一种优化的众核处理器核级冗余拓扑重构算法

发布时间：2018-06-16 19:03

本文选题：众核处理器 + 微体系结构级冗余　；参考：《计算机工程》2015年05期

【摘要】：现有的行波列借拓扑重构算法是基于分级优化思想,把整体优化问题分解为以失效核为中心的局部优化问题,通过局部搜索失效核重构的最优解来求解整体优化问题的最优解。但其在局部邻域进行的是单向搜索,易导致搜索到的解并不是局部最优解,或者前一单元依次占用下一单元最优解而导致连锁列借操作。针对上述情况,构造一种局部邻域双向搜索的优化行波列借算法,可使局部解更优,并避免连锁操作。实验结果表明,该算法在失效核数目较多的情况下,与原有行波列借算法相比,众核处理器虚拟拓扑结构性能明显提高。
[Abstract]:The existing traveling wave train topology reconstruction algorithm is based on the idea of hierarchical optimization. The global optimization problem is decomposed into a local optimization problem centered on the failure kernel, and the optimal solution of the global optimization problem is solved by local searching the optimal solution of the failure kernel reconstruction. However, the local neighborhood is a one-way search, which easily leads to the search solution is not the local optimal solution, or the former unit occupies the next unit optimal solution in turn, which leads to the chain sequence borrowing operation. In view of the above situation, an optimal traveling wave train borrowing algorithm based on local neighborhood bidirectional search is constructed, which can make the local solution better and avoid the linkage operation. The experimental results show that compared with the original traveling wave train borrowing algorithm, the performance of the virtual topology of the multi-core processor is obviously improved when the number of failure cores is large.
【作者单位】：东华大学计算机科学与技术学院;广西财经学院信息与统计学院;
【基金】：国家自然科学基金资助项目(6126200) 中央高校基本科研业务费专项基金资助项目(11D11209)
【分类号】：TP301.6;TP332

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