Resource Scaling Performance for Cache Intensive Algorithms in Windows Azure

Part of the Studies in Computational Intelligence book series (SCI, volume 511)


Customers usually expect linear performance increase for increased demand for renting resources from cloud. However, it is not always the case, although the cloud service provider offers the specified infrastructure. The real expectation is limited due to memory access type, how data fits in available cache, nature of programs (if they are computation-intensive, memory or cache demanding and intensive) etc. Cloud infrastructure in addition rises new challenges by offered resources via virtual machines. The ongoing open question is choosing what is better - usage of parallelization with more resources or spreading the job among several instances of virtual machines with less resources. In this paper we analyze behavior of Microsoft Windows Azure Cloud on different loads. We find the best way to scale the resources to speedup the calculations and obtain best performance for cache intensive algorithms.


Cloud Computing HPC Matrix Multiplication 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Information Sciences and Computer EngineeringSs. Cyril and Methodious UniversitySkoipjeMacedonia

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