Zobrazeno 1 - 10
of 178
pro vyhledávání: '"Chuliang Weng"'
Publikováno v:
Data Science and Engineering, Vol 3, Iss 3, Pp 263-276 (2018)
Abstract Hardware techniques and environments underwent significant transformations in the field of information technology, represented by high-performance processors and hardware accelerators characterized by abundant heterogeneous parallelism, nonv
Externí odkaz:
https://doaj.org/article/92504043e26e4681b8f5ca340c9a2eb8
Publikováno v:
Frontiers of Computer Science. 17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39ea9e133eb5bd6422bd579b4fa726d4
https://doi.org/10.1007/s11704-023-2483-4
https://doi.org/10.1007/s11704-023-2483-4
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 34:2241-2253
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c909f9ea786482263a4be7170fafdaec
https://doi.org/10.1109/tkde.2020.3011510
https://doi.org/10.1109/tkde.2020.3011510
Publikováno v:
Frontiers of Computer Science. 17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae962352fede9a9f77b1e05e1a99fc3d
https://doi.org/10.1007/s11704-022-2160-z
https://doi.org/10.1007/s11704-022-2160-z
Publikováno v:
IEEE Transactions on Computers. 69:819-831
Nowadays, GPUs have achieved high throughput computing by running plenty of threads. However, owing to disjoint memory spaces of discrete CPU-GPU systems, exploiting CPU and GPU within a data processing pipeline is a non-trivial issue, which can only
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55ba145d35750f955b940d4d1150dc5b
https://doi.org/10.1109/tc.2020.2968302
https://doi.org/10.1109/tc.2020.2968302
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering. 32:533-546
To fully utilize the resources of a main memory database cluster, we additionally take the independent parallelism into account to parallelize multiple pipelines of one query. However, scheduling resources to multiple pipelines is an intractable prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8210c40e3d025ee265dca058e0f1d719
https://doi.org/10.1109/tkde.2018.2884724
https://doi.org/10.1109/tkde.2018.2884724
Publikováno v:
Proceedings of the VLDB Endowment. 13:226-238
SIMD is an instruction set in mainstream processors, which provides the data level parallelism to accelerate the performance of applications. However, its advantages diminish when applications suffer from heavy cache misses. To eliminate cache misses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f47552d404a5caa53988faa06851c624
https://doi.org/10.14778/3368289.3368290
https://doi.org/10.14778/3368289.3368290
Publikováno v:
ICDE
Distributed in-memory computing systems have dramatic performance improvement over traditional disk-based systems, which makes them widely used in large-scale data processing applications. Unfortunately, uneven and unpredictable data distributions ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d52bd37cf3baf44025a6f2f736fccf3d
https://doi.org/10.1109/icde51399.2021.00168
https://doi.org/10.1109/icde51399.2021.00168
Publikováno v:
PPoPP
With the development of the big data ecosystem, large-scale data analytics has become more prevalent in the past few years. Apache Spark, etc., provide a flexible approach for scalable processing upon massive data. However, they are not designed for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad70fb67bc2787a5f959aa7bf94a0d25
https://doi.org/10.1145/3437801.3441595
https://doi.org/10.1145/3437801.3441595
Publikováno v:
ICDE
Most database systems rely on complex multi-layer and compatibility-oriented storage stacks, which results in sub-optimal database management system (DBMS) performance and significant write amplification. A heavy storage stack can be tolerated in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac1d49f0cc470b0cce0bf6a1b66e5457
https://doi.org/10.1109/icde48307.2020.00110
https://doi.org/10.1109/icde48307.2020.00110