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QoS policies and architecture for cache/memory in CMP platforms
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Joint International Conference on Measurement and Modeling of Computer Systems archive
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems table of contents
San Diego, California, USA
SESSION: Storage table of contents
Pages: 25 - 36  
Year of Publication: 2007
ISBN:978-1-59593-639-4
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Authors
Ravi Iyer  Intel Corporation
Li Zhao  Intel Corporation
Fei Guo  North Carolina State University
Ramesh Illikkal  Intel
Srihari Makineni  Intel
Don Newell  Intel
Yan Solihin  North Carolina State University
Lisa Hsu  University of Michigan
Steve Reinhardt  University of Michigan
Sponsors
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

As we enter the era of CMP platforms with multiple threads/cores on the die, the diversity of the simultaneous workloads running on them is expected to increase. The rapid deployment of virtualization as a means to consolidate workloads on to a single platform is a prime example of this trend. In such scenarios, the quality of service (QoS) that each individual workload gets from the platform can widely vary depending on the behavior of the simultaneously running workloads. While the number of cores assigned to each workload can be controlled, there is no hardware or software support in today's platforms to control allocation of platform resources such as cache space and memory bandwidth to individual workloads. In this paper, we propose a QoS-enabled memory architecture for CMP platforms that addresses this problem. The QoS-enabled memory architecture enables more cache resources (i.e. space) and memory resources (i.e. bandwidth) for high priority applications based on guidance from the operating environment. The architecture also allows dynamic resource reassignment during run-time to further optimize the performance of the high priority application with minimal degradation to low priority. To achieve these goals, we will describe the hardware/software support required in the platform as well as the operating environment (O/S and virtual machine monitor). Our evaluation framework consists of detailed platform simulation models and a QoS-enabled version of Linux. Based on evaluation experiments, we show the effectiveness of a QoS-enabled architecture and summarize key findings/trade-offs.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ravi Iyer: colleagues
Li Zhao: colleagues
Fei Guo: colleagues
Ramesh Illikkal: colleagues
Srihari Makineni: colleagues
Don Newell: colleagues
Yan Solihin: colleagues
Lisa Hsu: colleagues
Steve Reinhardt: colleagues