Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters
In this article, we propose new extensions to Hadoop to enable clusters of reconfigurable active solid-state drives (RASSDs) to process streaming data from SSDs using FPGAs. We also develop an analytical model to estimate the performance of RASSD clusters running under Hadoop. Using the Hadoop RASSD...
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| مؤلفون آخرون: | , , , , , , |
| التنسيق: | article |
| منشور في: |
2014
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| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/15388 https://doi.org/10.1145/2608199 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://dl.acm.org/doi/abs/10.1145/2608199 |
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| _version_ | 1864513470521671680 |
|---|---|
| author | Kaitoua, Abdul Rahman |
| author2 | Hajj, Hazem Saghir, Mazen A.R. Artail, Hassan Akkary, Haitham Awad, Mariette Sharafeddine, Mageda Mershad, Khaleel |
| author2_role | author author author author author author author |
| author_facet | Kaitoua, Abdul Rahman Hajj, Hazem Saghir, Mazen A.R. Artail, Hassan Akkary, Haitham Awad, Mariette Sharafeddine, Mageda Mershad, Khaleel |
| author_role | author |
| dc.creator.none.fl_str_mv | Kaitoua, Abdul Rahman Hajj, Hazem Saghir, Mazen A.R. Artail, Hassan Akkary, Haitham Awad, Mariette Sharafeddine, Mageda Mershad, Khaleel |
| dc.date.none.fl_str_mv | 2014 2014-07-15 2024-03-07T11:25:59Z 2024-03-07T11:25:59Z |
| dc.identifier.none.fl_str_mv | 1544-3566 http://hdl.handle.net/10725/15388 https://doi.org/10.1145/2608199 Kaitoua, A., Hajj, H., Saghir, M. A., Artail, H., Akkary, H., Awad, M., ... & Mershad, K. (2014). Hadoop extensions for distributed computing on reconfigurable active SSD clusters. ACM Transactions on Architecture and Code Optimization (TACO), 11(2), 1-26. http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://dl.acm.org/doi/abs/10.1145/2608199 |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | ACM Transactions on Architecture and Code Optimization |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.title.none.fl_str_mv | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | In this article, we propose new extensions to Hadoop to enable clusters of reconfigurable active solid-state drives (RASSDs) to process streaming data from SSDs using FPGAs. We also develop an analytical model to estimate the performance of RASSD clusters running under Hadoop. Using the Hadoop RASSD platform and network simulators, we validate our design and demonstrate its impact on performance for different workloads taken from Stanford's Phoenix MapReduce project. Our results show that for a hardware acceleration factor of 20×, compute-intensive workloads processing 153MB of data can run up to 11× faster than a standard Hadoop cluster. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | LAURepo_eb9ef596f281e6c1a54f5c8fa7f7d455 |
| identifier_str_mv | 1544-3566 Kaitoua, A., Hajj, H., Saghir, M. A., Artail, H., Akkary, H., Awad, M., ... & Mershad, K. (2014). Hadoop extensions for distributed computing on reconfigurable active SSD clusters. ACM Transactions on Architecture and Code Optimization (TACO), 11(2), 1-26. |
| language_invalid_str_mv | en |
| network_acronym_str | LAURepo |
| network_name_str | Lebanese American University repository |
| oai_identifier_str | oai:laur.lau.edu.lb:10725/15388 |
| publishDate | 2014 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD ClustersKaitoua, Abdul RahmanHajj, HazemSaghir, Mazen A.R.Artail, HassanAkkary, HaithamAwad, MarietteSharafeddine, MagedaMershad, KhaleelIn this article, we propose new extensions to Hadoop to enable clusters of reconfigurable active solid-state drives (RASSDs) to process streaming data from SSDs using FPGAs. We also develop an analytical model to estimate the performance of RASSD clusters running under Hadoop. Using the Hadoop RASSD platform and network simulators, we validate our design and demonstrate its impact on performance for different workloads taken from Stanford's Phoenix MapReduce project. Our results show that for a hardware acceleration factor of 20×, compute-intensive workloads processing 153MB of data can run up to 11× faster than a standard Hadoop cluster.Published2024-03-07T11:25:59Z2024-03-07T11:25:59Z20142014-07-15Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1544-3566http://hdl.handle.net/10725/15388https://doi.org/10.1145/2608199Kaitoua, A., Hajj, H., Saghir, M. A., Artail, H., Akkary, H., Awad, M., ... & Mershad, K. (2014). Hadoop extensions for distributed computing on reconfigurable active SSD clusters. ACM Transactions on Architecture and Code Optimization (TACO), 11(2), 1-26.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttps://dl.acm.org/doi/abs/10.1145/2608199enACM Transactions on Architecture and Code Optimizationinfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/153882024-07-03T08:20:39Z |
| spellingShingle | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters Kaitoua, Abdul Rahman |
| status_str | publishedVersion |
| title | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| title_full | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| title_fullStr | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| title_full_unstemmed | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| title_short | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| title_sort | Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters |
| url | http://hdl.handle.net/10725/15388 https://doi.org/10.1145/2608199 http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://dl.acm.org/doi/abs/10.1145/2608199 |