A. Ayala, H. Osman, Daniel Shapiro, J. Desmarais, J. Parri, M. Bolic, V. Groza
{"title":"使用OpenMP加速n皇后问题","authors":"A. Ayala, H. Osman, Daniel Shapiro, J. Desmarais, J. Parri, M. Bolic, V. Groza","doi":"10.1109/SACI.2011.5873061","DOIUrl":null,"url":null,"abstract":"Backtracking algorithms are used to methodically and exhaustively search a solution space for an optimal solution to a given problem. A classic example of a backtracking algorithm is illustrated by finding all solutions to the problem of placing N-queens on an N × N chess board such that no two queens attack each other. This paper demonstrates a methodology for rewriting this backtracking algorithm to take advantage of multi-core computing resources. We accelerated a sequential version of the N-queens problem on ×86 and PPC64 architectures. Using problem sizes between 13 and 17, we observed an average speedup of 3.24 for ×86 and 9.24 for the PPC64.","PeriodicalId":334381,"journal":{"name":"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Accelerating N-queens problem using OpenMP\",\"authors\":\"A. Ayala, H. Osman, Daniel Shapiro, J. Desmarais, J. Parri, M. Bolic, V. Groza\",\"doi\":\"10.1109/SACI.2011.5873061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Backtracking algorithms are used to methodically and exhaustively search a solution space for an optimal solution to a given problem. A classic example of a backtracking algorithm is illustrated by finding all solutions to the problem of placing N-queens on an N × N chess board such that no two queens attack each other. This paper demonstrates a methodology for rewriting this backtracking algorithm to take advantage of multi-core computing resources. We accelerated a sequential version of the N-queens problem on ×86 and PPC64 architectures. Using problem sizes between 13 and 17, we observed an average speedup of 3.24 for ×86 and 9.24 for the PPC64.\",\"PeriodicalId\":334381,\"journal\":{\"name\":\"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SACI.2011.5873061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2011.5873061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Backtracking algorithms are used to methodically and exhaustively search a solution space for an optimal solution to a given problem. A classic example of a backtracking algorithm is illustrated by finding all solutions to the problem of placing N-queens on an N × N chess board such that no two queens attack each other. This paper demonstrates a methodology for rewriting this backtracking algorithm to take advantage of multi-core computing resources. We accelerated a sequential version of the N-queens problem on ×86 and PPC64 architectures. Using problem sizes between 13 and 17, we observed an average speedup of 3.24 for ×86 and 9.24 for the PPC64.