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Title: Pairwise Sequence Alignment Library

Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.
Publication Date:
OSTI Identifier:
Report Number(s):
ATPER; 003435MLTPL00
Battelle IPID 30770-E
DOE Contract Number:
Software Revision:
Software Package Number:
Software Package Contents:
Open Source Software package available from Pacific Northwest National Laboratory at the following URL:
Software CPU:
Open Source:
Source Code Available:
Other Software Info:
Open Source - BSD
Research Org:
Pacific Northwest National Laboratory
Sponsoring Org:
United States Department of Energy
Country of Publication:
United States

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