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Optimization of Real-World MapReduce Applications With Flame-MR: Practical Use Cases
(Institute of Electrical and Electronics Engineers, 2018-11-12)
[Abstract] Apache Hadoop is a widely used MapReduce framework for storing and processing large amounts of data. However, it presents some performance issues that hinder its utilization in many practical use cases. Although ...
Big Data-Oriented PaaS Architecture with Disk-as-a-Resource Capability and Container-Based Virtualization
(Springer Netherlands, 2018-12)
[Abstract] With the increasing adoption of Big Data technologies as basic tools for the ongoing Digital Transformation, there is a high demand for data-intensive applications. In order to efficiently execute such applications, ...
BDEv 3.0: energy efficiency and microarchitectural characterization of Big Data processing frameworks
(Elsevier BV * North-Holland, 2018-09)
[Abstract] As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks becomes a crucial task in order to identify potential performance bottlenecks that may delay the processing of large ...
BDWatchdog: real-time monitoring and profiling of Big Data applications and frameworks
(Elsevier BV * North-Holland, 2018-10)
[Abstract] Current Big Data applications are characterized by a heavy use of system resources (e.g., CPU, disk) generally distributed across a cluster. To effectively improve their performance there is a critical need for ...
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, ...
Solving Large Problem Sizes of Index-Digit Algorithms on GPU: FFT and Tridiagonal System Solvers
(Institute of Electrical and Electronics Engineers, 2018)
[Abstract] Current Graphics Processing Units (GPUs) are capable of obtaining high computational performance in scientific applications. Nevertheless, programmers have to use suitable parallel algorithms for these architectures ...
Multimethod optimization in the cloud: A case‐study in systems biology modelling
(Wiley, 2018-06-25)
[Abstract] Optimization problems appear in many different applications in science and engineering. A large number of different algorithms have been proposed for solving them; however, there is no unique general optimization ...
Enhancing in-memory Efficiency for MapReduce-based Data Processing
(Academic Press, 2018-10)
[Abstract] As the memory capacity of computational systems increases, the in-memory data management of Big Data processing frameworks becomes more crucial for performance. This paper analyzes and improves the memory ...
Robust step counting for inertial navigation with mobile phones
(MDPI AG, 2018-09-19)
[Abstract]: Mobile phones are increasingly used for purposes that have nothing to do with phone calls or simple data transfers, and one such use is indoor inertial navigation. Nevertheless, the development of a standalone ...
Implementing cloud-based parallel metaheuristics: an overview
(Universidad Nacional de la Plata - Facultad de Informatica, 2018-12-12)
[Abstract]
Metaheuristics are among the most popular methods for solving hard global optimization problems in many areas of science and engineering. Their parallel im- plementation applying HPC techniques is a common ...