Distributed Computing in a Pandemic
The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of this COVID-19 research depends on distributed computing. In...
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| Format: | Article |
| Language: | English |
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Ediciones Universidad de Salamanca
2022-06-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
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| Online Access: | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/27337 |
| _version_ | 1797943633712775168 |
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| author | Jamie Alnasir |
| author_facet | Jamie Alnasir |
| author_sort | Jamie Alnasir |
| collection | DOAJ |
| description | The current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of this COVID-19 research depends on distributed computing. In this article, I review distributed architectures -- various types of clusters, grids and clouds -- that can be leveraged to perform these tasks at scale, at high-throughput, with a high degree of parallelism, and which can also be used to work collaboratively. High-performance computing (HPC) clusters will be used to carry out much of this work. Several bigdata processing tasks used in reducing the spread of SARS-CoV-2 require high-throughput approaches, and a variety of tools, which Hadoop and Spark offer, even using commodity hardware. Extremely large-scale COVID-19 research has also utilised some of the world's fastest supercomputers, such as IBM's SUMMIT -- for ensemble docking high-throughput screening against SARS-CoV-2 targets for drug-repurposing, and high-throughput gene analysis -- and Sentinel, an XPE-Cray based system used to explore natural products. Grid computing has facilitated the formation of the world's first Exascale grid computer. This has accelerated COVID-19 research in molecular dynamics simulations of SARS-CoV-2 spike protein interactions through massively-parallel computation and was performed with over 1 million volunteer computing devices using the Folding@home platform. Grids and clouds both can also be used for international collaboration by enabling access to important datasets and providing services that allow researchers to focus on research rather than on time-consuming data-management tasks. |
| first_indexed | 2024-04-10T20:27:15Z |
| format | Article |
| id | doaj.art-3df7413263ce449b8fbe649c8723c973 |
| institution | Directory Open Access Journal |
| issn | 2255-2863 |
| language | English |
| last_indexed | 2024-04-10T20:27:15Z |
| publishDate | 2022-06-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj.art-3df7413263ce449b8fbe649c8723c9732023-01-25T08:53:33ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632022-06-01111194310.14201/adcaij.2733732776Distributed Computing in a PandemicJamie Alnasir0Department of Computing, Imperial College LondonThe current COVID-19 global pandemic caused by the SARS-CoV-2 betacoronavirus has resulted in over a million deaths and is having a grave socio-economic impact, hence there is an urgency to find solutions to key research challenges. Much of this COVID-19 research depends on distributed computing. In this article, I review distributed architectures -- various types of clusters, grids and clouds -- that can be leveraged to perform these tasks at scale, at high-throughput, with a high degree of parallelism, and which can also be used to work collaboratively. High-performance computing (HPC) clusters will be used to carry out much of this work. Several bigdata processing tasks used in reducing the spread of SARS-CoV-2 require high-throughput approaches, and a variety of tools, which Hadoop and Spark offer, even using commodity hardware. Extremely large-scale COVID-19 research has also utilised some of the world's fastest supercomputers, such as IBM's SUMMIT -- for ensemble docking high-throughput screening against SARS-CoV-2 targets for drug-repurposing, and high-throughput gene analysis -- and Sentinel, an XPE-Cray based system used to explore natural products. Grid computing has facilitated the formation of the world's first Exascale grid computer. This has accelerated COVID-19 research in molecular dynamics simulations of SARS-CoV-2 spike protein interactions through massively-parallel computation and was performed with over 1 million volunteer computing devices using the Folding@home platform. Grids and clouds both can also be used for international collaboration by enabling access to important datasets and providing services that allow researchers to focus on research rather than on time-consuming data-management tasks.https://revistas.usal.es/cinco/index.php/2255-2863/article/view/27337distributedhpcsupercomputinggridcloudclustersars-cov-2covid-19 |
| spellingShingle | Jamie Alnasir Distributed Computing in a Pandemic Advances in Distributed Computing and Artificial Intelligence Journal distributed hpc supercomputing grid cloud cluster sars-cov-2 covid-19 |
| title | Distributed Computing in a Pandemic |
| title_full | Distributed Computing in a Pandemic |
| title_fullStr | Distributed Computing in a Pandemic |
| title_full_unstemmed | Distributed Computing in a Pandemic |
| title_short | Distributed Computing in a Pandemic |
| title_sort | distributed computing in a pandemic |
| topic | distributed hpc supercomputing grid cloud cluster sars-cov-2 covid-19 |
| url | https://revistas.usal.es/cinco/index.php/2255-2863/article/view/27337 |
| work_keys_str_mv | AT jamiealnasir distributedcomputinginapandemic |