Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Evangelia Sitaridi"'
Autor:
Kenneth A. Ross, Evangelia Sitaridi
Publikováno v:
The VLDB Journal. 25:719-740
Implementations of relational operators on GPU processors have resulted in order of magnitude speedups compared to their multicore CPU counterparts. Here we focus on the efficient implementation of string matching operators common in SQL queries. Due
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a29c664f386079dbe56734aaee01bd20
https://doi.org/10.1007/s00778-015-0409-y
https://doi.org/10.1007/s00778-015-0409-y
Autor:
Evangelia Sitaridi
Publikováno v:
ICDE
Advances in hardware strongly influence the database system design. The flattening speed of CPU cores makes manycore accelerators a vital alternative to explore for processing the ever-increasing amounts of data. Accelerators typically employ more an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1fa17c2954c2e14abeaebc4931f8283
https://doi.org/10.1109/icde.2017.239
https://doi.org/10.1109/icde.2017.239
Publikováno v:
ICPP
Today's exponentially increasing data volumes and the high cost of storage make compression essential for the Big Data industry. Although research has concentrated on efficient compression, fast decompression is critical for analytics queries that re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6002f239ca30b07f7df1ef8e8e38b55d
http://arxiv.org/abs/1606.00519
http://arxiv.org/abs/1606.00519
Autor:
Kenneth A. Ross, Evangelia Sitaridi
Publikováno v:
DaMoN
Implementations of database operators on GPU processors have shown dramatic performance improvement compared to multicore-CPU implementations. GPU threads can cooperate using shared memory, which is organized in interleaved banks and is fast only whe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d23e3ed4f1a19f5960ef27f080efc386
https://doi.org/10.1145/2236584.2236590
https://doi.org/10.1145/2236584.2236590