The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. However, SW is expensive in terms of both execution time and memory usage, which makes it impractical in many applications. Some heuristics are possible but at the expense of losing sensitivity. Fortunately, previous research have shown that new computing platforms such as GPUs and FPGAs are able to accelerate SW and achieve impressive speedups. In this paper we have explored SW acceleration on a heterogeneous platform equipped with an Intel Xeon Phi coprocessor. Our evaluation, using the well-known Swiss-Prot database as a benchmark, has shown that a hybrid CPU-Phi heterogeneous system is able to achieve competitive performance (62.6 GCUPS), eve...
Abstract—The Smith-Waterman algorithm is a dynamic programming method for determining optimal local ...
The well-known Smith–Waterman (SW) algorithm is the most commonly used method for local sequence ali...
With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the sci...
Alignment is essential in many areas such as biological, chemical and criminal forensics. The well‐k...
Bioinformatics is one of the areas affected by current HPC problems due to the exponential growth of...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Unfo...
Trabajo presentado en el VIII Jornadas de Divulgación de la Investigación en Biología Molecular, Cel...
Abstract: Efficient sequence alignment is one of the most important and challenging activities in bi...
The Smith-Waterman algorithm is a dynamic programming method for determining op-timal local alignmen...
Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. Th...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
The Smith-Waterman algorithm is a common localsequence alignment method which gives a high accuracy....
We present a novel hardware implementation of the double affine Smith-Waterman (DASW) algorithm, whi...
Abstract Background To infer homology and subsequentl...
Abstract—The Smith-Waterman algorithm is a dynamic programming method for determining optimal local ...
The well-known Smith–Waterman (SW) algorithm is the most commonly used method for local sequence ali...
With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the sci...
Alignment is essential in many areas such as biological, chemical and criminal forensics. The well‐k...
Bioinformatics is one of the areas affected by current HPC problems due to the exponential growth of...
The well-known Smith-Waterman (SW) algorithm is a high-sensitivity method for local alignments. Unfo...
Trabajo presentado en el VIII Jornadas de Divulgación de la Investigación en Biología Molecular, Cel...
Abstract: Efficient sequence alignment is one of the most important and challenging activities in bi...
The Smith-Waterman algorithm is a dynamic programming method for determining op-timal local alignmen...
Summary Alignment is essential in many areas such as biological, chemical and criminal forensics. Th...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
Background: The Smith-Waterman (SW) algorithm is the best choice for searching similar regions betwe...
The Smith-Waterman algorithm is a common localsequence alignment method which gives a high accuracy....
We present a novel hardware implementation of the double affine Smith-Waterman (DASW) algorithm, whi...
Abstract Background To infer homology and subsequentl...
Abstract—The Smith-Waterman algorithm is a dynamic programming method for determining optimal local ...
The well-known Smith–Waterman (SW) algorithm is the most commonly used method for local sequence ali...
With the greater importance of parallel architectures such as GPUs or Xeon Phi accelerators, the sci...