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1. 扬州大学信息工程学院,江苏,扬州,225000
2. 南京航空航天大学电子信息工程学院,江苏,南京,210016
3. 扬州大学信息工程学院,江苏,扬州,225000
4. 南京航空航天大学电子信息工程学院,江苏,南京,210016
Published:2016
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A Predictive Thermal Model Combined with the Second Derivative for Multiprocessor System-on-Chips[J]. Acta Electronica Sinica, 2016, 44(6): 1272-1278.
A Predictive Thermal Model Combined with the Second Derivative for Multiprocessor System-on-Chips[J]. Acta Electronica Sinica, 2016, 44(6): 1272-1278. DOI: 10.3969/j.issn.0372-2112.2016.06.002.
区域温度预测是多处理器片上系统(MultiProcessor System-on-Chips
MPSoCs)高效散热的基础.本文以RC热传导(Thermal Resistance and Capacitance
Thermal RC)模型为基础
结合二阶导数提出了一种温度预测模型.该模型不仅可以在较低的运算复杂度下准确预测温度
而且能在固定的预测误差率范围内拓宽预测时间长度
进而减少模型在实际运行中被调用的次数
降低额外功耗.实验结果表明
相比现有的一次导数预测模型
在相同可接受误差率范围内
该模型能将预测时长拓宽至对比模型的1.6倍.同时
当预测时长拓展至2.5s时
该模型的预测准确率比对比模型高3.84%.
The regional temperature prediction is the basis of the efficient heat dissipation in multiprocessor system-on-chips (MPSoCs).Based on the thermal resistance and capacitance (Thermal RC) model
this paper proposed a predictive thermal model combined with the second derivative.It predicts the temperature accurately with low complexity
and increases the prediction time length within a certain prediction error range to reduce the number of times that the prediction module is invoked and the extra power consumption.Experimental results show that
compared to the existing model combined with the first derivative
the proposed model increases the prediction length by 1.6 times within the same acceptable prediction error range.When the prediction time length is increased to 2.5s
the prediction accuracy of the proposed model is 3.84% higher than that of the contrastive model.
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