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Power Supply Noise Aware Task Scheduling on Homogeneous 3D MPSoCs Considering the Thermal Constraint

Power Supply Noise Aware Task Scheduling on Homogeneous 3D MPSoCs Considering the Thermal Constraint
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摘要 Thanks to the emerging 3D integration technology, The multiprocessor system on chips (MPSoCs) can now integrate more IP cores on chip with improved energy efficiency. However, several severe challenges also rise up for 3D ICs due to the die-stacking architecture. Among them, power supply noise becomes a big concern. In the paper, we investigate power supply noise (PSN) interactions among different cores and tiers and show that PSN variations largely depend on task assignments. On the other hand, high integration density incurs a severe thermal issue on 3D ICs. In the paper, we propose a novel task scheduling framework considering both the PSN and the thermal issue. It mainly consists of three parts. First, we extract current stimuli of running tasks by analyzing their power traces derived from architecture level simulations. Second, we develop an efficient power delivery network (PDN) solver to evaluate PSN magnitudes efficiently. Third, we propose a heuristic algorithm to solve the formulated task scheduling problem. Compared with the state-of-the-art task assignment algorithm, the proposed method can reduce PSN by 12% on a 2 × 2 × 2 3D MPSoCs and by 14% on a 3 × 3 × 3 3D MPSoCs. The end-to-end task execution time also improves as much as 5.5% and 7.8% respectively due to the suppressed PSN. Thanks to the emerging 3D integration technology, The multiprocessor system on chips (MPSoCs) can now integrate more IP cores on chip with improved energy efficiency. However, several severe challenges also rise up for 3D ICs due to the die-stacking architecture. Among them, power supply noise becomes a big concern. In the paper, we investigate power supply noise (PSN) interactions among different cores and tiers and show that PSN variations largely depend on task assignments. On the other hand, high integration density incurs a severe thermal issue on 3D ICs. In the paper, we propose a novel task scheduling framework considering both the PSN and the thermal issue. It mainly consists of three parts. First, we extract current stimuli of running tasks by analyzing their power traces derived from architecture level simulations. Second, we develop an efficient power delivery network (PDN) solver to evaluate PSN magnitudes efficiently. Third, we propose a heuristic algorithm to solve the formulated task scheduling problem. Compared with the state-of-the-art task assignment algorithm, the proposed method can reduce PSN by 12% on a 2 × 2 × 2 3D MPSoCs and by 14% on a 3 × 3 × 3 3D MPSoCs. The end-to-end task execution time also improves as much as 5.5% and 7.8% respectively due to the suppressed PSN.
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2018年第5期966-983,共18页 计算机科学技术学报(英文版)
基金 This work was supported by the National Natural Science Foundation of China under Grant Nos. 61401008 and 61602022, and the State Key Laboratory of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences, under Grant No. CARCH201602.
关键词 MPSoCs power supply noise (PSN) power delivery network (PDN) task scheduling algorithm TEMPERATURE 3D MPSoCs power supply noise (PSN) power delivery network (PDN) task scheduling algorithm temperature 3D
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