SSS

Author:

Du Gaoming1ORCID,Liu Guanyu1,Li Zhenmin1,Cao Yifan1,Zhang Duoli1,Ouyang Yiming1,Gao Minglun1,Lu Zhonghai2

Affiliation:

1. Hefei University of Technology, Tunxi Rd., Hefei, China

2. KTH, Stockholm, Sweden

Abstract

Network-on-Chip (NoC) has become the de facto communication standard for multi-core or many-core System-on-Chip (SoC) due to its scalability and flexibility. However, an important factor in NoC design is temperature, which affects the overall performance of SoC—decreasing circuit frequency, increasing energy consumption, and even shortening chip lifetime. In this article, we propose SSS, a self-aware SoC using a static-dynamic hybrid method that combines dynamic mapping and static mapping to reduce the hotspot temperature for NoC-based SoCs. First, we propose monitoring and thermal modeling for self-state sensoring. Then, in static mapping stage, we calculate the optimal mapping solutions under different temperature modes using the discrete firefly algorithm to help self-decision making. Finally, in dynamic mapping stage, we achieve dynamic mapping through configuring NoC and SoC sentient units for self-optimizing. Experimental results show that SSS has substantially reduced the peak temperature by up to 37.52%. The FPGA prototype proves the effectiveness and smartness of SSS in reducing hotspot temperature.

Funder

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Electrical and Electronic Engineering,Hardware and Architecture,Software

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