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Parallel Implementation of BWT

Parallel Implementation of BWT. Presented By: Lalchand Gaurav Jain. Under the Guidance of : Prof . Kolin Paul. Agenda. Application Domain & objective Use of Bwt in Sequence assembly Bwt Implementation on GPU Bwt Implementation for larger Genome Comparative study. Agenda.

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Parallel Implementation of BWT

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  1. Parallel Implementation of BWT Presented By: Lalchand Gaurav Jain Under the Guidance of : Prof . Kolin Paul

  2. Agenda • Application Domain & objective • Use of Bwt in Sequence assembly • Bwt Implementation on GPU • Bwt Implementation for larger Genome • Comparative study

  3. Agenda • Application Domain & objective • Use of Bwt in Sequence assembly • Bwt Implementation on GPU • Bwt Implementation for larger Genome • Comparative study

  4. Agenda • Application Domain & objective • Use of Bwt in Sequence assembly • Bwt Implementation on GPU • Bwt Implementation for larger Genome • Comparative study

  5. Agenda • Application Domain & objective • Use of Bwt in Sequence assembly • Bwt Implementation on GPU • Bwt Implementation for larger Genome • Comparative study

  6. Agenda • Application Domain & objective • Use of Bwt in Sequence assembly • Bwt Implementation on GPU • Bwt Implementation for larger Genome • Comparative study

  7. Application Domain & Objective • Analyzing Gene expression • Mapping variations between individuals • Mapping homologous Proteins • Assembling Genome of Organism To present an efficient implementation of BWT for larger Genome.

  8. Use of Bwt in Sequence assembly Genomee Indexing BWT Algorithm Intermediate size :10^18 Assembly Process BWT : Bwt[i] = Ref(SA[i]-1) {3 GB } Suffix Array : 15GB for human genome {3 billion * 4 B + 3 GB genome} SGA Contigs

  9. Burrows-Wheeler Transform Input: A C G T A $ indices: 0 1 2 3 4 5 indices: 5 4 0 1 2 3 Output: A T $ A C G • Bwt[i] = ref [ SA[i] -1] {Bwt[i] = $ when S(i)= 0}

  10. Work Done • Implemented Bwt on GPU • Bitonic sort • Implemented Bwt for larger genome • In mutipass (GPU and CPU)

  11. Concatenations of two sub-sequences sorted in opposite directions A cyclic shift of elements Implemented by comparator networks Work in place No Communication Naturally suitable for SIMD architectures Each thread executing same code but different data O(log2n) time and O(nlog2n) work Why Bitonic ??...

  12. Bwt Procedure For larger Genome Genome 2*CHUNK Read & store (CPU) Bitonic_sort_step Calcualte Gt array Merge Suffix array (CPU) Suffix - > BWT Calcualte Gap array Suffix array (CPU)

  13. Comparison between Parallel BWT(GPU) and serial BWT (CPU) Serial Bwt : Does not work for large files

  14. Comparison between Parallel BWT (GPU) and Parallel BWT (CPU)

  15. Evaluation for larger Genome

  16. References : • Lightweight Data Indexing and Compression in External Memor • Paolo Ferragina 1, Travis Gagie2 , and Giovanni Manzini • Fast in-place sorting with CUDA based on bitonic sort :Hagen Peters • Rapid Parallel Genome Indexing with MapReduce :Rohith K. Menon • M. Burrows and D. Wheeler. A Block-Sorting Lossless Data Compression Algorithm. Technical report • Lightweight Data Indexing and Compression in External Memory :Paolo Ferragina • Parallel Lossless Data Compression on the GPU : Yao Zhang

  17. Thanks

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