Evaluating the combined impact of node architecture and cloud workload characteristics on network traffic and performance/cost

Diman Zad Tootaghaj, Farshid Farhat, Mohammad Arjomand, Paolo Faraboschi, Mahmut Taylan Kandemir, Anand Sivasubramaniam, Chita R. Das

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

The combined impact of node architecture and workload characteristics on off-chip network traffic with performance/cost analysis has not been investigated before in the context of emerging cloud applications. Motivated by this observation, this paper performs a thorough characterization of twelve cloud workloads using a full-system datacenter simulation infrastructure. We first study the inherent network characteristics of emerging cloud applications including message inter-arrival times, packet sizes, inter-node communication overhead, self-similarity, and traffic volume. Then, we study the effect of hardware architectural metrics on network traffic. Our experimental analysis reveals that (1) the message arrival times and packet-size distributions exhibit variances across different cloud applications, (2) the inter-arrival times imply a large amount of self-similarity as the number of nodes increase, (3) the node architecture can play a significant role in shaping the overall network traffic, and finally, (4) the applications we study can be broadly divided into those which perform better in a scale-out or scale-up configuration at node level and into two categories, namely, those that have long-duration, low-burst flows and those that have short-duration, high-burst flows. Using the results of (3) and (4), the paper discusses the performance/cost trade-offs for scale-out and scale-up approaches and proposes an analytical model that can be used to predict the communication and computation demand for different configurations. It is shown that the difference between two different node architecture's performance per dollar cost (under same number of cores system wide) can be as high as 154 percent which disclose the need for accurate characterization of cloud applications before wasting the precious cloud resources by allocating wrong architecture. The results of this study can be used for system modeling, capacity planning and managing heterogeneous resources for large-scale system designs.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE International Symposium on Workload Characterization, IISWC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages203-212
Number of pages10
ISBN (Electronic)9781509000883
DOIs
StatePublished - Oct 30 2015
EventIEEE International Symposium on Workload Characterization, IISWC 2015 - Atlanta, United States
Duration: Oct 4 2015Oct 6 2015

Publication series

NameProceedings - 2015 IEEE International Symposium on Workload Characterization, IISWC 2015

Conference

ConferenceIEEE International Symposium on Workload Characterization, IISWC 2015
CountryUnited States
CityAtlanta
Period10/4/1510/6/15

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

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  • Cite this

    Tootaghaj, D. Z., Farhat, F., Arjomand, M., Faraboschi, P., Kandemir, M. T., Sivasubramaniam, A., & Das, C. R. (2015). Evaluating the combined impact of node architecture and cloud workload characteristics on network traffic and performance/cost. In Proceedings - 2015 IEEE International Symposium on Workload Characterization, IISWC 2015 (pp. 203-212). [7314166] (Proceedings - 2015 IEEE International Symposium on Workload Characterization, IISWC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IISWC.2015.31