{"title":"基于并行小波变换的多核/GPU宽带DOA","authors":"M. W. Majid, Golrokh Mirzaei, M. Jamali","doi":"10.1109/EIT.2013.6632679","DOIUrl":null,"url":null,"abstract":"In most of the signal processing applications, main interest is to obtain an accurate estimation of the Direction-Of-Arrival (DOA) of a received signal. Computation of Direction-Of-Arrival (DOA) based on Wavelet transform and other techniques are available in the literature. This work is an improved work of our previously parallel implementation of DOA. In this work, Parallel Haar Wavelet Transform (PHWT) is proposed for use in wideband DOA algorithm. This algorithm has been parallelized and implemented on Intel Nehalem Quad Core processor and NVidia GeForce GTX 260 GPU. The algorithm uses data level and instruction level parallelism for faster execution. The parallel algorithm is developed in C# using .Net framework 4.0 for Multi-Core. It uses combination of C and CUDA for its implementation on GPU. This brings the significant performance on a consumer level PC without any extra cost.","PeriodicalId":201202,"journal":{"name":"IEEE International Conference on Electro-Information Technology , EIT 2013","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Parallel wavelet transform based wideband Direction-Of-Arrival (DOA) on multicore/GPU\",\"authors\":\"M. W. Majid, Golrokh Mirzaei, M. Jamali\",\"doi\":\"10.1109/EIT.2013.6632679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In most of the signal processing applications, main interest is to obtain an accurate estimation of the Direction-Of-Arrival (DOA) of a received signal. Computation of Direction-Of-Arrival (DOA) based on Wavelet transform and other techniques are available in the literature. This work is an improved work of our previously parallel implementation of DOA. In this work, Parallel Haar Wavelet Transform (PHWT) is proposed for use in wideband DOA algorithm. This algorithm has been parallelized and implemented on Intel Nehalem Quad Core processor and NVidia GeForce GTX 260 GPU. The algorithm uses data level and instruction level parallelism for faster execution. The parallel algorithm is developed in C# using .Net framework 4.0 for Multi-Core. It uses combination of C and CUDA for its implementation on GPU. This brings the significant performance on a consumer level PC without any extra cost.\",\"PeriodicalId\":201202,\"journal\":{\"name\":\"IEEE International Conference on Electro-Information Technology , EIT 2013\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE International Conference on Electro-Information Technology , EIT 2013\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIT.2013.6632679\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Electro-Information Technology , EIT 2013","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIT.2013.6632679","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
摘要
在大多数信号处理应用中，主要的兴趣是获得接收信号的到达方向(DOA)的准确估计。基于小波变换和其他技术的到达方向(DOA)计算已经在文献中得到。这项工作是我们以前并行实现DOA的改进工作。本文提出将并行Haar小波变换(PHWT)用于宽带DOA算法。该算法已在Intel Nehalem四核处理器和NVidia GeForce GTX 260 GPU上并行化实现。该算法使用数据级和指令级并行性来提高执行速度。并行算法是使用。net framework 4.0 for Multi-Core在c#中开发的。它使用C和CUDA的组合在GPU上实现。这带来了显著的性能在消费级PC没有任何额外的成本。
Parallel wavelet transform based wideband Direction-Of-Arrival (DOA) on multicore/GPU
In most of the signal processing applications, main interest is to obtain an accurate estimation of the Direction-Of-Arrival (DOA) of a received signal. Computation of Direction-Of-Arrival (DOA) based on Wavelet transform and other techniques are available in the literature. This work is an improved work of our previously parallel implementation of DOA. In this work, Parallel Haar Wavelet Transform (PHWT) is proposed for use in wideband DOA algorithm. This algorithm has been parallelized and implemented on Intel Nehalem Quad Core processor and NVidia GeForce GTX 260 GPU. The algorithm uses data level and instruction level parallelism for faster execution. The parallel algorithm is developed in C# using .Net framework 4.0 for Multi-Core. It uses combination of C and CUDA for its implementation on GPU. This brings the significant performance on a consumer level PC without any extra cost.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
