Zobrazeno 1 - 8
of 8
pro vyhledávání: '"DUNBO ZHANG"'
Publikováno v:
ACM Transactions on Architecture & Code Optimization; Mar2024, Vol. 21 Issue 1, p1-23, 23p
Publikováno v:
Algorithms and Architectures for Parallel Processing ISBN: 9783030953874
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::780bec911f525a58a8bf0da68e8ffc88
https://doi.org/10.1007/978-3-030-95388-1_3
https://doi.org/10.1007/978-3-030-95388-1_3
Publikováno v:
Algorithms and Architectures for Parallel Processing ISBN: 9783030953836
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::166fefd218b7201bde45c0c9ad6c1551
https://doi.org/10.1007/978-3-030-95384-3_22
https://doi.org/10.1007/978-3-030-95384-3_22
Publikováno v:
2021 12th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::79859d76c994c7da49bab34e7e5ac3cf
https://doi.org/10.1109/paap54281.2021.9720477
https://doi.org/10.1109/paap54281.2021.9720477
Publikováno v:
Frontiers of Computer Science. 16
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d58353b1fe379cdb71ff623b57ca2c3
https://doi.org/10.1007/s11704-020-9485-2
https://doi.org/10.1007/s11704-020-9485-2
Publikováno v:
Electronics
Volume 10
Issue 17
Electronics, Vol 10, Iss 2176, p 2176 (2021)
Volume 10
Issue 17
Electronics, Vol 10, Iss 2176, p 2176 (2021)
Deep learning has achieved outstanding results in various tasks in machine learning under the background of rapid increase in equipment’s computing capacity. However, while achieving higher performance and effects, model size is larger, training an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6aa2651cc73de032f7980f964fa24e7d
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030794774
NPC
NPC
As a popular research field of computer vision, super-resolution is currently widely studied. In the past, the size of the training set required for super-resolution work was too large. A large training set would cause more resource requirements, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::178d77dd8b8f745f8e7cdcdb814ba04d
https://doi.org/10.1007/978-3-030-79478-1_9
https://doi.org/10.1007/978-3-030-79478-1_9
Publikováno v:
ISPA/BDCloud/SocialCom/SustainCom
GPU enables shared virtual memory (SVM) to eliminate complex data transfer in GPU programming for programmers. However, SVM bring the expensive overhead of address translation due to the large number of address translation requests which are generate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a3028a12d3cb61d56a20eb2d689a8a1
https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00038
https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00038