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SparkEC: speeding up alignment-based DNA error correction tools
(BioMed Central (Springer), 2022)
[Abstract]: In recent years, huge improvements have been made in the context of sequencing genomic data under what is called Next Generation Sequencing (NGS). However, the DNA reads generated by current NGS platforms are ...
SMusket: Spark-based DNA error correction on distributed-memory systems
(Elsevier B.V., 2020)
[Abstract]: Next-Generation Sequencing (NGS) technologies have revolutionized genomics research over the last decade, bringing new opportunities for scientists to perform groundbreaking biological studies. Error correction ...
Real-time resource scaling platform for Big Data workloads on serverless environments
(2020)
The serverless execution paradigm is becoming an increasingly popular option when workloads are to be deployed in an abstracted way, more specifically, without specifying any infrastructure requirements. Currently, such ...
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 ...
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 ...
ParRADMeth: Identification of Differentially Methylated Regions on Multicore Clusters
(IEEE, 2023)
[Abstract]: The discovery of Differentially Methylated (DM) regions is an important research field in biology, as it can help to anticipate the risk of suffering from specific diseases. Nevertheless, the high computational ...
SeQual-Stream: approaching stream processing to quality control of NGS datasets
(BMC, 2023-10)
[Abstract]: Background
Quality control of DNA sequences is an important data preprocessing step in many genomic analyses. However, all existing parallel tools for this purpose are based on a batch processing model, ...
CUDA acceleration of MI-based feature selection methods
(Elsevier, 2024-08)
[Abstract]: Feature selection algorithms are necessary nowadays for machine learning as they are capable of removing irrelevant and redundant information to reduce the dimensionality of the data and improve the quality of ...
FastMPJ: a scalable and efficient Java message-passing library
(Springer New York LLC, 2014)
[Abstract] The performance and scalability of communications are key for high performance computing (HPC) applications in the current multi-core era. Despite the significant benefits (e.g., productivity, portability, ...
Design and Implementation of an extended collectives library for unified Parallel C
(Springer New York LLC, 2013)
[Abstract] Unified Parallel C (UPC) is a parallel extension of ANSI C based on the Partitioned Global Address Space (PGAS) programming model, which provides a shared memory view that simplifies code development while it ...