کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6961371 | 1452100 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Running high resolution coastal models in forecast systems: Moving from workstations and HPC cluster to cloud resources
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزار
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Herein, the performance of CFS using ECO-SELFE MPI-based model is assessed and compared for the first time in multiple environments, including local workstations, an HPC cluster and a pilot cloud. The analysis is conducted in a range of resources from the physical core count available at the smaller resources to the optimal number of processes, using cloud and HPC cluster resources. Results for the smaller, common physical resources show that the cloud is an attractive option for CFS operation. As the optimal number of processes for the use case is at the limit of the workstations common pool, an analysis was also performed using HPC cluster nodes and federated MPI resources. Results show that the cloud remains an attractive option for CFS. This conclusion is valid both for the use of a single host or through federated hosts, providing that efficient communication infrastructure (such as SRIOV) is available.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Advances in Engineering Software - Volume 117, March 2018, Pages 70-79
Journal: Advances in Engineering Software - Volume 117, March 2018, Pages 70-79
نویسندگان
João Rogeiro, Marta Rodrigues, Alberto Azevedo, Anabela Oliveira, João Paulo Martins, Mário David, João Pina, Nuno Dias, Jorge Gomes,