Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources
W Kurtz, A Lapin, OS Schilling, Q Tang… - … modelling & software, 2017 - Elsevier
Online data acquisition, data assimilation and integrated hydrological modelling have
become more and more important in hydrological science. In this study, we explore cloud …
become more and more important in hydrological science. In this study, we explore cloud …
Toward high-performance computing and big data analytics convergence: The case of spark-diy
Convergence between high-performance computing (HPC) and big data analytics (BDA) is
currently an established research area that has spawned new opportunities for unifying the …
currently an established research area that has spawned new opportunities for unifying the …
Spark-diy: A framework for interoperable spark operations with high performance block-based data models
Today's scientific applications are increasingly relying on a variety of data sources, storage
facilities, and computing infrastructures, and there is a growing demand for data analysis …
facilities, and computing infrastructures, and there is a growing demand for data analysis …
Accelerated iterative image reconstruction for cone-beam computed tomography through Big Data frameworks
One of the latest trends in Computed Tomography (CT) is the reduction of the radiation dose
delivered to patients through the decrease of the amount of acquired data. This reduction …
delivered to patients through the decrease of the amount of acquired data. This reduction …
Data-aware support for hybrid HPC and big data applications
S Caíno-Lores, F Isaila… - 2017 17th IEEE/ACM …, 2017 - ieeexplore.ieee.org
Nowadays there is a raising interest in bridging the gap between Big Data application
models and data-intensive HPC. This work explores the effects that Big Data-inspired …
models and data-intensive HPC. This work explores the effects that Big Data-inspired …
[PDF][PDF] (2020). Applying big data paradigms to a large scale scientific workflow: Lessons learned and future directions. Future Generation Computer Systems, 110, pp …
S Caíno-Lores, A Lapin, J Carretero, P Kropf - 2020 - e-archivo.uc3m.es
The increasing amounts of data related to the execution of scientific workflows has raised
awareness of their shift towards parallel data-intensive problems. In this paper, we deliver …
awareness of their shift towards parallel data-intensive problems. In this paper, we deliver …
[PDF][PDF] Abella, M.(2020). Accelerated iterative image reconstruction for cone-beam computed tomography through Big Data frameworkse. Future Generation Computer …
One of the latest trends in Computed Tomography (CT) is the reduction of the radiation dose
delivered to patients through the decrease of the amount of acquired data. This reduction …
delivered to patients through the decrease of the amount of acquired data. This reduction …
[HTML][HTML] On the convergence of big data analytics and high-performance computing: a novel approach for runtime interoperability
SC Lores - 2019 - documat.unirioja.es
The information technology ecosystem is currently in transition to a new generation of
applications requiring intensive data acquisition, processing and storage. As a result of this …
applications requiring intensive data acquisition, processing and storage. As a result of this …
[PDF][PDF] T. Peterka," Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models," 2018 IEEE/ACM 5th
Today's scientific applications are increasingly relying on a variety of data sources, storage
facilities, and computing infrastructures, and there is a growing demand for data analysis …
facilities, and computing infrastructures, and there is a growing demand for data analysis …
[引用][C] Report on techniques for data management on integrated HPC and Big Data platforms
GA de Computadores - 2018