A GPU based implementation of Needleman-Wunsch algorithm using skewing transformation

We present a new parallel approach of Needleman-Wunsch algorithm for global sequence alignment. This approach uses skewing transformation for traversal and calculation of the dynamic programming matrix. We compare the execution time of sequential CPU based implementation with two parallel GPU based implementations: Single-kernel invocation with lock-free block synchronization and multi-kernel invocation at block-synchronization points. Both the GPU based implementations gave upto 6 times performance improvement over the sequential CPU based implementation.