Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Abid M. Malik"'
Publikováno v:
Proceedings of the 14th International Workshop on Programming Models and Applications for Multicores and Manycores.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c47041a28bead7f225395dd767b904df
https://doi.org/10.1145/3582514.3582519
https://doi.org/10.1145/3582514.3582519
Publikováno v:
Proceedings of the 19th ACM International Conference on Computing Frontiers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4033d4b992d8c344316a19dd73f0eb0e
https://doi.org/10.1145/3528416.3530251
https://doi.org/10.1145/3528416.3530251
Publikováno v:
2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45180ad56a5baf38bf38f86898362c1b
https://doi.org/10.1109/ipdpsw55747.2022.00074
https://doi.org/10.1109/ipdpsw55747.2022.00074
Autor:
Wenbin Lu, Baodi Shan, Eric Raut, Jie Meng, Mauricio Araya-Polo, Johannes Doerfert, Abid M. Malik, Barbara Chapman
Publikováno v:
OpenMP in a Modern World: From Multi-device Support to Meta Programming ISBN: 9783031159213
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92024c866bcf8dc3d2e038146387cc81
https://doi.org/10.1007/978-3-031-15922-0_2
https://doi.org/10.1007/978-3-031-15922-0_2
Publikováno v:
Sustainable Computing: Informatics and Systems. 23:1-12
Energy consumption of an application has gained the same importance as execution time in current HPC systems, primarily due to the massive energy consumption of these systems and consequently substantial energy bills. This fact forced software develo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::145141ca40252511635bf839a39d1548
https://doi.org/10.1016/j.suscom.2019.04.002
https://doi.org/10.1016/j.suscom.2019.04.002
Publikováno v:
IPDPS Workshops
Recently, edge computing has received considerable attention as a promising means to provide Deep Learning (DL) based services. However, due to the limited computation capability of the data processing units (such as CPUs, GPUs, and specialized accel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::229659347a5d63207639089f202508d9
https://doi.org/10.1109/ipdpsw52791.2021.00128
https://doi.org/10.1109/ipdpsw52791.2021.00128
Publikováno v:
2020 IEEE/ACM 6th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC) and Workshop on Hierarchical Parallelism for Exascale Computing (HiPar).
OpenMP 5.0 introduces many new directives to meet the demand of emerging high performance computing systems. Among these new directives, the metadirective and declare variant directives are important to control the execution behavior of a given appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac839e19598deb91c509b84723cbd395
https://doi.org/10.1109/llvmhpchipar51896.2020.00009
https://doi.org/10.1109/llvmhpchipar51896.2020.00009
Publikováno v:
OpenMP: Portable Multi-Level Parallelism on Modern Systems ISBN: 9783030581435
IWOMP
IWOMP
In the high performance computing sector, researchers and application developers expend considerable effort to port their applications to GPU-based clusters in order to take advantage of the massive parallelism and energy efficiency of a GPU. Unfortu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de54212e7c3e3e46d63a3e0f0ff3d791
https://doi.org/10.1007/978-3-030-58144-2_18
https://doi.org/10.1007/978-3-030-58144-2_18
Publikováno v:
OpenMP: Portable Multi-Level Parallelism on Modern Systems ISBN: 9783030581435
IWOMP
IWOMP
Many modern supercomputers such as ORNL’s Summit, LLNL’s Sierra, and LBL’s upcoming Perlmutter offer or will offer multiple, e.g., 4 to 8, GPUs per node for running computational science and engineering applications. One should expect an applic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7defd7223aea6cf82a01354929239702
https://doi.org/10.1007/978-3-030-58144-2_19
https://doi.org/10.1007/978-3-030-58144-2_19
Publikováno v:
2018 New York Scientific Data Summit (NYSDS).
Long training times for building a high accuracy deep neural networks (DNNs) is impeding research for new DNN architectures. For example, time for training GoogleNet with the ImageNet dataset on a single Nvidia K20 GPU almost takes 25 days. Therefore
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3d856acd2d193b50b61a82900b91da47
https://doi.org/10.1109/nysds.2018.8538946
https://doi.org/10.1109/nysds.2018.8538946