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
Web crawlers are an important part of modern search engines.With the development of the times,data has exploded and humans have entered a“big data era”.For example,Wikipedia carries the knowledge from all over the w...Web crawlers are an important part of modern search engines.With the development of the times,data has exploded and humans have entered a“big data era”.For example,Wikipedia carries the knowledge from all over the world,records the realtime news that occurs every day,and provides users with a good database of data,but because of the large amount of data,it puts a lot of pressure on users to search.At present,single-threaded crawling data can no longer meet the requirements of text crawling.In order to improve the performance and program versatility of single-threaded crawlers,a high-speed multi-threaded web crawler is designed to crawl the network hyper-scale text database.Multi-threaded crawling uses multiple threads to process web pages in parallel,combining breadth-first and depth-first algorithms to control web crawling.The practice project is based on the Python language to achieve multi-threaded optimization network hyper-large-scale text database-Wikipedia book crawling method,the project is inspired by the article on the Wikipedia article in the Big Data Digest public number.展开更多
This paper introduces the general process of the search algorithm Structure through the knight problem. According to the characteristics of the problem, we detailed discuss the DFS（Depth First Search） algorithm and ...This paper introduces the general process of the search algorithm Structure through the knight problem. According to the characteristics of the problem, we detailed discuss the DFS（Depth First Search） algorithm and BFS（Breadth First Search） algorithm, and combine the two algorithms together to solve the knights coverage problem. This article has a good reference for the mixed-use scenarios which requires a variety of search algorithms.展开更多
首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率...首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率角和潮流转移灵敏度)分别进行定义。提出潮流转移模型及其灵敏度的表达式。提出安全评估的评估方法,建立安全评估的数学模型,最终得到安全评估的综合指标,并阐述了指标的使用。开发潮流转移灵敏度及安全评估程序,利用该程序对真实电网算例进行仿真验证。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 is funded by the Open Foundation for the University Innovation Platform in the Hunan Province,grant number 16K013Hunan Provincial Natural Science Foundation of China,grant number 2017JJ2016+2 种基金2016 Science Research Project of Hunan Provincial Department of Education,grant number 16C0269.Accurate crawler design and implementation with a data cleaning function,National Students innovation and entrepreneurship of training program,grant number 201811532010.This research work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province.Open Foundation for the University Innovation Platform in the Hunan Province,grant number 16K013Hunan Provincial Natural Science Foundation of China,grant number 2017JJ20162016 Science Research Project of Hunan Provincial Department of Education,grant number 16C0269.This research work is implemented at the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province.Open project,grant number 20181901CRP03,20181901CRP04,20181901CRP05.
文摘Web crawlers are an important part of modern search engines.With the development of the times,data has exploded and humans have entered a“big data era”.For example,Wikipedia carries the knowledge from all over the world,records the realtime news that occurs every day,and provides users with a good database of data,but because of the large amount of data,it puts a lot of pressure on users to search.At present,single-threaded crawling data can no longer meet the requirements of text crawling.In order to improve the performance and program versatility of single-threaded crawlers,a high-speed multi-threaded web crawler is designed to crawl the network hyper-scale text database.Multi-threaded crawling uses multiple threads to process web pages in parallel,combining breadth-first and depth-first algorithms to control web crawling.The practice project is based on the Python language to achieve multi-threaded optimization network hyper-large-scale text database-Wikipedia book crawling method,the project is inspired by the article on the Wikipedia article in the Big Data Digest public number.
文摘This paper introduces the general process of the search algorithm Structure through the knight problem. According to the characteristics of the problem, we detailed discuss the DFS（Depth First Search） algorithm and BFS（Breadth First Search） algorithm, and combine the two algorithms together to solve the knights coverage problem. This article has a good reference for the mixed-use scenarios which requires a variety of search algorithms.
文摘首先分析潮流转移的原因及伴随的现象。其次讨论潮流转移区域以及区域界定,对传统广度优先遍历(breadth first search,BFS)算法进行改进,提出潮流转移影响区域的界定方法。对安全评估工作的理论基础——3个基本概念(模型量化、平均功率角和潮流转移灵敏度)分别进行定义。提出潮流转移模型及其灵敏度的表达式。提出安全评估的评估方法,建立安全评估的数学模型,最终得到安全评估的综合指标,并阐述了指标的使用。开发潮流转移灵敏度及安全评估程序,利用该程序对真实电网算例进行仿真验证。
