{"title":"Julia编程语言的并行计算实验","authors":"Rui Song, Xumin Song, Yasheng Zhang, Yanni Ma","doi":"10.1145/3446132.3446166","DOIUrl":null,"url":null,"abstract":"Julia language is a free developing scripting language under the MIT license. Its goal is to case the difficulty of parallel programming. Based on the language mechanisms of Julia, we constructed a use case of computing the average running-time between every two bus stops. And then, we exampled the Julia programming framework and the code refining steps. Julia language supports both multi-cores/CPUs parallel programming mode. To full use all the computing resources, we developed some experiments on new policies about how to improve the computing performance. Experiments show that managing processors in parallel computing model consume working time, but with the increasing of problem size, this impact can be gradually ignored, and gaining nearly linear speedups.","PeriodicalId":125388,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experiment in Parallel Computing for the Julia Programming Language\",\"authors\":\"Rui Song, Xumin Song, Yasheng Zhang, Yanni Ma\",\"doi\":\"10.1145/3446132.3446166\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Julia language is a free developing scripting language under the MIT license. Its goal is to case the difficulty of parallel programming. Based on the language mechanisms of Julia, we constructed a use case of computing the average running-time between every two bus stops. And then, we exampled the Julia programming framework and the code refining steps. Julia language supports both multi-cores/CPUs parallel programming mode. To full use all the computing resources, we developed some experiments on new policies about how to improve the computing performance. Experiments show that managing processors in parallel computing model consume working time, but with the increasing of problem size, this impact can be gradually ignored, and gaining nearly linear speedups.\",\"PeriodicalId\":125388,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3446132.3446166\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 3rd International Conference on Algorithms, Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3446132.3446166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Experiment in Parallel Computing for the Julia Programming Language
Julia language is a free developing scripting language under the MIT license. Its goal is to case the difficulty of parallel programming. Based on the language mechanisms of Julia, we constructed a use case of computing the average running-time between every two bus stops. And then, we exampled the Julia programming framework and the code refining steps. Julia language supports both multi-cores/CPUs parallel programming mode. To full use all the computing resources, we developed some experiments on new policies about how to improve the computing performance. Experiments show that managing processors in parallel computing model consume working time, but with the increasing of problem size, this impact can be gradually ignored, and gaining nearly linear speedups.