In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

Many bioinformatics applications, such as the optimal pairwise biological sequence
comparison, demand a great quantity of computing resource, thus are excellent candidates …

The serverless computing model has been on the rise in recent years due to a lower barrier
to entry and elastic scalability. However, our experimental evidence suggests that multiple …

This paper proposes and evaluates CUDAlign 4.0, a parallel strategy to obtain the optimal
alignment of huge DNA sequences in multi-GPU platforms, using the exact Smith–Waterman …

As an optimal method for sequence alignment, the Smith-Waterman (SW) algorithm is widely
used. Unfortunately, this algorithm is computationally demanding, especially for long …

We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient
implementation of dynamic programming algorithm, for local alignment. It can be used as …

Motivation Pairwise sequence alignment is undoubtedly a central tool in many
bioinformatics analyses. In this paper, we present a generically accelerated module for …

GPUs lack fundamental support for data-dependent parallelism and synchronization. While
CUDA Dynamic Parallelism signals progress in this direction, many limitations and …

Computing edit distance for very long strings has been hampered by quadratic time
complexity with respect to string length. The WFA algorithm reduces the time complexity to a …

Multiple sequence alignment (MSA) constitutes an extremely powerful tool for many
biological applications including phylogenetic tree estimation, secondary structure …