C3Map and ARPSO based mapping algorithms for energy-efficient regular 3-D NoC architectures

Bhardwaj, Kartikeya; Mane, Pravin

doi:10.1109/vlsi-dat.2014.6834909

Cited by 11 publications

(9 citation statements)

References 4 publications

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“…Many researchers have done lots of work on multi-objective mapping. Some studies are done to optimise one metric (reliability, communication energy, temperature or performance) [5][6][7][8][9][10]. Some studies are done to optimise two or three metrics [2,11,12].…”

Section: Introductionmentioning

confidence: 99%

Unified multi‐objective mapping for network‐on‐chip using genetic‐based hyper‐heuristic algorithms

Liu

Yang

2018

IET Computers & Digital Techniques

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In this study, a flexible energy-and delay-aware mapping approach is proposed for the co-optimisation of energy consumption and communication latency for network-on-chips (NoCs). A novel genetic-based hyper-heuristic algorithm (GHA) is proposed as the core algorithm. This algorithm consists of bottom-level optimisation which includes a variety of operators and top-level optimisation which selects suitable operators through a 'reward' mechanism. As this algorithm can select suitable operators automatically during the mapping process, it noticeably improves convergence speed and demonstrates excellent stability. Compared to the random algorithm, GHA can achieve on average 23.28% delay reduction and 11.81% power reduction. Compared to state-of-the-art mapping algorithms, GHA produces improved mapping results with less time, especially when the size of NoC is large.

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Section: Introductionmentioning

confidence: 99%

Unified multi‐objective mapping for network‐on‐chip using genetic‐based hyper‐heuristic algorithms

Liu

Yang

2018

IET Computers & Digital Techniques

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“…In this paper, the bit energy values for the link and the router is set to 0.449 pJ and 4.171 pJ, respectively according to [5].…”

Section: Energy Modelmentioning

confidence: 99%

“…Some are based on heuristic algorithms, such as genetic algorithm (GA), Simulated Annealing algorithm (SA), Particle Swarm algorithm (PS) and so on [3,4,5]. The others are based on specialized algorithms for NoC mapping [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

An efficient energy and thermal-aware mapping for regular network-on-chip

Liu

Zhu

et al. 2017

IEICE Electron. Express

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Chip temperature and energy consumption become one of the most critical design issues with technology scaling to nanometre-scale, especially for NoC systems with large number of cores and shrunken core size. To balance the temperature and energy consumption on NoC-based multi-cores system, this paper proposes an efficient NoC mapping approach in which the hyper-heuristic algorithm based on genetic operators (HAGO) is the core of this approach. Compared to simulated annealing algorithm and genetic algorithm, HAGO demonstrates a faster convergence speed and excellent stability. Experimental results show that our proposed mapping approach can make a better balance between energy consumption and temperature, which reduces the peak temperature from 365.2 K to 352 K and only increases the energy consumption by 1.12%.

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“…To map k IP cores on n network nodes ( k ≤ n ), the possible core arrangements ( N _ag) on the NoC network is given by:

N_{ag} = \frac{n!}{()(, n - k)!} .

Therefore, it is a combinatorial optimisation problem that requires efficient heuristic algorithms to get solutions. Different heuristic algorithms have been proposed in the literature which try to get the best answer in the limited computing resources, such as BMAP (batch Markovian arrival process), SMAP (smart mobile access point), NMAP (near‐optimal mapping), SA (simulated annealing algorithm), PSO (particle swarm optimisation), GA (genetic algorithm), ACO (ant colony optimisation), GHA (genetic‐based hyper‐heuristic algorithm), [7–15]. GA is a very efficient algorithm which is often used in NoC mapping solutions, [14, 16–18].…”

Section: Introductionmentioning

confidence: 99%

Network‐on‐chip heuristic mapping algorithm based on isomorphism elimination for NoC optimisation

Weng

Liu

Yang

2020

IET Computers & Digital Techniques

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C3Map and ARPSO based mapping algorithms for energy-efficient regular 3-D NoC architectures

Cited by 11 publications

References 4 publications

Unified multi‐objective mapping for network‐on‐chip using genetic‐based hyper‐heuristic algorithms

Unified multi‐objective mapping for network‐on‐chip using genetic‐based hyper‐heuristic algorithms

An efficient energy and thermal-aware mapping for regular network-on-chip

Network‐on‐chip heuristic mapping algorithm based on isomorphism elimination for NoC optimisation

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