Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Jianchen Shan"'
Publikováno v:
IEEE Transactions on Cloud Computing. :1-12
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27f2f3255073e546743d38770dd2a559
https://doi.org/10.1109/tcc.2023.3276368
https://doi.org/10.1109/tcc.2023.3276368
Publikováno v:
Proceedings of the Eighteenth European Conference on Computer Systems.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a7300c991b47542b8fe7808c04a7d39
https://doi.org/10.1145/3552326.3567487
https://doi.org/10.1145/3552326.3567487
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 32:2557-2570
Despite great advancements in hardware-assisted virtualization of the x86 architecture, certain workloads still suffer significant overhead. This article dissects said overhead in the context of multi-threading. We describe the state-of-the-art, pinp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b0700add48429e6601f24352b726276
https://doi.org/10.1109/tpds.2021.3064709
https://doi.org/10.1109/tpds.2021.3064709
Publikováno v:
Proceedings of the 13th Symposium on Cloud Computing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eddf0157ccef28100fa6defe5b262e3f
https://doi.org/10.1145/3542929.3563459
https://doi.org/10.1145/3542929.3563459
Autor:
Jianchen Shan, Cristian Borcea, Narain Gehani, Reza Curtmola, Xiaoning Ding, Nafize R. Paiker
Publikováno v:
IEEE Transactions on Cloud Computing. 8:97-111
With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the cloud. This leads to a scenario where computation tasks in the same program run concurrently on both the mobile device and the cloud. An important challe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1eaee2145dc203303f1fb2afe9279083
https://doi.org/10.1109/tcc.2017.2763158
https://doi.org/10.1109/tcc.2017.2763158
Publikováno v:
2021 IEEE International Performance, Computing, and Communications Conference (IPCCC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa07898573f413d6200d487b7feeda07
https://doi.org/10.1109/ipccc51483.2021.9679439
https://doi.org/10.1109/ipccc51483.2021.9679439
Publikováno v:
PACT
Substantial renovations in hardware cache have been focused on reducing cache interference between workloads recently. However, cache conflicts within each workload are surprisingly overlooked. The paper identifies that cache conflicts cannot be effe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::808ae997829dcaa46347c4e6f4d861bf
https://doi.org/10.1109/pact52795.2021.00027
https://doi.org/10.1109/pact52795.2021.00027
Publikováno v:
ISPA/BDCloud/SocialCom/SustainCom
The cost of TLB consistency is steadily increasing as we evolve towards ever more parallel and consolidated systems. In many cases the application memory allocator is responsible for much of this cost. Existing allocators to our knowledge universally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a4972261cd98608872e9023393f6f92
https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00036
https://doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00036
Autor:
Matthew Elbing, Jianchen Shan
Publikováno v:
2020 IEEE Cloud Summit.
With the rise of multicore machines, the Linux scheduler has introduced a sophisticated load balancing mechanism to spread the tasks over the cores. Study [1] has shown that the load balancer implemented in the default Linux scheduler, Complete Fair
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6d8d59174a5011f60e823706e01ca6de
https://doi.org/10.1109/ieeecloudsummit48914.2020.00035
https://doi.org/10.1109/ieeecloudsummit48914.2020.00035
Publikováno v:
2020 IEEE Cloud Summit.
This paper proposes a neuron drop-out mechanism to control the training paces of mobile devices in federated deep learning. The aim is to accelerate the speed of local training on slow mobile devices with minimal impact on training quality, such that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb4dc8d1656396340755d749338c3f5a
https://doi.org/10.1109/ieeecloudsummit48914.2020.00036
https://doi.org/10.1109/ieeecloudsummit48914.2020.00036