A mathematical model to calculate real cost/performance in software distributed shared memory on computing environments.
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| Title: | A mathematical model to calculate real cost/performance in software distributed shared memory on computing environments. |
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| Authors: | Khaneghah, Ehsan Mousavi1 EMousavi@Shahed.ac.ir, Shadnoush, Nosratollah2 Nosratollah.Shadnosh@Gmail.com, Ghobakhlou, Amir Hossein1 Amirh_gh@Outlook.com |
| Source: | Journal of Supercomputing. Apr2018, Vol. 74 Issue 4, p1715-1764. 50p. |
| Subjects: | Performance of distributed shared memory, Computer software costs, High performance computing, LINPACK (Computer system), Parallel programming |
| Abstract: | One of the important factors in high-performance computing (HPC) is the cost/performance ratio. Calculation of cost/performance ratio is the main criterion for the separation of hardware computing systems (supercomputers) from software computing systems (Cluster, Grid, Peer-to-Peer). There are various economic methods to calculate hardware cost. In addition, there are numerous methods in software engineering to calculate the cost of developing and programming the scientific and engineering software. The computing power in the aforementioned systems is basically calculated with programs like LINPACK and HPCL. The inter-process communication is considered as a variable in calculating the cost of executing the scientific programs, whose nature and amount depends on the program execution itself. As there is a high dependency of effective variables in cost calculation of inter-process communications during the program execution, it should be used for calculating the cost of any application. This paper complements the existing methods by presenting a more comprehensive and accurate method to calculate the real cost of distributed shared memory (DSM) mechanisms used by HPC Systems. Therefore, a systematic method has been used to achieve a whole equation for DSM costing, determine the effective factors of the cost, and propose a method based on costing economic methods. Effective parameters are classified into two groups, namely DSM-inhere dependent and application-specific dependent parameters. Each parameter is presented and discussed, and the correlation between them specifies the system’s weight on DSM real cost according to which the cost is modeled and validated analytically. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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