Browsing by Subject "Big data"

Now showing items 1-20 of 298

    • A city of cities: Measuring how 15-minutes urban accessibility shapes human mobility in Barcelona 

      Graells Garrido, Eduardo; Serra Burriel, Feliu; Rowe, Francisco; Cucchietti, Fernando; Reyes Valenzuela, Patricio Alejandro (Public Library of Science (PLOS), 2021-05-05)
      Article
      Open Access
      As cities expand, human mobility has become a central focus of urban planning and policy making to make cities more inclusive and sustainable. Initiatives such as the “15-minutes city” have been put in place to shift the ...

    • A compromise archive platform for monitoring infrastructures 

      García Calatrava, Carlos; Cucchietti, Fernando; Becerra Fontal, Yolanda (Barcelona Supercomputing Center, 2020-05)
      Conference report
      Open Access
      The great advancement in the technological field has led to an explosion in the amount of generated data. Many different sectors have understood the opportunity that acquiring, storing, and analyzing further information ...

    • A cost-based storage format selector for materialized results in big data frameworks 

      Munir, Rana Faisal; Abelló Gamazo, Alberto; Romero Moral, Óscar; Thiele, Maik; Lehner, Wolfgang (2019-05-08)
      Article
      Open Access
      Modern big data frameworks (such as Hadoop and Spark) allow multiple users to do large-scale analysis simultaneously, by deploying data-intensive workflows (DIWs). These DIWs of different users share many common tasks (i.e, ...

    • A general guide to applying machine learning to computer architecture 

      Nemirovsky, Daniel; Arkose, Tugberk; Markovic, Nikola; Nemirovsky, Mario; Unsal, Osman Sabri; Cristal Kestelman, Adrián; Valero Cortés, Mateo (2018)
      Article
      Open Access
      The resurgence of machine learning since the late 1990s has been enabled by significant advances in computing performance and the growth of big data. The ability of these algorithms to detect complex patterns in data which ...

    • A methodology for Spark parameter tuning 

      Gounaris, Anastasios; Torres Viñals, Jordi (2017-05-19)
      Article
      Open Access
      Spark has been established as an attractive platform for big data analysis, since it manages to hide most of the complexities related to parallelism, fault tolerance and cluster setting from developers. However, this comes ...

    • A new reliability-based data-driven approach to simulation-based models 

      Ayensa Jiménez, Jacobo; Doweidar, Mohamed Hamdy; Doblaré Castellano, Manuel (Barcelona Supercomputing Center, 2017-05-04)
      Conference report
      Open Access
      Data Science has burst into simulation-based en-gineering sciences with an impressive impulse. However, data are never uncertainty-free and a suitable approach is needed to face data measurement errors and their intrinsic ...

    • A New role of ontologies and advanced scientific visualization in big data analytics 

      Chuprina, Svetlana (Barcelona Supercomputing Center, 2016-09-10)
      Conference report
      Open Access
      Accessing and contextual semantic searching structured, semi-structured and unstructured information resources and their ontology based analysis in a uniform way across text-free Big Data query implementation is a main ...

    • A programming model for hybrid workflows: combining task-based workflows and dataflows all-in-one 

      Ramón Cortés, Cristian; Lordan Gomis, Francesc; Ejarque Artigas, Jorge; Badia Sala, Rosa Maria (Elsevier, 2020-12)
      Article
      Restricted access - publisher's policy
      In the past years, e-Science applications have evolved from large-scale simulations executed in a single cluster to more complex workflows where these simulations are combined with High-Performance Data Analytics (HPDA). ...

    • A Quick View on Current Techniques and Machine Learning Algorithms for Big Data Analytics 

      Berral García, Josep Lluís (Institute of Electrical and Electronics Engineers (IEEE), 2016)
      Conference report
      Open Access
      Big-data is an excellent source of knowledge and information from our systems and clients, but dealing with such amount of data requires automation, and this brings us to data mining and machine leaming techniques. In ...

    • A resilient and distributed near real-time traffic forecasting application for Fog computing environments 

      Pérez, Juan L.; Gutierrez-Torre, Alberto; Berral, Josep Ll.; Carrera, David (Elsevier, 2018-10)
      Article
      Open Access
      In this paper we propose an architecture for a city-wide traffic modeling and prediction service based on the Fog Computing paradigm. The work assumes an scenario in which a number of distributed antennas receive data ...

    • A resilient and distributed near real-time traffic forecasting application for Fog computing environments 

      Pérez, Juan Luis; Gutiérrez Torre, Alberto; Berral García, Josep Lluís; Carrera Pérez, David (Elsevier, 2018-10-01)
      Article
      Open Access
      In this paper we propose an architecture for a city-wide traffic modeling and prediction service based on the Fog Computing paradigm. The work assumes an scenario in which a number of distributed antennas receive data ...

