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Payload fragmentation framework for high-performance computing in cloud environment.

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Title: Payload fragmentation framework for high-performance computing in cloud environment.
Authors: Srinivasan, R.1, Elijah Blessing, R.1, Vivek, V.1,2, Dhanasekaran, R.3
Source: Journal of Supercomputing. May2019, Vol. 75 Issue 5, p2789-2804. 16p.
Subjects: Cloud computing, Storage fragmentation (Computer science), Central processing units, C++, Compilers (Computer programs)
Abstract: Cloud computing environment delivers resources such as CPU cycles, storage, network service and memory through a web-based model. Users run their applications on remote infrastructure and get benefited more at a lesser cost. Compiling large-scale applications such as compiling GCC and compiling Clang in C and C++ environments where applications involve encryption breaking tools require extensive analysis. Lack of CPU cycles in consumer-grade computing will be detrimental to such applications. Fragmenting and distributing payloads across multiple clusters for such applications in a cloud-like environment is a challenging task. We have proposed a novel approach to perform payload distribution for users who want to run their computationally expensive tasks efficiently. The proposed framework has performed well compared to the 'traditional' payload execution policy. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Cloud computing environment delivers resources such as CPU cycles, storage, network service and memory through a web-based model. Users run their applications on remote infrastructure and get benefited more at a lesser cost. Compiling large-scale applications such as compiling GCC and compiling Clang in C and C++ environments where applications involve encryption breaking tools require extensive analysis. Lack of CPU cycles in consumer-grade computing will be detrimental to such applications. Fragmenting and distributing payloads across multiple clusters for such applications in a cloud-like environment is a challenging task. We have proposed a novel approach to perform payload distribution for users who want to run their computationally expensive tasks efficiently. The proposed framework has performed well compared to the 'traditional' payload execution policy. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Central processing units
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              Text: May2019
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