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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 ...
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 ...
Serverless-like platform for container-based YARN clusters
(Elsevier, 2024-06)
[Abstract]: Serverless computing is an emerging paradigm that has gained a lot of relevance in recent years, as it allows users to consume computing resources without worrying about the underlying infrastructure and pay ...
Performance Evaluation of Big Data Frameworks for Large-Scale Data Analytics
(IEEE Computer Society, 2017-02-06)
[Abstract] The increasing adoption of Big Data analytics has led to a high demand for efficient technologies in order to manage and process large datasets. Popular MapReduce frameworks such as Hadoop are being replaced by ...
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 ...
Accelerating the quality control of genetic sequences through stream processing
(Association for Computing Machinery, 2023)
[Abstract]: 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, needing to have ...
Evaluation of Java for General Purpose GPU Computing
(IEEE Computer Society, 2013-07-01)
[Abstract] The presence of many-core units as accelerators has been increasing due to their ability to improve the performance of highly parallel workloads. General Purpose GPU(GPGPU) computing has allowed the graphical ...
Analysis and evaluation of MapReduce solutions on an HPC cluster
(Pergamon Press, 2016-02)
[Abstract] The ever growing needs of Big Data applications are demanding challenging capabilities which cannot be handled easily by traditional systems, and thus more and more organizations are adopting High Performance ...
Automated Approach for Accurate CPU Power Modelling
(IEEE, 2024)
[Abstract]: Power supply is a limiting factor when increasing the computing capacity of supercomputers. As a consequence, power consumption has become one of the biggest challenges in the field of High Performance Computing ...
MREv: An Automatic MapReduce Evaluation Tool for Big Data Workloads
(Elsevier, 2015)
[Abstract]: The popularity of Big Data computing models like MapReduce has caused the emergence of many frameworks oriented to High Performance Computing (HPC) systems. The suitability of each one to a particular use case ...
