Hanif, Muhammad KashifMuhammad KashifHanifZimmermann, Karl-HeinzKarl-HeinzZimmermann2019-09-302019-09-302017-05-19Computing 11 (99): 1105-1123 (2017)http://hdl.handle.net/11420/3466Viterbi algorithm is used in different scientific applications including biological sequence alignment, speech recognition, and probabilistic inference. However, high computational complexity of the Viterbi algorithm is a major concern. Accelerating the Viterbi algorithm is important, especially when the number of states or the length of the sequences increase significantly. In this paper, a parallel solution to improve the performance of Viterbi algorithm is presented. This is achieved by formulating a matrix product based algorithm. This algorithm has been mapped to a NVIDIA graphics processing unit. The performance for different parameters and realizations are compared. The results depicts matrix product is not a viable option for small number of states. However, matrix product solution using shared memory for large number of states gains good performance when compared with the serial version.en1436-505720171111051123SpringerCUDAGraphics processing unitHidden Markov modelMatrix productViterbi algorithmHandel, Kommunikation, VerkehrTechnikJournal Article10.1007/s00607-017-0557-6Other