaboration of Parafrase-2 and NaraView for Effective Parallelization Supports

  2. Background According to parallelizing compiler development, necessity of parallelization support tools increases. We developed NaraView that visualizes program information as a parallelization support tool. Purpose Validation of NaraView as a parallelization support tool

  3. Contents 1. NaraView 2. Validation Method 3. Result of Parallelization 4. Validation 5. Conclusion

  4. 1. NaraView Visualize internal representations of parallelizing compiler Parafrase-2 4 Types of View 1. Program Structure View 2. Source Code View 3. Hierarchical CFG View 4. Data Dependence View They provide interactive parallelization between users and a compiler

  5. Parafrase-2 Parafrase-2 is a parallelizing compiler that was developed in University of Illinois. Passfile: It specifies program analysis and optimization in the file Program Parafrase-2 Parallelized Program User’s strategy decides execution efficiency

  6. Program Structure View Loop Condition Expression Expression (concurrent)

  7. Data Dependence View write access read access write & read access data dependence

  8. 2. Method of Validation Parallelize a real application with Parafrase-2 and NaraView in 3 distinguished ways Application Program Extended Huckel calculation program 3 Ways of Parallelization 1. Use only default passfile 2. Use a modified passfile 3. Use a modified passfile and hand optimize Finally, compare three results and validate them

  9. Extended Huckel calculation program Optimize molecular geometry parameters. It consists of 8 subroutines. clean.f sortds.f sortdk.f matrix.f matpr.f smplhk.f srtvdd.f hoqrv2.f Simple calculation Main calculation

  10. 3. Result of Parallelization Case1: Use only default passfile Result (Program Structure View) Some non-parallelized loops remain

  11. To Eliminate Data Dependence Add adequate code transformations into default passfile Code Transformation: modify internal representations to optimize program execution time How to decide adequate code transformations? Observe data dependencies in the program in detail Program structure view & data dependence view of NaraView are useful to observe them

  12. Case2: Use a modified passfile Example (line-13) DO 10 j= k + 1, n 13 w (j,1) = 0.d0 14 e (j) = a (k,j) 15 10 s = e (j) * e (j) + s 16 non-parallelized loop (program structure view) Observe data dependence view corresponding this loop to parallelize

  13. e w a s Loop Distribution Scalar Expansion Add the two transformations into default passfile

  14. Result of Case2 Program Structure View Two more loops are parallelized

  15. Case3: Use a Modified Passfile and Hand Optimize Example (line-21) DO 347 j = k + 1,n 21 e(j) = a(k,j) 22 cptmp_346(j) = e(j) * e(j) 1 +cptmp_346(j-1) 23 347CONTINUE 24 Display corresponding data dependence view

  16. DO 347 j = k + 1,n 21 e(j) = a(k,j) 22 cptmp_346(j) = e(j) * e(j) 1 +cptmp_346(j-1) 23 347CONTINUE 24 DO 347 j = k + 1,n 22 e(j) = a(k,j) 23 347 CONTINUE 24 DO 390 j = k + 1,n2 25 cptmp_346(j) = e(j) * e(j) 1 + cptmp_346(j - 1) 26 390 CONTINUE 27 Example of Modification (line-21) After the modification, Parafrase-2 can parallelize this loop.

  17. Result of Case3 Program Structure View

  18. 4. Validation Parallelization process at line-13 Case1 Case2 Case3 Effectiveness of each method The Number of Loop Iterations

  19. 5. Conclusion Effectiveness of visualized program information is indicated by these results Future Work It is difficult to decide adequate transformation for parallelization. Propose candidates of transformation Select one from them with visualized program information

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