Cloud Benchmarking for Maximising Performance of Scientific Applications

Varghese, Blesson; Akgün, Özgür; Miguel, Ian; Thai, Long; Barker, Adam

doi:10.1109/tcc.2016.2603476

Cited by 21 publications

(20 citation statements)

References 38 publications

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“…Performance is measured on the cloud using a variety of techniques, such as benchmarking to facilitate the selection of resources that maximise performance of an application and periodic monitoring of the resources to ensure whether user-defined service level objectives are achieved [112,113,114,115]. Existing techniques are suitable in the cloud context since they monitor nodes that are solely used for executing the workloads [116,117].…”

Section: Offering Efficient Management Strategies In the Computing Ecmentioning

confidence: 99%

Next generation cloud computing: New trends and research directions

Varghese

Buyya

2018

Future Generation Computer Systems

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621

270

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The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.

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Section: Offering Efficient Management Strategies In the Computing Ecmentioning

confidence: 99%

Next generation cloud computing: New trends and research directions

Varghese

Buyya

2018

Future Generation Computer Systems

Self Cite

621

270

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“…The application benchmarks consist of a Molecular Dynamics Simulation (MDSim) from the scientific computing domain and a Word-Press Benchmark (WPBench) from the Web serving domain. MDSim is similarly used as an example of a scientific computing application in previous work [14] and WordPress was chosen because it is the most popular Content Management System (CMS) software (60% market share) used by 30% of the top 10 million websites (as of March 2017 from W3Techs 5 ) and it also has been used previously for benchmarking cloud VMs [13]. The WPBench implements three user scenarios, which capture short read, search, and write blogging browser sessions.…”

Section: Methodsmentioning

confidence: 99%

“…Researchers propose new cloud-specific application benchmarks [9], [10] and evaluate their performance [11]- [13] in cloud environments. Extensive studies have been conducted to collect microbenchmark measurements for many different VM configurations [2]- [4], [14]. However, it remains unclear how relevant these artificial benchmarks are to gain insights into the performance of real-world applications.…”

Section: Introductionmentioning

confidence: 99%

Estimating Cloud Application Performance Based on Micro-Benchmark Profiling

Scheuner

Leitner

2018

2018 IEEE 11th International Conference on Cloud Computing (CLOUD)

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The continuing growth of the cloud computing market has led to an unprecedented diversity of cloud services. To support service selection, micro-benchmarks are commonly used to identify the best performing cloud service. However, it remains unclear how relevant these synthetic micro-benchmarks are for gaining insights into the performance of real-world applications.Therefore, this paper develops a cloud benchmarking methodology that uses micro-benchmarks to profile applications and subsequently predicts how an application performs on a wide range of cloud services. A study with a real cloud provider (Amazon EC2) has been conducted to quantitatively evaluate the estimation model with 38 metrics from 23 micro-benchmarks and 2 applications from different domains. The results reveal remarkably low variability in cloud service performance and show that selected micro-benchmarks can estimate the duration of a scientific computing application with a relative error of less than 10% and the response time of a Web serving application with a relative error between 10% and 20%. In conclusion, this paper emphasizes the importance of cloud benchmarking by substantiating the suitability of micro-benchmarks for estimating application performance in comparison to common baselines but also highlights that only selected micro-benchmarks are relevant to estimate the performance of a particular application.

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“…Workload management is underpinned by benchmarking techniques that are used for workload placement and scheduling techniques. Current benchmarking practices are reasonably mature for the first level of heterogeneity and are developing for the second level [131,213]. However, significant research is still required to predict workload performance given the heterogeneity at the hardware architecture level.…”

Section: Heterogeneitymentioning

confidence: 99%

A Manifesto for Future Generation Cloud Computing

et al. 2018

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The Cloud computing paradigm has revolutionised the computer science horizon during the past decade and has enabled the emergence of computing as the fifth utility. It has captured significant attention of academia, industries, and government bodies. Now, it has emerged as the backbone of modern economy by offering subscription-based services anytime, anywhere following a pay-as-you-go model. This has instigated (1) shorter establishment times for start-ups, (2) creation of scalable global enterprise applications, (3) better cost-to-value associativity for scientific and high performance computing applications, and (4) different invocation/execution models for pervasive and ubiquitous applications. The recent technological developments and paradigms such as serverless computing, software-defined networking, Internet of Things, and processing at network edge are creating new opportunities for Cloud computing. However, they are also posing several new challenges and creating the need for new approaches and research strategies, as well as the re-evaluation of the models that were developed to * Corresponding

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Cloud Benchmarking for Maximising Performance of Scientific Applications

Cited by 21 publications

References 38 publications

Next generation cloud computing: New trends and research directions

Next generation cloud computing: New trends and research directions

Estimating Cloud Application Performance Based on Micro-Benchmark Profiling

A Manifesto for Future Generation Cloud Computing

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