Abstract
In this paper, we propose an improved model for predicting HPL (High performance Linpack) performance. In order to accurately predict the maximal LINPACK performance we first divide the performance model into two parts: computational cost and message passing overhead. In the message passing overhead, we adopt Xu and Hwang’s broadcast model instead of the point-to-point message passing model. HPL performance prediction is a multi-variables problem. In this proposed model we improved the existing model by introducing a weighting function to account for many effects such that the proposed model could more accurately predict the maximal LINPACK performance R max . This improvement in prediction accuracy has been verified on a variety of architectures, including IA64 and IA32 CPUs in a Myrinet-based environment, as well as in Quadrics, Gigabits Ethernet and other network environments. Our improved model can help cluster users in estimating the maximal HPL performance of their systems.
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Chou, CY., Chang, HY., Wang, ST., Huang, KC., Shen, CY. (2007). An Improved Model for Predicting HPL Performance. In: Cérin, C., Li, KC. (eds) Advances in Grid and Pervasive Computing. GPC 2007. Lecture Notes in Computer Science, vol 4459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72360-8_14
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DOI: https://doi.org/10.1007/978-3-540-72360-8_14
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