1<br />Is it an open door to<br />common parallelization strategy <br />for topological operators on multi-core multi-thre...
2<br />Summary<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – ...
3<br />Summary<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – ...
4<br />General framework<br />1. Scientific and technical context (1)<br />Image processingoperators<br />Fourier<br />Tra...
5<br />General framework<br />1. Scientific and technical context (2)<br />(Associated class) Vs (Parallelizationstrategie...
6<br />General framework<br />2. Ph. D. objectives (1)<br />Topological operators<br />Thinning operator [1]<br />common<b...
7<br />General framework<br />2. Ph. D. objectives (2)<br />Main Architectural Classes <br />SISD machines<br />SIMD machi...
8<br />General framework<br />2. Ph. D. objectives (3)<br />Needs<br />Common  parallelization strategy of topological ope...
9<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laborato...
10<br />Parallel thinning operator<br />1. Theoretical background<br />Filtered thinning method that allows to selectively...
11<br />Parallel thinning operator<br />1. Parallelization strategy (1)<br />Definesearch area<br />Startparallelcharacter...
12<br />Parallel thinning operator<br />1. Parallelization strategy (2)<br />SDM-Strategy<br />(Divide and conquer princip...
13<br />Parallel thinning operator<br />1. Parallelization strategy (3)<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
14<br />Parallel thinning operator<br />2. Coordination of threads (1)<br />Thread 1<br />Thread 2<br />First implementati...
15<br />Parallel thinning operator<br />2. Coordination of threads (2)<br />Thread 1<br />Thread 2<br />Lock() and access ...
16<br />Parallel thinning operator<br />3. Performance testing (1)<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
17<br />Parallel thinning operator<br />3. Performance testing (2)<br />First implementation using a lock-based shared FIF...
18<br />Parallel thinning operator<br />3. Performance testing (3)<br />Second implementation using a private-shared concu...
19<br />Parallel thinning operator<br />4. Conclusion<br />Non-specific nature of the proposed <br />parallelization strat...
20<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laborat...
21<br />Future work<br />1. Extension<br />SDM - Strategy<br />Performance enhancement (speed up)<br />Efficiency (work di...
22<br />Future work<br />2. New parallel topological watershed<br />% Achievement<br />Parallelwatershed Operator<br />SDM...
23<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laborat...
24<br />Discussion<br />Introduce future programming model<br /> (make it easy to write programs that execute efficiently ...
25<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
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parallelization strategy

  1. 1. 1<br />Is it an open door to<br />common parallelization strategy <br />for topological operators on multi-core multi-thread architecture ?<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  2. 2. 2<br />Summary<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  3. 3. 3<br />Summary<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  4. 4. 4<br />General framework<br />1. Scientific and technical context (1)<br />Image processingoperators<br />Fourier<br />Transformation<br />Opening<br />Thinning<br />Dynamic <br />redistribution<br />Linear filters<br />Closing<br />Crest restoring<br />Not-linear <br />filters <br />Euclidean <br />Distance<br />Transformation<br />Thresholding<br />Smoothing<br />Attributed<br />Filter<br />Watershed <br />Associated class<br />Topological <br />operators<br />Morphological <br />operators<br />Local <br />operators<br />Point-to-Point <br />operators<br />Global<br />operators<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  5. 5. 5<br />General framework<br />1. Scientific and technical context (2)<br />(Associated class) Vs (Parallelizationstrategies)<br />Global<br />operators<br />Topological <br />operators<br />Morphological <br />operators<br />Local <br />operators<br />Point-to-Point <br />operators<br />Sienstra [1]<br />(2002)<br />Wilkinson [2]<br />(2007)<br />Meijster [3]<br />[1] F. J. Seinstra, D. Koelma, and J. M. Geusebroek, “A software architecture for user transparent parallel image processing”.<br />[2] M.H.F. Wilkinson, H. Gao, W.H. Hesselink, “Concurrent Computation of Attribute Filters on Shared Memory Parallel Machines”.<br />[3] A. Meijster, J. B. T. M. Roerdink, and W. H. Hesselink, “A general algorithm for computing distance transforms in linear time” .<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  6. 6. 6<br />General framework<br />2. Ph. D. objectives (1)<br />Topological operators<br />Thinning operator [1]<br />common<br />parallelization<br />strategy<br />Crest restoring [1]<br />2D and 3D smoothing [2]<br />Watershed based on w-thinning [3]<br />Watershed based on graph [4]<br />Homotopic kernel transformation [5]<br />Leveling kernel transformation [5]<br />[1] M. Couprie, F. N. Bezerra, and G. Bertrand, “Topological operators for grayscale image processing”, <br />[2] M. Couprie, and G. Bertrand, “Topology preserving alternating sequential filter for smoothing 2D and 3D objects”.<br />[3] G. Bertrand, “On Topological Watersheds”.  <br />[4] J. Cousty, M. Couprie, L. Najman and G. Betrand “Weighted fusion graphs: Merging properties and watersheds”.<br />[5] G. Bertrand, J. C. Everat, and M. Couprie, &quot;Image segmentation through operators based on topology“ <br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  7. 7. 7<br />General framework<br />2. Ph. D. objectives (2)<br />Main Architectural Classes <br />SISD machines<br />SIMD machines<br />MISD machines<br />MIMD Machine :<br />(Execute several instruction streams in parallel on different data)<br />Shared Memory Machine<br />Distributed <br />Memory <br />System<br />CPU1<br />CPU2<br />CPU3<br />CPUn<br />Random Access Memory <br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  8. 8. 8<br />General framework<br />2. Ph. D. objectives (3)<br />Needs<br />Common parallelization strategy of topological operators on multi-core multithread architecture (MIMD Machines – Shared Memory System)?<br />Main Objectives<br />Unifyingparallelizationmethod of topologicaloperators class (Algorithmiclevel)<br />Implementation Methodology and optimization techniques on multi-core multithread <br /> architecture (Architecture level).<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  9. 9. 9<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  10. 10. 10<br />Parallel thinning operator<br />1. Theoretical background<br />Filtered thinning method that allows to selectively simplify the topology, based on a<br /> local contrast parameter λ.<br />(b) filtered skeleton <br /> with λ = 10.<br />(a) After Deriche <br />gradient operator<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  11. 11. 11<br />Parallel thinning operator<br />1. Parallelization strategy (1)<br />Definesearch area<br />Startparallelcharacterization <br />Create new shared data structure<br />End parallelcharacterization <br />Mergemodifiedsearch area<br />Restart process until stability<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  12. 12. 12<br />Parallel thinning operator<br />1. Parallelization strategy (2)<br />SDM-Strategy<br />(Divide and conquer principle)<br />Up level<br />DATA PARALLELISM<br />MIXED<br />PARALLELISM<br />Down level<br />THREAD PARALLELISM<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  13. 13. 13<br />Parallel thinning operator<br />1. Parallelization strategy (3)<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  14. 14. 14<br />Parallel thinning operator<br />2. Coordination of threads (1)<br />Thread 1<br />Thread 2<br />First implementation using a lock-based shared FIFO queue.<br />Lock()<br />Unlock()<br />Push()<br />Fail<br />Success<br />Blocked<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  15. 15. 15<br />Parallel thinning operator<br />2. Coordination of threads (2)<br />Thread 1<br />Thread 2<br />Lock() and access semaphore<br />Unlock() and leave semaphore<br />Semaphore<br />Push()<br />Second implementation using a private-shared concurrent FIFO queue<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  16. 16. 16<br />Parallel thinning operator<br />3. Performance testing (1)<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  17. 17. 17<br />Parallel thinning operator<br />3. Performance testing (2)<br />First implementation using a lock-based shared FIFO queue.<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  18. 18. 18<br />Parallel thinning operator<br />3. Performance testing (3)<br />Second implementation using a private-shared concurrent FIFO queue<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  19. 19. 19<br />Parallel thinning operator<br />4. Conclusion<br />Non-specific nature of the proposed <br />parallelization strategy.<br />Threads coordination and communication <br />during computing dependently parallel read/write<br /> for managing cache-resident data <br />1<br />2<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  20. 20. 20<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  21. 21. 21<br />Future work<br />1. Extension<br />SDM - Strategy<br />Performance enhancement (speed up)<br />Efficiency (work distribution)<br />Cache miss<br />ParallelThinning Operator<br />IMBRICATE <br />TWO<br />Operators<br />Crest restoring <br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  22. 22. 22<br />Future work<br />2. New parallel topological watershed<br />% Achievement<br />Parallelwatershed Operator<br />SDM - Strategy<br />Performance enhancement (speed up)<br />Efficiency (work distribution)<br />Cache miss<br />80%<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  23. 23. 23<br />General framework<br />Parallel thinning operator<br />Future work<br />Discussion<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  24. 24. 24<br />Discussion<br />Introduce future programming model<br /> (make it easy to write programs that execute efficiently on highly parallel C.S)<br />Introduce new “Draft”to design and evaluate parallel programming models <br />(instead of old benchmark)<br />Maximize programmer productivity, future programming model must be more human-centric<br />(than the conventional focus on hardware or application)<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />
  25. 25. 25<br />R. MAHMOUDI – A3SI Laboratory– 2009 April<br />

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