{"title":"基于GPU的AOM股票交易订单匹配的高性能计算","authors":"Ketsarin Rungraung, P. Uthayopas","doi":"10.1109/ICSEC.2013.6694750","DOIUrl":null,"url":null,"abstract":"The task of trading orders matching in financial markets is a very challenging task since due to the speed of arriving request. In this paper, the GPUs technology and CUDA programming is explored as a potential technology to accelerate this task. The trading method in Automatic Order Matching (AOM) of Stock Exchange of Thailand (SET) is used as a case study. The code is developed and parallelized using GPU technology to speeding up the. The experimental results indicated that GPU can increase the performance for this process. In addition, the speedup of the work increases with the data size. Thus, the use of GPU can be substantially important when there is a need to handle massive data at a very high speed.","PeriodicalId":191620,"journal":{"name":"2013 International Computer Science and Engineering Conference (ICSEC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A high performance computing for AOM stock trading order matching using GPU\",\"authors\":\"Ketsarin Rungraung, P. Uthayopas\",\"doi\":\"10.1109/ICSEC.2013.6694750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The task of trading orders matching in financial markets is a very challenging task since due to the speed of arriving request. In this paper, the GPUs technology and CUDA programming is explored as a potential technology to accelerate this task. The trading method in Automatic Order Matching (AOM) of Stock Exchange of Thailand (SET) is used as a case study. The code is developed and parallelized using GPU technology to speeding up the. The experimental results indicated that GPU can increase the performance for this process. In addition, the speedup of the work increases with the data size. Thus, the use of GPU can be substantially important when there is a need to handle massive data at a very high speed.\",\"PeriodicalId\":191620,\"journal\":{\"name\":\"2013 International Computer Science and Engineering Conference (ICSEC)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Computer Science and Engineering Conference (ICSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEC.2013.6694750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Computer Science and Engineering Conference (ICSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEC.2013.6694750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A high performance computing for AOM stock trading order matching using GPU
The task of trading orders matching in financial markets is a very challenging task since due to the speed of arriving request. In this paper, the GPUs technology and CUDA programming is explored as a potential technology to accelerate this task. The trading method in Automatic Order Matching (AOM) of Stock Exchange of Thailand (SET) is used as a case study. The code is developed and parallelized using GPU technology to speeding up the. The experimental results indicated that GPU can increase the performance for this process. In addition, the speedup of the work increases with the data size. Thus, the use of GPU can be substantially important when there is a need to handle massive data at a very high speed.
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