GenDP: A Framework of Dynamic Programming Acceleration for Genome Sequencing Analysis. - Gu, Yufeng; Subramaniyan, Arun; Dunn, Tim; Khadem, Alireza; Chen, Kuan-Yu; Paul, Somnath; Vasimuddin, Mohammad; Misra, Sanchit; Blaauw, David; Narayanasamy, Satish; Das, Reetuparna (Communications of the ACM, 2025)
The article proposes GenDP, a framework of dynamic programming acceleration for genome sequencing analysis. The authors evaluate GenDP on four dynamic programming (DP) kernels including Banded Smith-Waterman (BSW), Chain, Pairwise Hidden Markov Model (PairHMM), and Partial Order Alignment (POA). The design of the DPAx accelerator is discussed and the graph-partitioning algorithm known as DPMap is also described.