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Evaluating the benefits of key-value databases for scientific applications
dc.contributor.author | Santamaria Mateu, Pol |
dc.contributor.author | Oden, Lena |
dc.contributor.author | Gil, Eloy |
dc.contributor.author | Becerra Fontal, Yolanda |
dc.contributor.author | Sirvent, Raül |
dc.contributor.author | Glock, Philipp |
dc.contributor.author | Torres Viñals, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.contributor.other | Barcelona Supercomputing Center |
dc.date.accessioned | 2019-07-18T09:49:26Z |
dc.date.available | 2019-07-18T09:49:26Z |
dc.date.issued | 2019 |
dc.identifier.citation | Santamaria, P. [et al.]. Evaluating the benefits of key-value databases for scientific applications. A: International Conference on Computational Science. "Computational Science: ICCS 2019, 19th International Conference: Faro, Portugal, June 12–14, 2019: proceedings, part I". Berlín: Springer, 2019, p. 412-426. |
dc.identifier.isbn | 3030227340 |
dc.identifier.uri | http://hdl.handle.net/2117/166407 |
dc.description.abstract | The convergence of Big Data applications with High-Performance Computing requires new methodologies to store, manage and process large amounts of information. Traditional storage solutions are unable to scale and that results in complex coding strategies. For example, the brain atlas of the Human Brain Project has the challenge to process large amounts of high-resolution brain images. Given the computing needs, we study the effects of replacing a traditional storage system with a distributed Key-Value database on a cell segmentation application. The original code uses HDF5 files on GPFS through an intricate interface, imposing synchronizations. On the other hand, by using Apache Cassandra or ScyllaDB through Hecuba, the application code is greatly simplified. Thanks to the Key-Value data model, the number of synchronizations is reduced and the time dedicated to I/O scales when increasing the number of nodes. |
dc.description.sponsorship | This project/research has received funding from the European Unions Horizon 2020 Framework Programme for Research and Innovation under the Speci c Grant Agreement No. 720270 (Human Brain Project SGA1) and the Speci c Grant Agreement No. 785907 (Human Brain Project SGA2). This work has also been supported by the Spanish Government (SEV2015-0493), by the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P), and by Generalitat de Catalunya (contract 2017-SGR-1414). |
dc.format.extent | 15 p. |
dc.language.iso | eng |
dc.publisher | Springer |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació |
dc.subject.lcsh | Information storage and retrieval systems |
dc.subject.lcsh | Big data |
dc.subject.lcsh | High performance computing |
dc.subject.other | Key-Value distributed databases |
dc.subject.other | HPC |
dc.subject.other | NoSQL |
dc.title | Evaluating the benefits of key-value databases for scientific applications |
dc.type | Conference report |
dc.subject.lemac | Informació -- Sistemes d'emmagatzematge i recuperació |
dc.subject.lemac | Macrodades |
dc.subject.lemac | Càlcul intensiu (Informàtica) |
dc.contributor.group | Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
dc.identifier.doi | 10.1007/978-3-030-22734-0_30 |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-030-22734-0_30 |
dc.rights.access | Open Access |
local.identifier.drac | 25422725 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/AGAUR/2017 SGR 1414 |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/ |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/720270/EU/Human Brain Project Specific Grant Agreement 1/HBP SGA1 |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/H2020/785907/EU/Human Brain Project Specific Grant Agreement 2/HBP SGA2 |
local.citation.author | Santamaria, P.; Oden, L.; Gil, E.; Becerra, Y.; Sirvent, R.; Glock, P.; Torres, J. |
local.citation.contributor | International Conference on Computational Science |
local.citation.pubplace | Berlín |
local.citation.publicationName | Computational Science: ICCS 2019, 19th International Conference: Faro, Portugal, June 12–14, 2019: proceedings, part I |
local.citation.startingPage | 412 |
local.citation.endingPage | 426 |