Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effecti...Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.展开更多
Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travell...Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travelled or time cost,and not the path simplicity.To balance these factors,this paper presented an algorithm to compute a path that not only possesses fewest turns but also is as short as possible by utilizing the breadth-first-search strategy.The proposed algorithm started searching from a starting point,and expanded layer by layer through searching zero-level reachable points until the endpoint is found,and then deleted unnecessary points in the reverse direction.The forward searching and backward cleaning strategies were presented to build a hierarchical graph of zero-level reachable points,and form a fewestturn-path graph(G^(*)).After that,a classic Dijkstra shortest path algorithm was executed on the G^(*) to obtain a fewestturn-and-shortest path.Comparing with the shortest path in Baidu map,the algorithm in this work has less than half of the turns but the nearly same length.The proposed fewest-turn-and-shortest path algorithm is proved to be more suitable for human beings according to human cognition research.展开更多
图是一种非常重要的数据结构形式,被广泛用于社交网络、交通网络和搜索引擎等领域。随着图数据规模爆发式增长,存储容量受限,分布式图计算成为处理大规模图数据的焦点。宽度优先搜索(breadth first search,BFS)算法是图遍历和许多图分...图是一种非常重要的数据结构形式,被广泛用于社交网络、交通网络和搜索引擎等领域。随着图数据规模爆发式增长,存储容量受限,分布式图计算成为处理大规模图数据的焦点。宽度优先搜索(breadth first search,BFS)算法是图遍历和许多图分析算法的基础,而在分布式图计算过程中存在严重的通信开销。针对上述问题,本文提出了一种综合的数据压缩编码优化方案,结合位图和变长压缩数组,通过更高的压缩率来降低数据通信开销;此外,还提出了一种点对点异步环形通信策略,进一步降低分布式图计算中计算-通信的同步开销。通过这些优化手段,本文在8节点的分布式集群上对优化后BFS算法的性能进行了系统评估,结果表明,当图数据规模为28时,优化后的BFS算法平均性能为46.79亿条边每秒遍历(giga-traversed edges per second,GTEPS),性能比优化前提升了接近7.82%。展开更多
针对当前CATIA软件存在三维公差标注功能操作繁琐、费时费力的问题,提出基于MBD(Model Based Definition)模型的三维尺寸公差自动标注方法。采用改进的广度优先搜索算法完整地遍历三维零件的结构树信息,分层访问所有的特征结构,获取包...针对当前CATIA软件存在三维公差标注功能操作繁琐、费时费力的问题,提出基于MBD(Model Based Definition)模型的三维尺寸公差自动标注方法。采用改进的广度优先搜索算法完整地遍历三维零件的结构树信息,分层访问所有的特征结构,获取包含于技术产品规范特征中的三维标注信息模块,通过筛选过滤提取尺寸标注信息;根据DT(Dimension-Tolerance)特征匹配公差信息,构建尺寸公差模型;通过CAA的二次开发接口,开发相应的功能模块,实现三维零件尺寸公差的自动标注。通过实例证明,该方法可以在三维零件设计时快速高效地提取所有三维尺寸标注信息,并实现三维环境下尺寸公差的自动标注。展开更多
基金Projects(61272142,61103082,61003075,61170261,61103193)supported by the National Natural Science Foundation of ChinaProject supported by the Program for New Century Excellent Talents in University of ChinaProjects(2012AA01A301,2012AA010901)supported by the National High Technology Research and Development Program of China
文摘Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.
基金This research was supported by the National Natural Science Foundation of China(Nos.41471332 and 41101354)the National High Technology Research and Development Program of China(863 Program)(No.2013AA12A302)+1 种基金the Fundamental Research Funds for the Central Universities(No.ZYGX2011J077)the Fund of China Scholarship Council.
文摘Many cognitive studies have indicated that the path simplicity may be as important as its distance travelled.However,the optimality of paths for current navigation system is often judged purely on the distance travelled or time cost,and not the path simplicity.To balance these factors,this paper presented an algorithm to compute a path that not only possesses fewest turns but also is as short as possible by utilizing the breadth-first-search strategy.The proposed algorithm started searching from a starting point,and expanded layer by layer through searching zero-level reachable points until the endpoint is found,and then deleted unnecessary points in the reverse direction.The forward searching and backward cleaning strategies were presented to build a hierarchical graph of zero-level reachable points,and form a fewestturn-path graph(G^(*)).After that,a classic Dijkstra shortest path algorithm was executed on the G^(*) to obtain a fewestturn-and-shortest path.Comparing with the shortest path in Baidu map,the algorithm in this work has less than half of the turns but the nearly same length.The proposed fewest-turn-and-shortest path algorithm is proved to be more suitable for human beings according to human cognition research.
文摘图是一种非常重要的数据结构形式,被广泛用于社交网络、交通网络和搜索引擎等领域。随着图数据规模爆发式增长,存储容量受限,分布式图计算成为处理大规模图数据的焦点。宽度优先搜索(breadth first search,BFS)算法是图遍历和许多图分析算法的基础,而在分布式图计算过程中存在严重的通信开销。针对上述问题,本文提出了一种综合的数据压缩编码优化方案,结合位图和变长压缩数组,通过更高的压缩率来降低数据通信开销;此外,还提出了一种点对点异步环形通信策略,进一步降低分布式图计算中计算-通信的同步开销。通过这些优化手段,本文在8节点的分布式集群上对优化后BFS算法的性能进行了系统评估,结果表明,当图数据规模为28时,优化后的BFS算法平均性能为46.79亿条边每秒遍历(giga-traversed edges per second,GTEPS),性能比优化前提升了接近7.82%。
文摘针对当前CATIA软件存在三维公差标注功能操作繁琐、费时费力的问题,提出基于MBD(Model Based Definition)模型的三维尺寸公差自动标注方法。采用改进的广度优先搜索算法完整地遍历三维零件的结构树信息,分层访问所有的特征结构,获取包含于技术产品规范特征中的三维标注信息模块,通过筛选过滤提取尺寸标注信息;根据DT(Dimension-Tolerance)特征匹配公差信息,构建尺寸公差模型;通过CAA的二次开发接口,开发相应的功能模块,实现三维零件尺寸公差的自动标注。通过实例证明,该方法可以在三维零件设计时快速高效地提取所有三维尺寸标注信息,并实现三维环境下尺寸公差的自动标注。
