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pro vyhledávání: '"Computational storage"'
Akademický článek
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Autor:
Cheng, Yaosong1 chengys@ihep.ac.cn, Bi, Yujiang1,2 chengys@ihep.ac.cn, Cheng, Yaodong1,2,3, Li, Haibo1,2,3, Gao, Yu1,3, Zhang, Minxing1,3
Publikováno v:
EPJ Web of Conferences. 5/6/2024, Vol. 295, p1-8. 8p.
Autor:
Montana, Aldrin, Xue, Yuanqing, LeFevre, Jeff, Maltzahn, Carlos, Stuart, Josh, Kufeldt, Philip, Alvaro, Peter
Over the years, hardware trends have introduced various heterogeneous compute units while also bringing network and storage bandwidths within an order of magnitude of memory subsystems. In response, developers have used increasingly exotic solutions
Externí odkaz:
http://arxiv.org/abs/2212.11459
Publikováno v:
IEEE Transactions on Computers
K-nearest neighbor search is one of the fundamental tasks in various applications and the hierarchical navigable small world (HNSW) has recently drawn attention in large-scale cloud services, as it easily scales up the database while offering fast se
Externí odkaz:
http://arxiv.org/abs/2207.05241
Publikováno v:
Memories - Materials, Devices, Circuits and Systems, Vol 4, Iss , Pp 100051- (2023)
The von Neumann bottleneck is imposed due to the explosion of data transfers and emerging data-intensive applications in heterogeneous system architectures. The conventional computation approach of transferring data to CPU is no longer suitable espec
Externí odkaz:
https://doaj.org/article/744f630507f1480b8ee928274bc70bf3
Autor:
HeydariGorji, Ali, Torabzadehkashi, Mahdi, Rezaei, Siavash, Bobarshad, Hossein, Alves, Vladimir, Chou, Pai H.
Computational storage drives (CSD) are solid-state drives (SSD) empowered by general-purpose processors that can perform in-storage processing. They have the potential to improve both performance and energy significantly for big-data analytics by bri
Externí odkaz:
http://arxiv.org/abs/2112.12415
Autor:
Lukken, Corne, Trivedi, Animesh
We live in a data-centric world where we are heading to generate close to 200 Zettabytes of data by the year 2025. Our data processing requirements have also increased as we push to build data processing frameworks that can process large volumes of d
Externí odkaz:
http://arxiv.org/abs/2112.09691
The Big Data trend is putting strain on modern storage systems, which have to support high-performance I/O accesses for the large quantities of data. With the prevalent Von Neumann computing architecture, this data is constantly moved back and forth
Externí odkaz:
http://arxiv.org/abs/2112.00142
Autor:
Huang, Wenjun, Paradies, Marcus
As the volume of data that needs to be processed continues to increase, we also see renewed interests in near-data processing in the form of computational storage, with eBPF (extended Berkeley Packet Filter) being proposed as a vehicle for computatio
Externí odkaz:
http://arxiv.org/abs/2111.01947