Contention and Reliability-Aware Energy Efficiency Task Mapping on NoC-Based MPSoCs

被引:0
|
作者
Mo, Lei [1 ]
Li, Xinmei [1 ]
Kritikakou, Angeliki [2 ,3 ]
Zhai, Xiaojun [4 ]
机构
[1] Southeast Univ, Sch Automat, Nanjing 210096, Peoples R China
[2] Univ Rennes, CNRS, INRIA, IRISA, F-35042 Rennes, France
[3] Inst Univ France, F-75005 Paris, France
[4] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, Essex, England
基金
中国国家自然科学基金;
关键词
Contention-aware; energy management; network-on-chip (NoC); reliability-aware; task mapping; PERFORMANCE; SYSTEMS; NETWORK; TIME; CHIP; OPTIMIZATION;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Recently, network-on-chip (NoC)-based multiprocessor system-on-chips (MPSoCs) have become popular computing platforms for real-time applications due to high communication performance and energy efficiency over traditional bus-based MPSoCs. Due to the nature of network structures, network congestion along with transient faults, can significantly affect communication efficiency and system reliability. Most existing works have rarely focused on the concurrent optimization of network contention, reliability, and energy consumption. Here, we study the problem of contention and reliability-aware task mapping under real-time constraints for dynamic voltage and frequency scaling-enabled NoC. The problem entails optimizing voltage/frequency on cores and links to reduce energy consumption and ensure system reliability, while task mapping and slack time are adopted to alleviate network contention and reduce latency. We aim to minimize computation and communication energy and balance workload. This problem is formulated as a mixed-integer nonlinear programming, and we present an effective linearization scheme that equivalently transforms it into a mixed-integer linear programming to find the optimal solution. To reduce computation time, we propose a three-step heuristic, including task allocation, frequency scaling and edge scheduling, and communication contention management. Finally, we perform extensive simulations to evaluate the proposed method. The results show we can achieve 31.6% and 21.7% energy savings, with 95.5% and 98.6% less contention than the existing methods.
引用
收藏
页码:2010 / 2026
页数:17
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