本文關鍵詞： 功能腦網(wǎng)絡 網(wǎng)絡屬性 圖像處理器 統(tǒng)一計算設備架構 加速比　出處：《計算機工程與設計》2017年06期 　論文類型：期刊論文

【摘要】：為實現(xiàn)大規(guī)模功能腦網(wǎng)絡拓撲屬性的高效計算,提出基于GPU并行的腦網(wǎng)絡屬性分析方法。采用統(tǒng)一計算設備CUDA架構,屬性分析方法中的計算密集型操作由GPU完成。以功能腦網(wǎng)絡為對象,在GPU型號為NVIDIA Quadro K4200的工作站上對該并行方法進行模擬,將該方法與基于單程序多數(shù)據(jù)SPMD機制的腦網(wǎng)絡屬性分析方法進行比較。實驗結果表明,當網(wǎng)絡節(jié)點數(shù)大于1000時,該方法具有更高的計算性能。
[Abstract]:For the efficient computation of large-scale functional brain networks topology, the brain network properties analysis method is proposed based on parallel GPU. Using CUDA Compute Unified Device Architecture, attribute analysis computation intensive methods of operation is completed by GPU. The functional brain network as the object, in the GPU model NVIDIA Quadro K4200 workstation for the parallel method by simulation, the method and the analysis method of the brain network properties of single program multiple data based on SPMD mechanism were compared. The experimental results show that when the network node number is greater than 1000, this method has higher computing performance.

【作者單位】： 太原理工大學計算機科學與技術學院;
【基金】：國家自然科學基金青年基金項目(61503273) 太原理工大學�；痦椖�(1205-04020202)
【分類號】：O157.5
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本文編號：1529110