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基于云進(jìn)化算法的3D NoC測試規劃
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(桂林電子科技大學(xué) 電子工程與自動(dòng)化學(xué)院,廣西 桂林 541004)

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許川佩(1968),女,教授,主要從事自動(dòng)測試總線(xiàn)與系統、集成電路測試理論與技術(shù)研究。

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TP306

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Test Scheduling for 3-D Network on Chip Based on Cloud Evolutionary Algorithm
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(School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004,China)

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    摘要:

    針對三維片上網(wǎng)絡(luò )(Three Dimensional Network-on-Chip, 3D NoC) IP核的測試問(wèn)題,采用云進(jìn)化算法優(yōu)化測試規劃,完成3D NoC測試;該方法首先通過(guò)平分搜索范圍的方式形成第一代種群,依據3D NoC結構特點(diǎn)建立功耗模型,在滿(mǎn)足功耗約束的情況下進(jìn)行測試,采用種群精英個(gè)體保留策略選擇優(yōu)秀個(gè)體,并利用云模型的隨機性和穩定性特點(diǎn)進(jìn)行迭代尋優(yōu),旨在降低總的測試時(shí)間,獲得最佳測試規劃;以ITC′02測試標準電路作為實(shí)驗對象,實(shí)驗結果表明,在獲得相同測試時(shí)間下,云進(jìn)化算法比遺傳算法具有更好的尋優(yōu)能力,收斂代數提高了約50%,有效提高了測試效率。

    Abstract:

    For the test scheduling of 3D NoC (Three Dimensional Network-on-Chip, 3D NoC) resources cores, this paper presents a test scheduling method based on cloud evolutionary algorithm to complete test. Firstly, formed the first generation of population by means of share the whole scope, secondly, established power model based on the structural characteristics of 3D NoC, then complete test under the condition of dual power consumption constrain, thirdly, select excellent individuals by use the population elite reserve strategy, finally, use the randomness and stable tendency property of cloud model complete the iterative optimization and then reduce the total test time. Experiments with ITC′02 test circuit as the simulation object, the experimental results show that, For the same test time, cloud evolution algorithm has better search ability than the genetic algorithm, convergence is improved by about 50%, and improve the efficiency of the test.

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許川佩,尹芝.基于云進(jìn)化算法的3D NoC測試規劃計算機測量與控制[J].,2014,22(10):3114-31163121.

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  • 在線(xiàn)發(fā)布日期: 2015-01-15
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