This chapter explores the process of defining and optimizing a relatively simple matching algorithm in CUDA. The project was designed to be a tool to explore the process of developing algorithms from start to finish with CUDA in mind; it also intended to highlight some of the differences between development in a massively parallel GPU-based architecture and a more traditional CPU-based single- or multi
With the rise of Next-Generation Sequencing (NGS), clinical sequencing services have become more acc...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has ...
Massively parallel DNA sequencing technologies have revolutionized genomics and molecular biology by...
In recent decades, mapping of a variety of species' genomes has taken place. With the proliferation ...
Abstract. This paper deals with the mapping of the parallel island-based genetic algorithm with unid...
Genetic Algorithms(GAs) are suitable for parallel computing since population members fitness maybe e...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
problems of biological science. One of the most useful applications of bioinformatics is sequence an...
Graphics processor a b s t r a c t Finding regions of similarity between two very long data streams ...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
Abstract — The m a i n a i m of string matching algorithm is to locate the appearance of a specific ...
Pattern discovery is one of the fundamental tasks in bioinformatics and pattern recognition is a pow...
The next-generation sequencing instruments enable biological researchers to generate voluminous amou...
Abstract—Many general-purpose applications exploit Graphics Processing Units (GPUs) by executing a s...
With the rise of Next-Generation Sequencing (NGS), clinical sequencing services have become more acc...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has ...
Massively parallel DNA sequencing technologies have revolutionized genomics and molecular biology by...
In recent decades, mapping of a variety of species' genomes has taken place. With the proliferation ...
Abstract. This paper deals with the mapping of the parallel island-based genetic algorithm with unid...
Genetic Algorithms(GAs) are suitable for parallel computing since population members fitness maybe e...
We present a multi-purpose genetic algorithm, designed and implemented with GPGPU / CUDA parallel co...
problems of biological science. One of the most useful applications of bioinformatics is sequence an...
Graphics processor a b s t r a c t Finding regions of similarity between two very long data streams ...
Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. GAs is one of...
Abstract — The m a i n a i m of string matching algorithm is to locate the appearance of a specific ...
Pattern discovery is one of the fundamental tasks in bioinformatics and pattern recognition is a pow...
The next-generation sequencing instruments enable biological researchers to generate voluminous amou...
Abstract—Many general-purpose applications exploit Graphics Processing Units (GPUs) by executing a s...
With the rise of Next-Generation Sequencing (NGS), clinical sequencing services have become more acc...
Abstract — Nowadays, multicore processor and GPUs have entered the mainstream of microprocessor dev...
The idea of using a graphics processing unit (GPU) for more than simply graphic output purposes has ...
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