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Automatic mapping of parallel applications on multicore architectures using the Servet benchmark suite
(Pergamon Press, 2012-03)
[Abstract] Servet is a suite of benchmarks focused on detecting a set of parameters with high influence on the overall performance of multicore systems. These parameters can be used for autotuning codes to increase their ...
CUDA-JMI: Acceleration of feature selection on heterogeneous systems
(Elsevier, 2020-01)
[Abstract]: Feature selection is a crucial step nowadays in machine learning and data analytics to remove irrelevant and redundant characteristics and thus to provide fast and reliable analyses. Many research works have ...
Parallel feature selection for distributed-memory clusters
(2019)
[Abstract]: Feature selection is nowadays an extremely important data mining stage in the field of machine learning due to the appearance of problems of high dimensionality. In the literature there are numerous feature ...
Fiuncho: a program for any-order epistasis detection in CPU clusters
(Springer, 2022)
[Abstract]: Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have ...
Performance Evaluation of Sparse Matrix Products in UPC
(Springer New York LLC, 2013-04)
[Abstract] Unified Parallel C (UPC) is a Partitioned Global Address Space (PGAS) language whose popularity has increased during the last years owing to its high programmability and reasonable performance through an efficient ...
SeQual: Big Data Tool to Perform Quality Control and Data Preprocessing of Large NGS Datasets
(Institute of Electrical and Electronics Engineers, 2020-08-07)
[Abstract]
This paper presents SeQual, a scalable tool to efficiently perform quality control of large genomic datasets. Our tool currently supports more than 30 different operations (e.g., filtering, trimming, formatting) ...
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 ...
Fast search of third-order epistatic interactions on CPU and GPU clusters
(Sage Publications Ltd., 2019-05-27)
[Abstract]
Genome-Wide Association Studies (GWASs), analyses that try to find a link between a given phenotype (such as a disease) and genetic markers, have been growing in popularity in the recent years. Relations between ...
ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems
(PLoS, 2018)
[Abstract]: Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, ...
A SIMD Algorithm for the Detection of Epistatic Interactions of Any Order
(Elsevier, 2022)
[Abstract] Epistasis is a phenomenon in which a phenotype outcome is determined by the interaction of genetic variation at two or more loci and it cannot be attributed to the additive combination of effects corresponding ...
