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pro vyhledávání: '"Graph500"'
Akademický článek
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Autor:
Tiejun Li, Jie Liu, Ruibo Wang, Yiming Zhang, Tiaojie Xiao, Kai Lu, Zeng Ruigeng, Xinbiao Gan
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 33:941-951
As the era of exascale supercomputing is coming, it is vital for next-generation supercomputers to find appropriate applications with high social and economic benefit. In recent years, it has been widely accepted that extremely-large graph computatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d5496d4f6826f69b2c42a8febb68b655
https://doi.org/10.1109/tpds.2021.3100785
https://doi.org/10.1109/tpds.2021.3100785
Publikováno v:
CCF Transactions on High Performance Computing. 3:271-285
Graphs are an effective approach for data representation and organization, and graph analysis is a promising killer application for AI systems. However, recently emerging extremely large graphs (consisting of trillions of vertices and edges) exceed t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6445dbf867c79355972ddcf365afde7
https://doi.org/10.1007/s42514-021-00070-z
https://doi.org/10.1007/s42514-021-00070-z
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030787127
ISC
ISC
In this paper, we present the performance of the supercomputer Fugaku for breadth-first search (BFS) problem in the Graph500 benchmark, which is known as a ranking benchmark used to evaluate large-scale graph processing performance on supercomputer s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7060c3e68a428d62678d80b4de5dde0
http://hdl.handle.net/2324/4771851
http://hdl.handle.net/2324/4771851
Conference
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Publikováno v:
IEEE Transactions on Computers. 69:749-763
Automated performance modeling and performance prediction of parallel programs are highly valuable in many use cases, such as in guiding task management and job scheduling, offering insights of application behaviors, and assisting resource requiremen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24eefb56bd612cd0a039724f54d4d48c
https://doi.org/10.1109/tc.2020.2964767
https://doi.org/10.1109/tc.2020.2964767
Autor:
Ihre Sherif, Alan
On certain CPUs part of the Intel Xeon Scalable CPU family, the level three (L3) cache is shared among the CPU cores residing on the same CPU socket. This has benefits in that a larger and more scalable cache space is available to the CPU cores. Howe
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-306728
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 16:1-27
Memory prefetchers are designed to identify and prefetch specific access patterns, including spatiotemporal locality (e.g., strides, streams), recurring patterns (e.g., varying strides, temporal correlation), and specific irregular patterns (e.g., po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd59c9ac4a3387cebda19d7fd7e81aa4
https://doi.org/10.1145/3345000
https://doi.org/10.1145/3345000
Publikováno v:
IEEE Transactions on Computers. 68:1019-1034
In-memory computing has inspired researchers to consider integrating large-capacity persistent memory (PM) into the main memory subsystem. However, several challenges still remain for providing an integration approach for DRAM-comparable PM on existi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4279e73aec7cfb8e497951fa38e388b1
https://doi.org/10.1109/tc.2019.2899836
https://doi.org/10.1109/tc.2019.2899836
Publikováno v:
2021 5th International Conference on High Performance Compilation, Computing and Communications.
Performance tuning faces challenges of the heterogeneousness, complexity and flexibility of the modern processors. Due to the limited knowledge of the underlining architecture, users are usually confused about which optimizing should be enabled to sp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::87bc094318fd8f0a87b74b28cf4bf784
https://doi.org/10.1145/3471274.3471282
https://doi.org/10.1145/3471274.3471282