    • A scalable synthetic traffic model of Graph500 for computer networks analysis 

      Fuentes Sáez, Pablo; Benito, Mariano; Vallejo, Enrique; Bosque Orero, José Luis; Beivide Palacio, Ramon; Anghel, Andreea; Rodríguez Herrera, Germán; Gusat, Mitch; Minkenberg, Cyriel; Valero Cortés, Mateo (2017-12-25)
      Article
      Open Access
      The Graph500 benchmark attempts to steer the design of High-Performance Computing systems to maximize the performance under memory-constricted application workloads. A realistic simulation of such benchmarks for architectural ...

    • A software reference architecture for semantic-aware big data systems 

      Nadal Francesch, Sergi; Herrero Otal, Víctor; Romero Moral, Óscar; Abelló Gamazo, Alberto; Franch Gutiérrez, Javier; Vansummeren, Stijn; Valerio, Danilo (2016-06-13)
      Article
      Open Access
      Context: Big Data systems are a class of software systems that ingest, store, process and serve massive amounts of heterogeneous data, from multiple sources. Despite their undisputed impact in current society, their ...

    • Acceleració d'algoritmes de clustering mitjançant targetes gràfiques 

      Orrit Palau, Joan (Universitat Politècnica de Catalunya, 2017-06-29)
      Bachelor thesis
      Open Access
      En aquest projecte s'ha estudiat com es comporten diferents algoritmes de clustering amb diferents opotimitzacions de CUDA. Concretament s'han estudiat com funcionen l'algoritme k-means i k-centers amb les optimitzacions ...

    • Accelerating Hash-Based Query Processing Operations on FPGAs by a Hash Table Caching Technique 

      Salami, Behzad; Arcas-Abella, Oriol; Sonmez, Nehir; Unsal, Osman; Cristal Kestelman, Adrián (Springer International Publishing, 2017-04-29)
      Conference lecture
      Open Access
      Extracting valuable information from the rapidly growing field of Big Data faces serious performance constraints, especially in the software-based database management systems (DBMS). In a query processing system, hash-based ...

    • Aircraft conflict detection using data mining and statistical tools 

      Perez Font, Marc (Universitat Politècnica de Catalunya, 2016-10-28)
      Bachelor thesis
      Open Access
      Nowadays and taking into account the different indicators and the forecast of the air traffic volume from Eurocontrol, it is accepted the idea that the traffic will be doubled by 2030, that is why it is so important ...

    • Aligning textual and model-based process descriptions 

      Sánchez Ferreres, Josep; van der Aa, Han; Carmona Vargas, Josep; Padró, Lluís (Elsevier, 2018-01-01)
      Article
      Open Access
      Process model descriptions are an ubiquitous source of information that exists in any organization. To reach different types of stakeholders, distinct descriptions are often kept, so that process understandability is boosted ...

    • ALOJA: A benchmarking and predictive platform for big data performance analysis 

      Poggi, Nicolas; Berral García, Josep Lluís; Carrera Pérez, David (Springer, 2016)
      Conference report
      Open Access
      The main goals of the ALOJA research project from BSC-MSR, are to explore and automate the characterization of cost-effectivenessof Big Data deployments. The development of the project over its first year, has resulted in ...

    • ALOJA: A framework for benchmarking and predictive analytics in Hadoop deployments 

      Berral García, Josep Lluís; Poggi Mastrokalo, Nicolas; Carrera Pérez, David; Call, Aaron; Reinauer, Rob; Green, Daron (Institute of Electrical and Electronics Engineers (IEEE), 2015-10)
      Article
      Open Access
      This article presents the ALOJA project and its analytics tools, which leverages machine learning to interpret Big Data benchmark performance data and tuning. ALOJA is part of a long-term collaboration between BSC and ...

    • ALOJA: a systematic study of Hadoop deployment variables to enable automated characterization of cost-effectiveness 

      Poggi Mastrokalo, Nicolas; Carrera Pérez, David; Call, Aaron; Mendoza, Sergio; Becerra Fontal, Yolanda; Torres Viñals, Jordi; Ayguadé Parra, Eduard; Gagliardi, Fabrizio; Labarta Mancho, Jesús José; Reinauer, Rob; Vujic, Nikola; Green, Daron; Blakeley, Jose (Institute of Electrical and Electronics Engineers (IEEE), 2014)
      Conference report
      Open Access
      This article presents the ALOJA project, an initiative to produce mechanisms for an automated characterization of cost-effectiveness of Hadoop deployments and reports its initial results. ALOJA is the latest phase of a ...