12 papers · ranked by Valyu relevance
Cristian Peñaranda, Carlos Reaño, Federico Silla, David Plets
GPUs are commonly used to accelerate the execution of applications in domains such as deep learning. Deep learning applications are applied to an increasing variety of scenarios, with edge computing being one of them. However, edge devices present severe computing power and energy limitations. In this context, the use…
Jaroslav Budiš, Werner Krampl, Marcel Kucharík, Rastislav Hekel + 12 more
'Adrián Goga' 'Jozef Sitarčík' 'Michal Lichvár' 'Dávid Smol’ak' 'Miroslav Böhmer' 'Andrej Baláž' 'František Ďuriš' 'Juraj Gazdarica' 'Katarína Šoltys' 'Ján Turňa' 'Ján Radvánszky' 'Tomáš Szemes'] Title: Abstract With the rapid growth of massively parallel sequencing technologies, still more laboratories are utilising…
Marek Sztuka, Krzysztof Kotlarz, Magda Mielczarek, Piotr Hajduk + 2 more
'Jakub Liu' 'Joanna Szyda'] Title: Abstract This study compared computational approaches to parallelization of an SNP calling workflow. The data comprised DNA from five Holstein-Friesian cows sequenced with the Illumina platform. The pipeline consisted of quality control, alignment to the reference genome…
Ashish Chapagain, Dima Abuoliem, In Ho Cho, Tongbiao Wang
Multifunctional nanosurfaces receive growing attention due to their versatile properties. Capillary force lithography (CFL) has emerged as a simple and economical method for fabricating these surfaces. In recent works, the authors proposed to leverage the evolution strategies (ES) to modify nanosurface characteristics…
Zeyu Xia, Canqun Yang, Chenchen Peng, Yifei Guo + 3 more
'Tao Tang' 'Yingbo Cui'] Background The advent of Single Molecule Real-Time (SMRT) sequencing has overcome many limitations of second-generation sequencing, such as limited read lengths, PCR amplification biases. However, longer reads increase data volume exponentially and high error rates make many existing alignment…
Paul Cardosi, Bérenger Bramas, Bilal Alatas
Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow efficient parallelization across distributed…
Vladislav Skorpil, Vaclav Oujezsky, Arcangelo Castiglione, Gianni D’Angelo
'Gianni D’Angelo'] This paper presents an implementation of the parallelization of genetic algorithms. Three models of parallelized genetic algorithms are presented, namely the Master-Slave genetic algorithm, the Coarse-Grained genetic algorithm, and the Fine-Grained genetic algorithm. Furthermore, these models are…
Károly Bósa, Paul Heinzlreiter
Background Data preparation is a fundamental aspect of data engineering, a prerequisite for later tasks such as data visualization, reporting, and training machine learning models. Despite the recurring patterns in data transformation processes, the specific steps often vary depending on the project context, data…
Zongli Xu, Liang Niu, Jack A. Taylor
Background Illumina DNA methylation arrays are high-throughput platforms for cost-effective genome-wide profiling of individual CpGs. Experimental and technical factors introduce appreciable measurement variation, some of which can be mitigated by careful “preprocessing” of raw data. Methods Here we describe the ENmix…
Sirilak Ketchaya, Apisit Rattanatranurak
Quicksort is an important algorithm that uses the divide and conquer concept, and it can be run to solve any problem. The performance of the algorithm can be improved by implementing this algorithm in parallel. In this paper, the parallel sorting algorithm named the Multi-Deque Partition Dual-Deque Merge Sorting…
Tianye Zhai, Hong Gu, Anika Holton, Elanor Chang + 4 more
Functional magnetic resonance imaging (fMRI) is a powerful tool for probing neuronal activity in vivo, but fMRI data are inherently noisy. To mitigate this, a wide range of denoising strategies have been developed, including volume censoring, anatomical component-based noise correction (aCompCor), ICA-based methods…
Raúl Miñón, Josu Diaz-de-Arcaya, Ana I. Torre-Bastida, Juan López-de-Armentia + 4 more
'Juan López-de-Armentia' 'Gorka Zarate' 'Lander Bonilla' 'Asier Garcia-Perez' 'Jon Aguirre-Usandizaga'] Machine learning is already integrated in diverse domains enhancing their performance and decision support. For laboratories, this approach is normally sufficient. However, in real environments, these models can not…