Zobrazeno 1 - 9
of 9
pro vyhledávání: '"SIOULAS PANAGIOTIS"'
Analytical tools often require real-time responses for highly concurrent parameterized workloads. A common solution is to answer queries using materialized subexpressions, hence reducing processing at runtime. However, as queries are still processed
Externí odkaz:
http://arxiv.org/abs/2307.08018
Autor:
Sioulas, Panagiotis, Chrysogelos, Periklis, Karpathiotakis, Manos, Appuswamy, Raja, Ailamaki, Anastasia
Publikováno v:
ICDE 2019, 35th IEEE International Conference on Data Engineering, 8-12 April 2019, Macau SAR, China
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1093::40610a26955288ed29edc89792160cce
http://www.eurecom.fr/publication/5780
http://www.eurecom.fr/publication/5780
Autor:
Aunn Raza, Chrysogelos, Periklis, Sioulas, Panagiotis, Indjic, Vladimir, Anadiotis, Angelos Christos, Ailamaki, Anastasia
Publikováno v:
Conference on Innovative Data Systems Research (CIDR)
GPUs are becoming increasingly popular in large scale data center installations due to their strong, embarrassingly parallel, processing capabilities. Data management systems are riding the wave by using GPUs to accelerate query execution, mainly for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c8ddcf154a7fbcff19d44ea35a00f12
https://doi.org/10.5281/zenodo.3827490
https://doi.org/10.5281/zenodo.3827490
Η πρόσφατη ανάδειξη των κοινωνικών δικτύων και ειδικότερα του Twitter έφερε ως αποτέλεσμα δεδομένα πρωτοφανούς μεγέθους για το περιεχόμεν
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2127::1d927e4805096094413833b754fb6f17
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:1705247
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:1705247
Autor:
Sioulas, Panagiotis
In the recent years, the trend in computing has shifted from delivering processors with faster clock speeds to increasing the number of cores per processor. This marks a paradigm shift towards parallel programming in which applications are programmed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________65::a77916dc39958a514739517dbaebef63
http://cds.cern.ch/record/2214513
http://cds.cern.ch/record/2214513
Database systems serve a wide range of use cases efficiently, but require data to be loaded and adapted to the system's execution engine. This pre-processing step is a bottleneck to the analysis of the increasingly large and heterogeneous datasets. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2127::c2e3c63a075086303249a11ff2f23814
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3168895
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3168895
Analytical applications, such as exploratory data analysis and decision support, process complex workloads that include sequences of inter-dependent queries. While modern OLAP systems exploit data parallelism, dependencies force execution ordering co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::c4642fece554719afbe612c3e8eb2b7a
https://infoscience.epfl.ch/record/282304
https://infoscience.epfl.ch/record/282304
In order to improve their power efficiency and computational capacity, modern servers are adopting hardware accelerators, especially GPUs. Modern analytical DMBS engines have been highly optimized for multi-core multi-CPU query execution, but lack th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______185::299309e364e95ef26c9de2a5f6aca92a
https://infoscience.epfl.ch/record/262529
https://infoscience.epfl.ch/record/262529
Autor:
Sioulas, Panagiotis
Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3311e976cc152a7ef36a93595ea92490
https://infoscience.epfl.ch/record/302481
https://infoscience.epfl.ch/record/302481