IEICE TRANSACTIONS on Electronics
Inverse Distance Weighting Method Based on a Dynamic Voronoi Diagram for Thermal Reconstruction with Limited Sensor Data on Multiprocessors
Summary :
With exponentially increasing power densities due to technology scaling and ever increasing demand for performance, chip temperature has become an important issue that limits the performance of computer systems. Typically, it is essential to use a set of on-chip thermal sensors to monitor temperatures during the runtime. The runtime thermal measurements are then employed by dynamic thermal management techniques to manage chip performance appropriately. In this paper, we propose an inverse distance weighting method based on a dynamic Voronoi diagram for the reconstruction of full thermal characterization of integrated circuits with non-uniform thermal sensor placements. Firstly we utilize the proposed method to transform the non-uniformly spaced samples to virtual uniformly spaced data. Then we apply three classical interpolation algorithms to reconstruct the full thermal signals in the uniformly spaced samples mode. To evaluate the effectiveness of our method, we develop an experiment for reconstructing full thermal status of a 16-core processor. Experimental results show that the proposed method significantly outperforms spectral analysis techniques, and can obtain full thermal characterization with an average absolute error of 1.72% using 9 thermal sensors per core.
- Publication
- IEICE TRANSACTIONS on Electronics Vol.E94-C No.8 pp.1295-1301
- Publication Date
- 2011/08/01
- Publicized
- Online ISSN
- 1745-1353
- DOI
- 10.1587/transele.E94.C.1295
- Type of Manuscript
- PAPER
- Category
- Electronic Components
Authors
Keyword
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Xin LI, Mengtian RONG, Tao LIU, Liang ZHOU, "Inverse Distance Weighting Method Based on a Dynamic Voronoi Diagram for Thermal Reconstruction with Limited Sensor Data on Multiprocessors" in IEICE TRANSACTIONS on Electronics,
vol. E94-C, no. 8, pp. 1295-1301, August 2011, doi: 10.1587/transele.E94.C.1295.
Abstract: With exponentially increasing power densities due to technology scaling and ever increasing demand for performance, chip temperature has become an important issue that limits the performance of computer systems. Typically, it is essential to use a set of on-chip thermal sensors to monitor temperatures during the runtime. The runtime thermal measurements are then employed by dynamic thermal management techniques to manage chip performance appropriately. In this paper, we propose an inverse distance weighting method based on a dynamic Voronoi diagram for the reconstruction of full thermal characterization of integrated circuits with non-uniform thermal sensor placements. Firstly we utilize the proposed method to transform the non-uniformly spaced samples to virtual uniformly spaced data. Then we apply three classical interpolation algorithms to reconstruct the full thermal signals in the uniformly spaced samples mode. To evaluate the effectiveness of our method, we develop an experiment for reconstructing full thermal status of a 16-core processor. Experimental results show that the proposed method significantly outperforms spectral analysis techniques, and can obtain full thermal characterization with an average absolute error of 1.72% using 9 thermal sensors per core.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/transele.E94.C.1295/_p
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@ARTICLE{e94-c_8_1295,
author={Xin LI, Mengtian RONG, Tao LIU, Liang ZHOU, },
journal={IEICE TRANSACTIONS on Electronics},
title={Inverse Distance Weighting Method Based on a Dynamic Voronoi Diagram for Thermal Reconstruction with Limited Sensor Data on Multiprocessors},
year={2011},
volume={E94-C},
number={8},
pages={1295-1301},
abstract={With exponentially increasing power densities due to technology scaling and ever increasing demand for performance, chip temperature has become an important issue that limits the performance of computer systems. Typically, it is essential to use a set of on-chip thermal sensors to monitor temperatures during the runtime. The runtime thermal measurements are then employed by dynamic thermal management techniques to manage chip performance appropriately. In this paper, we propose an inverse distance weighting method based on a dynamic Voronoi diagram for the reconstruction of full thermal characterization of integrated circuits with non-uniform thermal sensor placements. Firstly we utilize the proposed method to transform the non-uniformly spaced samples to virtual uniformly spaced data. Then we apply three classical interpolation algorithms to reconstruct the full thermal signals in the uniformly spaced samples mode. To evaluate the effectiveness of our method, we develop an experiment for reconstructing full thermal status of a 16-core processor. Experimental results show that the proposed method significantly outperforms spectral analysis techniques, and can obtain full thermal characterization with an average absolute error of 1.72% using 9 thermal sensors per core.},
keywords={},
doi={10.1587/transele.E94.C.1295},
ISSN={1745-1353},
month={August},}
Copy
TY - JOUR
TI - Inverse Distance Weighting Method Based on a Dynamic Voronoi Diagram for Thermal Reconstruction with Limited Sensor Data on Multiprocessors
T2 - IEICE TRANSACTIONS on Electronics
SP - 1295
EP - 1301
AU - Xin LI
AU - Mengtian RONG
AU - Tao LIU
AU - Liang ZHOU
PY - 2011
DO - 10.1587/transele.E94.C.1295
JO - IEICE TRANSACTIONS on Electronics
SN - 1745-1353
VL - E94-C
IS - 8
JA - IEICE TRANSACTIONS on Electronics
Y1 - August 2011
AB - With exponentially increasing power densities due to technology scaling and ever increasing demand for performance, chip temperature has become an important issue that limits the performance of computer systems. Typically, it is essential to use a set of on-chip thermal sensors to monitor temperatures during the runtime. The runtime thermal measurements are then employed by dynamic thermal management techniques to manage chip performance appropriately. In this paper, we propose an inverse distance weighting method based on a dynamic Voronoi diagram for the reconstruction of full thermal characterization of integrated circuits with non-uniform thermal sensor placements. Firstly we utilize the proposed method to transform the non-uniformly spaced samples to virtual uniformly spaced data. Then we apply three classical interpolation algorithms to reconstruct the full thermal signals in the uniformly spaced samples mode. To evaluate the effectiveness of our method, we develop an experiment for reconstructing full thermal status of a 16-core processor. Experimental results show that the proposed method significantly outperforms spectral analysis techniques, and can obtain full thermal characterization with an average absolute error of 1.72% using 9 thermal sensors per core.
ER -
English
