NORMA eResearch @NCI Library

Benchmarking the Cloud: A Users Perspective

Dave, Khushal (2014) Benchmarking the Cloud: A Users Perspective. Masters thesis, Dublin, National College of Ireland.

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The increasing popularity of cloud computing and various options have manifolded over time. The foremost question in front of cloud users is how to precisely measure the performance capabilities of various options. The criteria for measuring performance could vary from measuring cost to floating point operations per second (FLOPS) or data manipulation (I/O).

Present benchmarking tools like Linpack, which measures performance in FLOPS cannot evaluate the performance of multi-core instances. Being non-adaptive, these bench-
mark do not take system configuration and environment into consideration during testing. Currently, there are no properly designed benchmark suite which suitably adapts
itself according to the node resources.

This research work focus on the designing of a scientific benchmark suite which will provide the maximum FLOPS performance of a CC over various CPU intensive tests. This
will allow us to evaluate the performance on criterias like FLOPS and effect of multi-threading. This approach is completely automatized thus can be used on any compute
instance starting from single node to multi-node instances.

The intelligent identification of suitable load data for individual tests which is automatically decided by the resource specification and the execution environment. Here we are using different data types to simulate CPU intensive tasks. This benchmark suite can be suitably used for any instance size without modification. The results obtained
from these tests will allow the user to identify the suitable option amongst various CC.

The tool developed has been tested on Openstack and Azure instances and was able to provide the correct results to compare the performance. This can be easily used by any
naive user to compare the performance of various CC's thus, allows easy comparison of performance.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Master of Science in Cloud Computing
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 12 Dec 2014 11:15
Last Modified: 12 Dec 2014 11:29

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