Spallation Neutron Source Drift Tube Linac Resonance Control Cooling System Modeling

Feschenko, A.V.; Kiselev, Yu. V.; Kovalishin, A.S.; Kravchuk, L.; Kvasha, A.I.; Tang, Jun; Aleksandrov, A.; Champion, M.; Gibson, P.; Schubert, J.

doi:10.1109/pac.2005.1591605

Cited by 1 publication

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“…Thermal capacitor and resistor symbols denote the heat exchange points, while heat and cooling power sources are denoted with the symbol P , entering with positive sign in case of heat sources, and minus for cooling devices (while the subscript defines the component, and thus its heating or cooling role, as it will be clarified later on). The mathematical equations of such class of models will be derived assuming the ensuing hypothesis to hold true (the reader is referred to [37], [38] for detailed motivations and range of validity of the hypotheses) In addition, by virtue of what stated in Section 2 and similarly to what shown in related works (see for instance [34]), a uniform air temperature distribution is assumed for the racks, thus the computing system thermal behavior can be characterized by means of fewer state variables (temperatures), e.g. one for each line of racks.…”

Section: Framework For Holistic Hpc Thermal Modellingmentioning

confidence: 99%

HPC Cooling: A Flexible Modeling Tool for Effective Design and Management

Conficoni

Bartolini

Tilli

et al. 2021

IEEE Trans. Sustain. Comput.

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Complex computing platforms such as High Performance Computers and Data Centers are critical systems from the energy sustainability viewpoint, due to their high computational power and demanding thermal stability specifications. In this context, cooling is a crucial component to operate such systems efficiently. Adavanced solutions, based on liquid and hybrid topologies are available today, but they come with a twofold challenge. On one hand, as widely recognized in the literature, the cooling devices need to be operated in a coordinated and energy-efficient fashion. In addition, after design and deployment, the cooling system has to be dynamically managed to efficiently adapt to workload, and environmental conditions. On the other hand, at design time, the cooling hardware architecture has to be selected in order to fit in the best way the needs of the computing facility, also depending on the environmental conditions characterizing its location. This work presents a flexible, low-complexity modeling tool to describe the overall thermal behavior of complex computational platforms, as well as the effect of the diverse cooling components, and the corresponding energy consumption. Analytical modeling equations, stemming from physical first principles, are used, thus providing a compact and computationally manageable tool. This can be then exploited to explore the design space, choosing the correct cooling configuration, and/or define energy-optimal holistic cooling strategies, for complex, multidimensional, and hard constrained systems such as today SuperComputers. The proposed method is presented in general terms, then validated on a case study of a real-life HPC system with a hybrid cooling architecture.

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Section: Framework For Holistic Hpc Thermal Modellingmentioning

confidence: 99%