Abstract
Power consumption is an increasingly limiting factor in modern ICT infrastructure, especially in the context of High Performance Computing. Common strategies to curb energy consumption are power capping, i.e. constraining the system power consumption within certain power budget, and Dynamic Voltage/Frequency Scaling, i.e. reducing the computing elements operating clock to decrease power usage. In this paper we tackle the frequency assignment problem in the context of a power capped system. We propose three approaches to solve the problem, a greedy algorithm, a CP model and MIP model. As a case study, we consider the Eurora supercomputer, hosted at CINECA computing center in Bologna. The experimental results show that the MIP approach outperforms the other methods when the problem is loosely constrained. With tighter bounds, the CP method can always find a solution, whereas the MIP fails to provide a solution for half of the considered instances.
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- 1.
Measured as FLOPS (floating point operations per second).
- 2.
This duration is the maximum allowed execution time declared by the user at submission time.
- 3.
We suppose that all jobs have already started, hence start-to-end relationships must already hold.
- 4.
In the current system running applications cannot be interrupted/restarted.
- 5.
A variable i is relaxed with probability \(P = \psi \frac{w_i}{\sum _{\forall i \in J} w_i} + (1-\psi ) \frac{1}{|J|} \) where \(w_i\) is the weight and \(\psi \in [0,1]\) is a real number.
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Acknowledgement
This work has been partially supported by European H2020 FET project OPRECOMP (g.a. 732631). We also want to thank CINECA and for granting us the access to their systems.
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Borghesi, A., Milano, M., Benini, L. (2019). Frequency Assignment in High Performance Computing Systems. In: Alviano, M., Greco, G., Scarcello, F. (eds) AI*IA 2019 – Advances in Artificial Intelligence. AI*IA 2019. Lecture Notes in Computer Science(), vol 11946. Springer, Cham. https://doi.org/10.1007/978-3-030-35166-3_11
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