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The New UPC++ DepSpawn High Performance Library for Data-Flow Computing with Hybrid Parallelism
(Springer, 2022)
[Abstract] Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit ...
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 ...
Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
(Elsevier, 2022)
[Abstract] Deep Learning approaches have brought solutions, with impressive performance, to general classification problems where wealthy of annotated data are provided for training. In contrast, less progress has been ...
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 ...
Optimizing parcel exchange among landowners: A soft alternative to land consolidation
(Elsevier, 2020-01)
[Abstract]: For decades, public policy has favored the use of land consolidation to reduce the fragmentation of land ownership. Private actors, on the other hand, have focused on the purchase, rental and exchange of land ...
Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy
(Oxford University Press, 2023)
[Abstract]: Due to the increasingly large amount of data acquired into point clouds, from LiDAR (Light Detection and Ranging) sensors and 2D/3D sensors, massive point clouds processing has become a topic with high interest ...
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 ...
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 ...
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 ...