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Heterogeneity in “Homogeneous” Warehouse-Scale Computers: A Performance Opportunity
July-December 2011 (vol. 10 no. 2)
pp. 29-32
Jason Mars, University of Virginia, Charlottesville
Lingjia Tang, University of Virginia, Charlottesville
Robert Hundt, Google, Mountain View
The class of modern datacenters recently coined as “warehouse scale computers” (WSCs) has traditionally been embraced as homogeneous computing platforms. However, due to frequent machine replacements and upgrades, modern WSCs are in fact composed of diverse commodity microarchitectures and machine configurations. Yet, current WSCs are designed with an assumption of homogeneity, leaving a potentially significant performance opportunity unexplored. In this paper, we investigate the key factors impacting the available heterogeneity in modern WSCs, and the benefit of exploiting this heterogeneity to maximize overall performance. We also introduce a new metric, opportunity factor, which can be used to quantify an application’s sensitivity to the heterogeneity in a given WSC. For applications that are sensitive to heterogeneity, we observe a performance improvement of up to 70% when employing our approach. In a WSC composed of state-of-the-art machines, we can improve the overall performance of the entire datacenter by 16% over the status quo.
Index Terms:
System architectures, integration and modeling, Distributed architectures, Design studies, Super (very large) computers
Citation:
Jason Mars, Lingjia Tang, Robert Hundt, "Heterogeneity in “Homogeneous” Warehouse-Scale Computers: A Performance Opportunity," IEEE Computer Architecture Letters, vol. 10, no. 2, pp. 29-32, July-Dec. 2011, doi:10.1109/L-CA.2011.14
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