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Acceleration of a Feature Selection Algorithm Using High Performance Computing
(MDPI AG, 2020-09-01)
[Abstract]
Feature selection is a subfield of data analysis that is on reducing the dimensionality of datasets, so that subsequent analyses over them can be performed in affordable execution times while keeping the same ...
Power Budgeting of Big Data Applications in Container-based Clusters
(Institute of Electrical and Electronics Engineers, 2020-11-02)
[Abstract]
Energy consumption is currently highly regarded on computing systems for many reasons, such as improving the environmental impact and reducing operational costs considering the rising price of energy. Previous ...
Optimizing Coherence Traffic in Manycore Processors Using Closed-Form Caching/Home Agent Mappings
(Institute of Electrical and Electronics Engineers, 2021-02-09)
[Abstract]
Manycore processors feature a high number of general-purpose cores designed to work in a multithreaded fashion. Recent manycore processors are kept coherent using scalable distributed directories. A paramount ...
Representing Integer Sequences Using Piecewise-Affine Loops
(MDPI, 2021)
[Abstract] A formal, high-level representation of programs is typically needed for static and dynamic analyses performed by compilers. However, the source code of target applications is not always available in an analyzable ...
RGen: Data Generator for Benchmarking Big Data Workloads
(MDPI, 2021)
[Abstract] This paper presents RGen, a parallel data generator for benchmarking Big Data workloads, which integrates existing features and new functionalities in a standalone tool. The main functionalities developed in ...
Performance Optimization of a Parallel Error Correction Tool
(MDPI, 2021)
[Abstract] Due to the continuous development in the field of Next Generation Sequencing (NGS) technologies that have allowed researchers to take advantage of greater genetic samples in less time, it is a matter of relevance ...
Parallel-FST: A feature selection library for multicore clusters
(Elsevier, 2022-11)
[Abstract]: Feature selection is a subfield of machine learning focused on reducing the dimensionality of datasets by performing a computationally intensive process. This work presents Parallel-FST, a publicly available ...
PATO: genome-wide prediction of lncRNA-DNA triple helices
(Oxford University Press, 2023-03)
[Abstract]: Motivation: Long non-coding RNA (lncRNA) plays a key role in many biological processes. For instance, lncRNA regulates chromatin using different molecular mechanisms, including direct RNA-DNA hybridization via ...
A pipeline architecture for feature-based unsupervised clustering using multivariate time series from HPC jobs
(Elsevier B.V., 2023-05)
[Abstract]: Time series are key across industrial and research areas for their ability to model behaviour across time, making them ideal for a wide range of use cases such as event monitoring, trend prediction or anomaly ...
pRIblast: A highly efficient parallel application for comprehensive lncRNA–RNA interaction prediction
(Elsevier, 2023-01)
[Abstract]: Long non-coding RNAs (lncRNAs) play a key role in several biological processes and scientists are constantly trying to come up with new strategies to elucidate their functions. One common approach to characterize ...