Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Alexandros Nikolaos Ziogas"'
Autor:
Christoph Weilenmann, Alexandros Nikolaos Ziogas, Till Zellweger, Kevin Portner, Marko Mladenović, Manasa Kaniselvan, Timoleon Moraitis, Mathieu Luisier, Alexandros Emboras
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Biological neural networks do not only include long-term memory and weight multiplication capabilities, as commonly assumed in artificial neural networks, but also more complex functions such as short-term memory, short-term plasticity, and
Externí odkaz:
https://doaj.org/article/a24f297471764226825bbfa23e486945
Autor:
Alexandros Nikolaos Ziogas, Grzegorz Kwasniewski, Tal Ben-Nun, Timo Schneider, Torsten Hoefler
Publikováno v:
SC '22: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Multilinear algebra kernel performance on modern massively-parallel systems is determined mainly by data movement. However, deriving data movement-optimal distributed schedules for programs with many high-dimensional inputs is a notoriously hard prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38380450e1260ffbb35d4f2fbabb2620
https://hdl.handle.net/20.500.11850/616286
https://hdl.handle.net/20.500.11850/616286
Autor:
Grzegorz Kwasniewski, Timo Schneider, André Gaillard, Joost VandeVondele, Maciej Besta, Alexandros Nikolaos Ziogas, Tal Ben-Nun, Torsten Hoefler, Marko Kabić, Jens Eirik Saethre, Anton Kozhevnikov
Publikováno v:
SC
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21)
Matrix factorizations are among the most important building blocks of scientific computing. However, state-of-The-Art libraries are not communication-optimal, underutilizing current parallel architectures. We present novel algorithms for Cholesky and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d07788117874f4a8d7c8aece9b843afa
http://arxiv.org/abs/2108.09337
http://arxiv.org/abs/2108.09337
Autor:
Torsten Hoefler, Timo Schneider, Alexandros Nikolaos Ziogas, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Alexandru Calotoiu, Tal Ben-Nun
Publikováno v:
SC
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '21)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Python has become the de facto language for scientific computing. Programming in Python is highly productive, mainly due to its rich science-oriented software ecosystem built around the NumPy module. As a result, the demand for Python support in High
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::770e3ddd632835da55946461b62be25b
http://arxiv.org/abs/2107.00555
http://arxiv.org/abs/2107.00555
Publikováno v:
Proceedings of the ACM International Conference on Supercomputing
ICS
ICS
Python, already one of the most popular languages for scientific computing, has made significant inroads in High Performance Computing (HPC). At the center of Python's ecosystem is NumPy, an efficient implementation of the multi-dimensional array (te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3098295ebf7fe438568de44650d8a647
Autor:
Timo Schneider, Torsten Hoefler, Alexandros Nikolaos Ziogas, Maciej Besta, Grzegorz Kwasniewski, Tal Ben-Nun
Publikováno v:
PPoPP
Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Dense linear algebra kernels, such as linear solvers or tensor contractions, are fundamental components of many scientific computing applications. In this work, we present a novel method of deriving parallel I/O lower bounds for this broad family of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fa9235d7821e4f55540a26515d2a532
http://arxiv.org/abs/2010.05975
http://arxiv.org/abs/2010.05975
Autor:
Torsten Hoefler, Mathieu Luisier, Guillermo Indalecio Fernández, Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun
Publikováno v:
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '19)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on-SC 19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on -SC '19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '19)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on-SC 19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on -SC '19
Designing efficient cooling systems for integrated circuits (ICs) relies on a deep understanding of the electro-thermal properties of transistors. To shed light on this issue in currently fabricated FinFETs, a quantum mechanical solver capable of rev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ec7f50b125c714ff228c65d9a2cd6a6
Autor:
Torsten Hoefler, Timo Schneider, Guillermo Indalecio Fernández, Mathieu Luisier, Alexandros Nikolaos Ziogas, Tal Ben-Nun
Publikováno v:
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '19)
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on -SC '19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on-SC 19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on -SC '19
Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on-SC 19
The computational efficiency of a state of the art ab initio quantum transport (QT) solver, capable of revealing the coupled electro-thermal properties of atomically-resolved nano-transistors, has been improved by up to two orders of magnitude throug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e51a062f1440966dcb97fe6a437ec49a
https://hdl.handle.net/20.500.11850/394966
https://hdl.handle.net/20.500.11850/394966
Autor:
Maciej Besta, Simon Huber, Daniel Peter, Torsten Hoefler, Tal Ben-Nun, Alexandros Nikolaos Ziogas
Publikováno v:
2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
IPDPS
IPDPS
We introduce Deep500: the first customizable benchmarking infrastructure that enables fair comparison of the plethora of deep learning frameworks, algorithms, libraries, and techniques. The key idea behind Deep500 is its modular design, where deep le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::554ac0d57e985fafb1cf0c277bf9542e