Empirical model-building and response surface
Empirical model-building and response surface
IEEE Transactions on Computers
Analysis of benchmark characteristics and benchmark performance prediction
ACM Transactions on Computer Systems (TOCS)
Computer architecture: a quantitative approach
Computer architecture: a quantitative approach
The Case for Application-Specific Benchmarking
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Memory System Behavior of Java-Based Middleware
HPCA '03 Proceedings of the 9th International Symposium on High-Performance Computer Architecture
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Performance debugging for distributed systems of black boxes
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Cross-architecture performance predictions for scientific applications using parameterized models
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A First-Order Superscalar Processor Model
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Performance directed energy management for main memory and disks
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An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Model-Driven Placement of Compute Tasks and Data in a Networked Utility
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Cache miss behavior: is it √2?
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Proceedings of the 15th international conference on Parallel architectures and compilation techniques
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ISPASS '04 Proceedings of the 2004 IEEE International Symposium on Performance Analysis of Systems and Software
Mercury and freon: temperature emulation and management for server systems
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A performance counter architecture for computing accurate CPI components
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OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Model-based resource provisioning in a web service utility
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
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Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
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VLDB '06 Proceedings of the 32nd international conference on Very large data bases
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Journal of Parallel and Distributed Computing
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As Internet services become ubiquitous, the selection and management of diverse server platforms now affects the bottom line of almost every firm in every industry. Ideally, such cross-platform management would yield high performance at low cost, but in practice, the performance consequences of such decisions are often hard to predict. In this paper, we present an approach to guide cross-platform management for real-world Internet services. Our approach is driven by a novel performance model that predicts application-level performance across changes in platform parameters, such as processor cache sizes, processor speeds, etc., and can be calibrated with data commonly available in today's production environments. Our model is structured as a composition of several empirically observed, parsimonious sub-models. These sub-models have few free parameters and can be calibrated with lightweight passive observations on a current production platform. We demonstrate the usefulness of our cross-platform model in two management problems. First, our model provides accurate performance predictions when selecting the next generation of processors to enter a server farm. Second, our model can guide platform-aware load balancing across heterogeneous server farms.