ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters
Abstract—This paper presents an offloading framework-ORCA- to map I/O-intensive code to a cluster that consists of computing and storage nodes. To reduce data transmission among computing and storage nodes. our offloading framework partitions and schedules CPU-bound and I/O-bound modules to computin...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.637.4492 2023-05-15T17:53:02+02:00 ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters Ji Zhang Xunfei Jiang Yun Tian Xiao Qin Mohammed I. Alghamdi Maen Al Assaf Meikang Qiu The Pennsylvania State University CiteSeerX Archives application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.4492 http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.4492 http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf text ftciteseerx 2016-01-08T15:45:59Z Abstract—This paper presents an offloading framework-ORCA- to map I/O-intensive code to a cluster that consists of computing and storage nodes. To reduce data transmission among computing and storage nodes. our offloading framework partitions and schedules CPU-bound and I/O-bound modules to computing nodes and active storage nodes, respectively. From developer’s perspective, ORCA helps them to deal with execution-path control, offloading executable code, and data sharing over a network. Powered by the offloading APIs, de-velopers without any I/O offloading or network programming experience are allowed to write new I/O-intensive code running efficiently on clusters. We implement the ORCA framework on a cluster to quantitatively evaluate performance improvements offered by our approach. We run five real-world applications on both homogeneous and heterogeneous computing environments. Ex-perimental results show ORCA speeds up the performance of all the five tested applications by a factor of up to 90.1 % with an average of 75.5%. Moreover, the results confirm that ORCA reduces network burden imposed by I/O-intensive applications by a factor of anywhere between 35 to 68. Keywords-offloading; I/O intensive; I. Text Orca Unknown |
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Abstract—This paper presents an offloading framework-ORCA- to map I/O-intensive code to a cluster that consists of computing and storage nodes. To reduce data transmission among computing and storage nodes. our offloading framework partitions and schedules CPU-bound and I/O-bound modules to computing nodes and active storage nodes, respectively. From developer’s perspective, ORCA helps them to deal with execution-path control, offloading executable code, and data sharing over a network. Powered by the offloading APIs, de-velopers without any I/O offloading or network programming experience are allowed to write new I/O-intensive code running efficiently on clusters. We implement the ORCA framework on a cluster to quantitatively evaluate performance improvements offered by our approach. We run five real-world applications on both homogeneous and heterogeneous computing environments. Ex-perimental results show ORCA speeds up the performance of all the five tested applications by a factor of up to 90.1 % with an average of 75.5%. Moreover, the results confirm that ORCA reduces network burden imposed by I/O-intensive applications by a factor of anywhere between 35 to 68. Keywords-offloading; I/O intensive; I. |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Ji Zhang Xunfei Jiang Yun Tian Xiao Qin Mohammed I. Alghamdi Maen Al Assaf Meikang Qiu |
spellingShingle |
Ji Zhang Xunfei Jiang Yun Tian Xiao Qin Mohammed I. Alghamdi Maen Al Assaf Meikang Qiu ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
author_facet |
Ji Zhang Xunfei Jiang Yun Tian Xiao Qin Mohammed I. Alghamdi Maen Al Assaf Meikang Qiu |
author_sort |
Ji Zhang |
title |
ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
title_short |
ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
title_full |
ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
title_fullStr |
ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
title_full_unstemmed |
ORCA: An Offloading Framework for I/O-Intensive Applications on Clusters |
title_sort |
orca: an offloading framework for i/o-intensive applications on clusters |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.4492 http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf |
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Orca |
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Orca |
op_source |
http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.637.4492 http://www.eng.auburn.edu/~xqin/pubs/zhang_IPCCC12.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766160770295398400 |