Listar1. Investigación por tema "Multithreading"
Mostrando ítems 1-6 de 6
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Accelerating binary biclustering on platforms with CUDA-enabled GPUs
(Elsevier Ltd, 2018)[Abstract]: Data mining is nowadays essential in many scientific fields to extract valuable information from large input datasets and transform it into an understandable structure. For instance, biclustering techniques are ... -
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 ... -
Easy Dataflow Programming in Clusters with UPC++ DepSpawn
(Institute of Electrical and Electronics Engineers, 2019-06-01)[Abstract]: The Partitioned Global Address Space (PGAS) programming model is one of the most relevant proposals to improve the ability of developers to exploit distributed memory systems. However, despite its important ... -
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 ... -
Multithreaded and Spark parallelization of feature selection filters
(2016)[Abstract]: Vast amounts of data are generated every day, constituting a volume that is challenging to analyze. Techniques such as feature selection are advisable when tackling large datasets. Among the tools that provide ... -
NPB-MPJ: NAS Parallel Benchmarks Implementation for Message-Passing in Java
(IEEE Computer Society, 2009-05-08)[Abstract] Java is a valuable and emerging alternative for the development of parallel applications, thanks to the availability of several Java message-passing libraries and its full multithreading support. The combination ...