Simulation of interprocessor interactions for MPI-applications in the cloud infrastructure Article Swipe
Nikolay Kutovskiy
,
Andrey Nechaevskiy
,
G. Ososkov
,
Darya I. Pryahina
,
V. Trofimov
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.20537/2076-7633-2017-9-6-955-963
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.20537/2076-7633-2017-9-6-955-963
А new cloud center of parallel computing is to be created in the Laboratory of Information Technologies (LIT) of the Joint Institute for Nuclear Research JINR) what is expected to improve significantly the efficiency of numerical calculations and expedite the receipt of new physically meaningful results due to the more rational use of computing resources. To optimize a scheme of parallel computations at a cloud environment it is necessary to test this scheme for various combinations of equipment parameters (processor speed and numbers, throughput оf а communication network etc). As a test problem, the parallel MPI algorithm for calculations of the long Josephson junctions (LDJ) is chosen. Problems of evaluating the impact of abovementioned factors of computing mean on the computing speed of the test problem are solved by simulation with the simulation program SyMSim developed in LIT. The simulation of the LDJ calculations in the cloud environment enable users without a series of test to find the optimal number of CPUs with a certain type of network run the calculations in a real computer environment. This can save significant computational time in countable resources. The main parameters of the model were obtained from the results of the computational experiment conducted on a special cloud-based testbed. Computational experiments showed that the pure computation time decreases in inverse proportion to the number of processors, but depends significantly on network bandwidth. Comparison of results obtained empirically with the results of simulation showed that the simulation model correctly simulates the parallel calculations performed using the MPI-technology. Besides it confirms our recommendation: for fast calculations of this type it is needed to increase both, - the number of CPUs and the network throughput at the same time. The simulation results allow also to invent an empirical analytical formula expressing the dependence of calculation time by the number of processors for a fixed system configuration. The obtained formula can be applied to other similar studies, but requires additional tests to determine the values of variables.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.20537/2076-7633-2017-9-6-955-963
- OA Status
- diamond
- Cited By
- 2
- References
- 12
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- 10
- OpenAlex ID
- https://openalex.org/W2789795209
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2789795209Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.20537/2076-7633-2017-9-6-955-963Digital Object Identifier
- Title
-
Simulation of interprocessor interactions for MPI-applications in the cloud infrastructureWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-12-01Full publication date if available
- Authors
-
Nikolay Kutovskiy, Andrey Nechaevskiy, G. Ososkov, Darya I. Pryahina, V. TrofimovList of authors in order
- Landing page
-
https://doi.org/10.20537/2076-7633-2017-9-6-955-963Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.20537/2076-7633-2017-9-6-955-963Direct OA link when available
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Cloud computing, Computer science, Parallel computing, Computational science, Distributed computing, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2023: 2Per-year citation counts (last 5 years)
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12Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.analytical | 292 |
| abstract_inverted_index.bandwidth. | 228 |
| abstract_inverted_index.dependence | 296 |
| abstract_inverted_index.efficiency | 33 |
| abstract_inverted_index.evaluating | 109 |
| abstract_inverted_index.experiment | 199 |
| abstract_inverted_index.expressing | 294 |
| abstract_inverted_index.meaningful | 44 |
| abstract_inverted_index.parameters | 78, 187 |
| abstract_inverted_index.physically | 43 |
| abstract_inverted_index.processors | 304 |
| abstract_inverted_index.proportion | 217 |
| abstract_inverted_index.resources. | 54, 184 |
| abstract_inverted_index.simulation | 129, 132, 139, 238, 242, 284 |
| abstract_inverted_index.throughput | 83, 278 |
| abstract_inverted_index.variables. | 329 |
| abstract_inverted_index.Information | 15 |
| abstract_inverted_index.calculation | 298 |
| abstract_inverted_index.cloud-based | 204 |
| abstract_inverted_index.computation | 212 |
| abstract_inverted_index.empirically | 233 |
| abstract_inverted_index.environment | 65, 147 |
| abstract_inverted_index.experiments | 207 |
| abstract_inverted_index.processors, | 222 |
| abstract_inverted_index.significant | 179 |
| abstract_inverted_index.Technologies | 16 |
| abstract_inverted_index.calculations | 36, 98, 143, 170, 248, 260 |
| abstract_inverted_index.combinations | 75 |
| abstract_inverted_index.computations | 61 |
| abstract_inverted_index.environment. | 175 |
| abstract_inverted_index.Computational | 206 |
| abstract_inverted_index.communication | 86 |
| abstract_inverted_index.computational | 180, 198 |
| abstract_inverted_index.significantly | 31, 225 |
| abstract_inverted_index.abovementioned | 113 |
| abstract_inverted_index.configuration. | 309 |
| abstract_inverted_index.MPI-technology. | 252 |
| abstract_inverted_index.recommendation: | 257 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 94 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.6299999952316284 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.25625789 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |