Optimal Scheduling Algorithms of System Chip Power Density Based on Network on Chip

Author(s):  
Jiashen Li ◽  
Yun Pan
Author(s):  
Jiashen Li ◽  
◽  
Yun Pan ◽  

The improvement of chip integration leads to the increase of power density of system chips, which leads to the overheating of system chips. When dispatching the power density of system chips, some working modules are selectively closed to avoid all modules on the chip being turned on at the same time and to solve the problem of overheating. Taking 2D grid-on-chip network as the research object, an optimal scheduling algorithm of system-on-chip power density based on network-on-chip (NoC) is proposed. Under the constraints of thermal design power (TDP) and system, dynamic programming algorithm is used to solve the optimal application set throughput allocation from bottom to top by dynamic programming for the number and frequency level of each application configuration processor under the given application set of network-on-chip. On this basis, the simulated annealing algorithm is used to complete the application mapping aiming at heat dissipation effect and communication delay. The open and closed processor layout is determined. After obtaining the layout results, the TDP is adjusted. The maximum TDP constraint is iteratively searched according to the feedback loop of the system over-hot spots, and the power density scheduling performance of the system chip is maximized under this constraint, so as to ensure the system core. At the same time, chip throughput can effectively solve the problem of chip overheating. The experimental results show that the proposed algorithm increases the system chip throughput by about 11%, improves the system throughput loss, and achieves a balance between the system chip power consumption and scheduling time.


2015 ◽  
Vol 25 (01) ◽  
pp. 1640003 ◽  
Author(s):  
Yingnan Cui ◽  
Wei Zhang ◽  
Vivek Chaturvedi ◽  
Weichen Liu ◽  
Bingsheng He

Three-dimensional network-on-chip (3D-NoC) emerges as a potential multi-core architecture delivering high performance, high energy efficiency and great scalability. However, 3D-NoC suffers from severe thermal problems due to its high power density. To solve this problem, thermal-aware scheduling is an effective solution. However, the high complexity of the thermal model of 3D-NoC becomes a major hurdle for developing efficient thermal-aware scheduling algorithms for 3D-NoC. In this paper, we propose a novel thermal-aware task scheduling scheme named as the Bottom-to-Top (B2T) approach to address this challenge. This heuristic-based method performs task allocation on processing units to efficiently minimize the peak temperature and improve the execution time of the tasks with low complexity. The algorithm is first designed for two-layer 3D-NoC and then extended to 3D-NoC with an arbitrary number of layers. When compared to traditional thermal-aware scheduling algorithms designed for 2D-NoC, our B2T algorithm can achieve significant peak temperature reduction (up to 11.9[Formula: see text]C) and performance improvement (up to 4%) on two-layer 3D-NoC. The improvement becomes more significant as the number of layers in 3D-NoC increases. For four-layer 3D-NoC, the improvement is up to [Formula: see text]C peak temperature reduction.


2014 ◽  
Vol 35 (2) ◽  
pp. 341-346
Author(s):  
Xiao-fu Zheng ◽  
Hua-xi Gu ◽  
Yin-tang Yang ◽  
Zhong-fan Huang

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