Thermal Model Identification of Computing Nodes in High-Performance Computing Systems

Thermal-aware design and online optimization of the cooling effort are becoming increasingly important in current and future high-performance computing (HPC) systems. A fundamental requirement to effectively develop such techniques is the availability of distributed and compact models representing t...

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Published in:	IEEE transactions on industrial electronics (1982) Vol. 67; no. 9; pp. 7778 - 7788
Main Authors:	Diversi, Roberto, Bartolini, Andrea, Benini, Luca
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Ambient temperature Autoregressive processes Computation Computational modeling Design optimization Floorplans High performance computing High-performance computing (HPC) systems Nodes supercomputing nodes System effectiveness System identification Temperature measurement Temperature sensors Thermal analysis thermal modeling Thermal noise Thermal response Thermodynamic properties
ISSN:	0278-0046, 1557-9948
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Abstract	Thermal-aware design and online optimization of the cooling effort are becoming increasingly important in current and future high-performance computing (HPC) systems. A fundamental requirement to effectively develop such techniques is the availability of distributed and compact models representing the system thermal behavior. System identification algorithms allow to extract models directly from the thermal response of the target device. This article proposes a novel thermal identification approach for real, in-production HPC systems, which is capable of extracting thermal models from a computing node affected by quantization noise on the temperature measurements as well as operating in the free-cooling mode, with variable ambient temperature. The approach allows also to identify the physical floorplan of the CPU dies in supercomputing nodes. The effectiveness of the proposed methodology has been tested on a node of the CINECA Galileo Tier-1 supercomputer system.
AbstractList	Thermal-aware design and online optimization of the cooling effort are becoming increasingly important in current and future high-performance computing (HPC) systems. A fundamental requirement to effectively develop such techniques is the availability of distributed and compact models representing the system thermal behavior. System identification algorithms allow to extract models directly from the thermal response of the target device. This article proposes a novel thermal identification approach for real, in-production HPC systems, which is capable of extracting thermal models from a computing node affected by quantization noise on the temperature measurements as well as operating in the free-cooling mode, with variable ambient temperature. The approach allows also to identify the physical floorplan of the CPU dies in supercomputing nodes. The effectiveness of the proposed methodology has been tested on a node of the CINECA Galileo Tier-1 supercomputer system.
Author	Diversi, Roberto Bartolini, Andrea Benini, Luca
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SubjectTerms	Algorithms Ambient temperature Autoregressive processes Computation Computational modeling Design optimization Floorplans High performance computing High-performance computing (HPC) systems Nodes supercomputing nodes System effectiveness System identification Temperature measurement Temperature sensors Thermal analysis thermal modeling Thermal noise Thermal response Thermodynamic properties
Title	Thermal Model Identification of Computing Nodes in High-Performance Computing Systems
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