Implications of virtualization on Grids for high energy physics applications
The simulations used in the field of high energy physics are compute intensive and exhibit a high level of data parallelism. These features make such simulations ideal candidates for Grid computing. We are taking as an example the GEANT4 detector simulation used for physics studies within the ATLAS...
| Main Authors: | , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2006
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| _version_ | 1797079813266079744 |
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| author | Gilbert, L Tseng, J Newman, R Iqbal, S Pepper, R Celebioglu, O Hsieh, J Mashayekhi, V Cobban, M |
| author_facet | Gilbert, L Tseng, J Newman, R Iqbal, S Pepper, R Celebioglu, O Hsieh, J Mashayekhi, V Cobban, M |
| author_sort | Gilbert, L |
| collection | OXFORD |
| description | The simulations used in the field of high energy physics are compute intensive and exhibit a high level of data parallelism. These features make such simulations ideal candidates for Grid computing. We are taking as an example the GEANT4 detector simulation used for physics studies within the ATLAS experiment at CERN. One key issue in Grid computing is that of network and system security, which can potentially inhibit the widespread use of such simulations. Virtualization provides a feasible solution because it allows the creation of virtual compute nodes in both local and remote compute clusters, thus providing an insulating layer which can play an important role in satisfying the security concerns of all parties involved. However, it has performance implications. This study provides quantitative estimates of the virtualization and hyper-threading overhead for GEANT on commodity clusters. Results show that virtualization has less than 15% run time overhead, and that the best run time (with the non-SMP license of ESX VMware) is achieved by using one virtual machine per CPU. We also observe that hyper-threading does not provide an advantage in this application. Finally, the effect of virtualization on run time, throughput, mean response time and utilization is estimated using simulations. © 2006 Elsevier Inc. All rights reserved. |
| first_indexed | 2024-03-07T00:51:09Z |
| format | Journal article |
| id | oxford-uuid:8673e165-bb4f-4f80-913b-7df0ea7a4df0 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T00:51:09Z |
| publishDate | 2006 |
| record_format | dspace |
| spelling | oxford-uuid:8673e165-bb4f-4f80-913b-7df0ea7a4df02022-03-26T22:04:01ZImplications of virtualization on Grids for high energy physics applicationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:8673e165-bb4f-4f80-913b-7df0ea7a4df0EnglishSymplectic Elements at Oxford2006Gilbert, LTseng, JNewman, RIqbal, SPepper, RCelebioglu, OHsieh, JMashayekhi, VCobban, MThe simulations used in the field of high energy physics are compute intensive and exhibit a high level of data parallelism. These features make such simulations ideal candidates for Grid computing. We are taking as an example the GEANT4 detector simulation used for physics studies within the ATLAS experiment at CERN. One key issue in Grid computing is that of network and system security, which can potentially inhibit the widespread use of such simulations. Virtualization provides a feasible solution because it allows the creation of virtual compute nodes in both local and remote compute clusters, thus providing an insulating layer which can play an important role in satisfying the security concerns of all parties involved. However, it has performance implications. This study provides quantitative estimates of the virtualization and hyper-threading overhead for GEANT on commodity clusters. Results show that virtualization has less than 15% run time overhead, and that the best run time (with the non-SMP license of ESX VMware) is achieved by using one virtual machine per CPU. We also observe that hyper-threading does not provide an advantage in this application. Finally, the effect of virtualization on run time, throughput, mean response time and utilization is estimated using simulations. © 2006 Elsevier Inc. All rights reserved. |
| spellingShingle | Gilbert, L Tseng, J Newman, R Iqbal, S Pepper, R Celebioglu, O Hsieh, J Mashayekhi, V Cobban, M Implications of virtualization on Grids for high energy physics applications |
| title | Implications of virtualization on Grids for high energy physics applications |
| title_full | Implications of virtualization on Grids for high energy physics applications |
| title_fullStr | Implications of virtualization on Grids for high energy physics applications |
| title_full_unstemmed | Implications of virtualization on Grids for high energy physics applications |
| title_short | Implications of virtualization on Grids for high energy physics applications |
| title_sort | implications of virtualization on grids for high energy physics applications |
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