Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Bryan Donyanavard"'
Autor:
Biswadip Maity, Minjun Seo, Eberle A. Rambo, Nikil Dutt, Rolf Ernst, Florian Maurer, Andreas Herkersdorf, Anmol Prakash Surhonne, Thawra Kadeed, Bryan Donyanavard, Fadi J. Kurdahi, Caio Batista de Melo
Publikováno v:
IEEE Transactions on Emerging Topics in Computing. 10:250-266
In order to provide performance increases despite the end of Moore's law and Dennard scaling, architectures aggressively exploit data- and thread-level parallelism using billions of transistors on a single chip, enabled by extreme geometry miniaturiz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f34926ff22dd78059d02672cadb37d13
https://doi.org/10.1109/tetc.2020.3011663
https://doi.org/10.1109/tetc.2020.3011663
Publikováno v:
Analysis, Estimations, and Applications of Embedded Systems ISBN: 9783031264993
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bea6c5e34d3558c779e5701cdb1e523
https://doi.org/10.1007/978-3-031-26500-6_6
https://doi.org/10.1007/978-3-031-26500-6_6
Autor:
Biswadip Maity, Sung-Soo Lim, Saehanseul Yi, Bryan Donyanavard, Dongjoo Seo, Jong-Chan Kim, Nikil Dutt, Leming Cheng
Publikováno v:
ACM Transactions on Embedded Computing Systems. 20:1-22
Self-driving systems execute an ensemble of different self-driving workloads on embedded systems in an end-to-end manner, subject to functional and performance requirements. To enable exploration, optimization, and end-to-end evaluation on different
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a7fd7164a2cd45bc57a7bc9b1929675
https://doi.org/10.1145/3477005
https://doi.org/10.1145/3477005
Publikováno v:
IEEE Embedded Systems Letters. 13:85-89
Users of embedded and cyber-physical systems expect dependable operation for an increasingly diverse set of applications and environments. Reactive self-diagnosis techniques either use unnecessarily conservative guardbands, or do not prevent catastro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39a0c0f6f18175311b687fecaa97e568
https://doi.org/10.1109/les.2020.3007361
https://doi.org/10.1109/les.2020.3007361
Publikováno v:
2022 IEEE International Conference on Networking, Architecture and Storage (NAS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17bd680b921ad24e865ae12010c80503
https://doi.org/10.1109/nas55553.2022.9925330
https://doi.org/10.1109/nas55553.2022.9925330
Autor:
Amir M. Rahmani, Biswadip Maity, Nikil Dutt, Andreas Herkersdorf, Bryan Donyanavard, Anmol Prakash Surhonne
Publikováno v:
ACM Transactions on Embedded Computing Systems. 20:1-26
Memory approximation techniques are commonly limited in scope, targeting individual levels of the memory hierarchy. Existing approximation techniques for a full memory hierarchy determine optimal configurations at design-time provided a goal and appl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8c2bce4f252f65b736d5e84fc5f72362
https://doi.org/10.1145/3466875
https://doi.org/10.1145/3466875
Autor:
Sina Shahhosseini, Tianyi Hu, Dongjoo Seo, Anil Kanduri, Bryan Donyanavard, Amir M. Rahmani, Nikil Dutt
Deep-learning-based intelligent services have become prevalent in cyber-physical applications including smart cities and health-care. Collaborative end-edge-cloud computing for deep learning provides a range of performance and efficiency that can add
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::288971c7d7697673c6363e0e41d6174f
http://arxiv.org/abs/2202.11098
http://arxiv.org/abs/2202.11098
Autor:
Sandra Hernandez, Jose Araujo, Patric Jensfelt, Ioannis Karagiannis, Ananya Muddukrishna, Bryan Donyanavard
Publikováno v:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9b2c1240d2bca7f7eac557a0cb56a47
https://doi.org/10.1109/iros51168.2021.9635978
https://doi.org/10.1109/iros51168.2021.9635978
Runtime resource management for many-core systems is increasingly complex. The complexity can be due to diverse workload characteristics with conflicting demands, or limited shared resources such as memory bandwidth and power. Resource management str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eac6f8808775727407b61c869ca5b594
https://doi.org/10.4018/978-1-7998-7156-9.ch004
https://doi.org/10.4018/978-1-7998-7156-9.ch004
Publikováno v:
IGSC (Workshops)
With the advent of GPUs and application-specific accelerators in embedded platforms, data-intensive applications have exacerbated the memory performance and energy bottleneck. Memory requirements and usage patterns vary widely in emerging architectur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c5cb5115f0f4a3d99b1481bc748ceca
https://doi.org/10.1109/igsc51522.2020.9291086
https://doi.org/10.1109/igsc51522.2020.9291086