Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Neena Imam"'
Autor:
Ali Passian, Neena Imam
Publikováno v:
Sensors, Vol 19, Iss 18, p 4048 (2019)
It is widely recognized that nanoscience and nanotechnology and their subfields, such as nanophotonics, nanoelectronics, and nanomechanics, have had a tremendous impact on recent advances in sensing, imaging, and communication, with notable developme
Externí odkaz:
https://doaj.org/article/3362bfbd797d45ea9024f40996f14aba
Publikováno v:
Entropy, Vol 19, Iss 9, p 500 (2017)
A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this problem usi
Externí odkaz:
https://doaj.org/article/09b9ec8137fa4b1e9f943183503119d1
Publikováno v:
Journal of Superconductivity and Novel Magnetism. 35:373-382
In this paper, operational principles of a cryogenic memory cell that utilizes high-temperature superconductors (high-Tc) are presented. Such a cell consists of three inductively coupled Josephson junctions coupled via inductors. Design and operation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d1f65f86c58fabd3d2a1a01320e604c6
https://doi.org/10.1007/s10948-021-06069-5
https://doi.org/10.1007/s10948-021-06069-5
Autor:
Chung-Hsing Hsu, Neena Imam
Publikováno v:
International Journal of Networking and Computing. 11:78-101
High Performance Computing has been a driving force behind important tasks such as scientific discovery and deep learning. It tends to achieve performance through greater concurrency and heterogeneity, where the underlying complexity of richer topolo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82254ef385dc884bb2b6e8dfd75b9bbc
https://doi.org/10.15803/ijnc.11.1_78
https://doi.org/10.15803/ijnc.11.1_78
Publikováno v:
2022 IEEE International Systems Conference (SysCon).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76d0618e1ca11bd5473d08f29ba39baf
https://doi.org/10.1109/syscon53536.2022.9773826
https://doi.org/10.1109/syscon53536.2022.9773826
Autor:
Nageswara S. V. Rao, Anees Al-Najjar, Neena Imam, Zhengchun Liu, Rajkumar Kettimuthu, Ian Foster
Publikováno v:
Machine Learning for Networking ISBN: 9783030989774
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc8d5d2b9856d02b06e6c284784001aa
https://doi.org/10.1007/978-3-030-98978-1_4
https://doi.org/10.1007/978-3-030-98978-1_4
Publikováno v:
IPDPS Workshops
Memory design space exploration methods study memory systems’ performances and limitations before implementation. The computer memory design space has grown exponentially because of the enormous growth of memory types, memory controllers, and appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::508c621607daa4b2e639f3de947ebef3
https://doi.org/10.1109/ipdpsw52791.2021.00075
https://doi.org/10.1109/ipdpsw52791.2021.00075
Publikováno v:
IPDPS Workshops
A graph is an excellent way of representing relationships among entities. We can use graph analytics to synthesize and analyze such relational data, and extract relevant features that are useful for various tasks such as machine learning. Considering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f103f61349978a923633e06147195b00
https://doi.org/10.1109/ipdpsw52791.2021.00053
https://doi.org/10.1109/ipdpsw52791.2021.00053
Publikováno v:
Advances in Data Science and Information Engineering ISBN: 9783030717032
We present Phoenix, a scalable hypergraph analytics framework for data analytics and knowledge discovery that was implemented on the leadership class computing platforms at Oak Ridge National Laboratory (ORNL). Our software framework comprises a dist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad93089205775de965fa5bea9104902d
https://doi.org/10.1007/978-3-030-71704-9_1
https://doi.org/10.1007/978-3-030-71704-9_1
Publikováno v:
IPDPS Workshops
High Performance Computing has been a driving force behind important tasks such as scientific discovery and deep learning. It tends to achieve performance through greater concurrency and heterogeneity, where the underlying complexity of richer topolo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0eaaf7c81ff67ae16029099704ade31
https://doi.org/10.1109/ipdpsw50202.2020.00104
https://doi.org/10.1109/ipdpsw50202.2020.00104