Energy-efficient NoC with multi-granularity power optimization.

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Bibliographic Details
Title:	Energy-efficient NoC with multi-granularity power optimization.
Authors:	Wu, Ji¹ wu_ji2012@163.com, Dong, Dezun¹ dong@nudt.edu.cn, Liao, Xiangke¹, Wang, Li¹
Source:	Journal of Supercomputing. Apr2017, Vol. 73 Issue 4, p1654-1671. 18p.
Subjects:	Networks on a chip, Energy consumption of computers, Computer network architectures, Algorithms, Systems on a chip
Abstract:	As the core count grows rapidly, NoC (Network-on-Chip) consumes an increasing fraction of the modern processors/SoCs (System-on-Chips) power. It is thus very important to design energy-efficient NoC architecture. Multi-NoC (Multiple Network-on-Chip) has demonstrated its advantages in power gating for reducing leakage power, which constitutes a significant fraction of NoC power. In this paper, we propose Chameleon, a novel heterogeneous Multi-NoC design. Chameleon employs a fine-grained power gating algorithm which exploits power saving opportunities at different levels of granularity simultaneously. Integrated with a congestion-aware traffic allocation policy, Chameleon is able to achieve both high performance and low power at varying network utilization. Our experimental results on both synthetic and real workloads show that Chameleon delivers an average of 2.61 % higher performance than Catnap, the best in the literature. More importantly, Chameleon consumes an average of 27.75 % less power than Catnap. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	As the core count grows rapidly, NoC (Network-on-Chip) consumes an increasing fraction of the modern processors/SoCs (System-on-Chips) power. It is thus very important to design energy-efficient NoC architecture. Multi-NoC (Multiple Network-on-Chip) has demonstrated its advantages in power gating for reducing leakage power, which constitutes a significant fraction of NoC power. In this paper, we propose Chameleon, a novel heterogeneous Multi-NoC design. Chameleon employs a fine-grained power gating algorithm which exploits power saving opportunities at different levels of granularity simultaneously. Integrated with a congestion-aware traffic allocation policy, Chameleon is able to achieve both high performance and low power at varying network utilization. Our experimental results on both synthetic and real workloads show that Chameleon delivers an average of 2.61 % higher performance than Catnap, the best in the literature. More importantly, Chameleon consumes an average of 27.75 % less power than Catnap. [ABSTRACT FROM AUTHOR]
ISSN:	09208542
DOI:	10.1007/s11227-016-1859-8