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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lingjia Tang Mars, J. Xiao Zhang Hagmann, R. Hundt, R. Tune, E. |
| Copyright Year | 2013 |
| Description | Author affiliation: Univ. of California, San Diego, La Jolla, CA, USA (Lingjia Tang; Mars, J.) |
| Abstract | Due to the complexity and the massive scale of modern warehouse scale computers (WSCs), it is challenging to quantify the performance impact of individual microarchitectural properties and the potential optimization benefits in the production environment. As a result of these challenges, there is currently a lack of understanding of the microarchitecture-workload interaction, leaving potentially significant performance on the table. This paper argues for a two-phase performance analysis methodology for optimizing WSCs that combines both an in-production investigation and an experimental load-testing study. To demonstrate the effectiveness of this two-phase approach, and to illustrate the challenges, methodologies and opportunities in optimizing modern WSCs, this paper investigates the impact of non-uniform memory access (NUMA) for several Google's key web-service workloads in large-scale production WSCs. Leveraging a newly-designed metric and continuous large-scale profiling in live datacenters, our production analysis demonstrates that NUMA has a significant impact (10-20%) on two important web-services: Gmail backend and web-search frontend. Our carefully designed load-test further reveals surprising tradeoffs between optimizing for NUMA performance and reducing cache contention. |
| Starting Page | 188 |
| Ending Page | 197 |
| File Size | 462040 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467355858 |
| ISSN | 15300897 |
| e-ISBN | 9781467355872 |
| DOI | 10.1109/HPCA.2013.6522318 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-02-23 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Production Servers Microarchitecture Measurement Google Memory management Correlation |
| Content Type | Text |
| Resource Type | Article |
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