Abstract
Recent studies have showed the effectiveness of job co-scheduling in alleviating shared-cache contention on Chip Multiprocessors. Although program inputs affect cache usage and thus cache contention significantly, their influence on co-scheduling remains unexplored. In this work, we measure that influence and show that the ability to adapt to program inputs is important for a co-scheduler to work effectively on Chip Multiprocessors. We then conduct an exploration in addressing the influence by constructing cross-input predictive models for some memory behaviors that are critical for a recently proposed co-scheduler. The exploration compares the effectiveness of both linear and non-linear regression techniques in the model building. Finally, we conduct a systematic measurement of the sensitivity of co-scheduling on the errors of the predictive behavior models. The results demonstrate the potential of the predictive models in guiding contention-aware co-scheduling.
Supported by the National Science Foundation (CNS-0720499) and IBM CAS Fellowship.
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Jiang, Y., Shen, X. (2008). Exploration of the Influence of Program Inputs on CMP Co-scheduling. In: Luque, E., Margalef, T., Benítez, D. (eds) Euro-Par 2008 – Parallel Processing. Euro-Par 2008. Lecture Notes in Computer Science, vol 5168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85451-7_29
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DOI: https://doi.org/10.1007/978-3-540-85451-7_29
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