String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that...String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-core based environment. Experimental outcomes reveal that the overall performance of the mentioned string matching algorithm has been improved, and the improvement in the execution time which has been obtained is considerable enough to recommend the multi-core environment as the suitable platform for parallelizing the Quick Search string matching algorithm.展开更多
By studying the algorithms of single pattern matching, five factors that have effect on time complexity of the algorithm are analyzed. The five factors are： sorting the characters of pattern string in an increasing o...By studying the algorithms of single pattern matching, five factors that have effect on time complexity of the algorithm are analyzed. The five factors are： sorting the characters of pattern string in an increasing order of using frequency, utilizing already-matched pattern suffix information, utilizing already-matched pattern prefix information, utilizing the position factor which is absorbed from quick search algorithm, and utilizing the continue-skip idea which is originally proposed by this paper. Combining all the five factors, a new single pattern matching algorithm is implemented. It＇s proven by the experiment that the efficiency of new algorithm is the best of all algorithms.展开更多
Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Chan...Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.展开更多
This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on gra...This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on graphics processing unit(GPGPU)programming concepts to enhance performance and gain insight into the parallel versions of these algorithms.We have developed the CUDA-enhanced SMART(CUSMART)library,which incorporates parallelized iterations of 64 string matching algorithms,leveraging the CUDA application programming interface.The performance of these algorithms has been assessed across various scenarios to ensure a comprehensive and impartial comparison,allowing for the identification of their strengths and weaknesses in specific application contexts.We have explored and established optimization techniques to gauge their influence on the performance of these algorithms.The results of this study highlight the potential of GPGPU computing in string matching applications through the scalability of algorithms,suggesting significant performance improvements.Furthermore,we have identified the best and worst performing algorithms in various scenarios.展开更多
As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This pape...As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick （AC） algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.展开更多
文摘String matching is seen as one of the essential problems in computer science. A variety of computer applications provide the string matching service for their end users. The remarkable boost in the number of data that is created and kept by modern computational devices influences researchers to obtain even more powerful methods for coping with this problem. In this research, the Quick Search string matching algorithm are adopted to be implemented under the multi-core environment using OpenMP directive which can be employed to reduce the overall execution time of the program. English text, Proteins and DNA data types are utilized to examine the effect of parallelization and implementation of Quick Search string matching algorithm on multi-core based environment. Experimental outcomes reveal that the overall performance of the mentioned string matching algorithm has been improved, and the improvement in the execution time which has been obtained is considerable enough to recommend the multi-core environment as the suitable platform for parallelizing the Quick Search string matching algorithm.
基金the National Natural Science Foundation of China (Nos. 60502032 and 60672068)
文摘By studying the algorithms of single pattern matching, five factors that have effect on time complexity of the algorithm are analyzed. The five factors are： sorting the characters of pattern string in an increasing order of using frequency, utilizing already-matched pattern suffix information, utilizing already-matched pattern prefix information, utilizing the position factor which is absorbed from quick search algorithm, and utilizing the continue-skip idea which is originally proposed by this paper. Combining all the five factors, a new single pattern matching algorithm is implemented. It＇s proven by the experiment that the efficiency of new algorithm is the best of all algorithms.
文摘Pattern matching is a very important algorithm used in many applications such as search engine and DNA analysis. They are aiming to find a pattern in a text. This paper proposes a Pattern Matching Algorithm Using Changing Consecutive Characters (PMCCC) to make the searching pro- cess of the algorithm faster. PMCCC enhances the shift process that determines how the pattern moves in case of the occurrence of the mismatch between the pattern and the text. It enhances the Berry Ravindran (BR) shift function by using m consecutive characters where m is the pattern length. The formal basis and the algorithms are presented. The experimental results show that PMCCC made enhancements in searching process by reducing the number of comparisons and the number of attempts. Comparing the results of PMCCC with other related algorithms has shown significant enhancements in average number of comparisons and average number of attempts.
基金Project supported by the Scientific and Technological Research Council of Türkiye(No.117E142)Open access funding provided by the Scientific and Technological Research Council of Türkiye(TÜBİTAK)。
文摘This study presents a parallel version of the string matching algorithms research tool(SMART)library,implemented on NVIDIA’s compute unified device architecture(CUDA)platform,and uses general-purpose computing on graphics processing unit(GPGPU)programming concepts to enhance performance and gain insight into the parallel versions of these algorithms.We have developed the CUDA-enhanced SMART(CUSMART)library,which incorporates parallelized iterations of 64 string matching algorithms,leveraging the CUDA application programming interface.The performance of these algorithms has been assessed across various scenarios to ensure a comprehensive and impartial comparison,allowing for the identification of their strengths and weaknesses in specific application contexts.We have explored and established optimization techniques to gauge their influence on the performance of these algorithms.The results of this study highlight the potential of GPGPU computing in string matching applications through the scalability of algorithms,suggesting significant performance improvements.Furthermore,we have identified the best and worst performing algorithms in various scenarios.
基金the Juniper Research Grant and Intel IXA Univer-sity Program
文摘As the core algorithm and the most time consuming part of almost every modern network intrusion management system （NIMS）, string matching is essential for the inspection of network flows at the line speed. This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors. Modifications of the Aho-Corasick （AC） algorithm based on the distribution characteristics of NIMS patterns drastically reduce the memory usage without sacrificing speed in software implementations. In tests on the Snort pattern set and traces that represent typical NIMS workloads, the Snort performance was enhanced 1.48%-20% compared to other well-known alternatives with an automaton size reduction of 4.86-6.11 compared to the standard AC implementation. The results show that special characteristics of the NIMS can be used into a very effective method to optimize the algorithm design.
