3706640
doi
10.5281/zenodo.3706640
oai:zenodo.org:3706640
Petrov Ivan
Lomonosov Moscow State University, 1 Leninskiye Gory, Moscow, 119991, Russia
Smeliansky Ruslan
Lomonosov Moscow State University, 1 Leninskiye Gory, Moscow, 119991, Russia
Huang Zhen Chun
Tsinghua University, 30 Shuangqing Rd, Haidian, Beijing, 100084, China
Chen Min
Huazhong University of Science & Technology, 1037 Luoyu Rd, Wuhan, 430074, China
Cao Donggang
Peking University, 5 Yiheyuan Rd, Haidian, 100871, China
Chen Xiangqun
Peking University, 5 Yiheyuan Rd, Haidian, 100871, China
MC2E: META-CLOUD COMPUTING ENVIRONMENT FOR HPC
Antonenko Vitaly
Lomonosov Moscow State University, 1 Leninskiye Gory, Moscow, 119991, Russia
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
High Performance Computing
Supercomputer
Cloud
Data-Center
<p>Recently in many scientific disciplines, e.g. physics, chemistry, biology and multidisciplinary research have shifted to the computational modeling. The main instrument for such numerical experiments has been supercomputing. However the number of supercomputers and their performance grows significantly slower than the growth of users’ demands. As a result, users may wait for weeks until their job will be done. At the same time the computational power of cloud computing grow up considerably and represent today a plenty available resources for numerical experiments for many applications. There are several problems related to cloud and supercomputer integration. First, is how to make a decision where to send a computational task: to a supercomputer or to cloud. Second, various platforms may have significantly different APIs, and it’s often labor-expensively for researchers to move from one platform to another since it would require large code modification. In this research we present MC2E –an environment for academic multidisciplinary research. MC2E aggregates heterogeneous resources such as private/public clouds, HPC clusters and supercomputers under a unified easy-to-use interface. This environment will allow to schedule parallel applications between clouds and supercomputers based on their performance and resource usage. MC2E will also provide a Channel-on-Demand service to connect clouds and supercomputers with channels that are used to send data for parallel applications.</p>
Zenodo
2019-09-30
info:eu-repo/semantics/conferencePaper
3706639
1583958024.530457
642731
md5:b637a1bd5c31b0ed0b8177c001117b0c
https://zenodo.org/records/3706640/files/7-15-paper-2.pdf
public
10.5281/zenodo.3706639
isVersionOf
doi