{"title":"基于奇偶归并排序器的高效硬件结构研究","authors":"Elsayed A. Elsayed, Kenji Kise","doi":"10.1109/MCSoC.2019.00043","DOIUrl":null,"url":null,"abstract":"Sorting is widely used in several practical applications such as searching and database. This paper proposes two improved FPGA-based architectures for merge sorter that use less hardware resources compared to the state-of-the-art. For instance, with 64 sorted records are output per cycle, implementation results of our first proposal show an improvement in the required number of Flip Flops (FFs) and Look-Up Tables (LUTs) by 84.4% and 77.7%, respectively over the state-of-the-art. In addition, the throughput of our merge sorter is 1.065x higher than that of state-of-the-art. As for the second proposal, a significant improvement is achieved by 66.3% and 84.6% for the needed FFs and LUTs, respectively. Moreover, while our second proposed merge sorter uses significant less resources, it achieves about 95.9% of the performance of state-of-the-art merge sorter.","PeriodicalId":104240,"journal":{"name":"2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Towards an Efficient Hardware Architecture for Odd-Even Based Merge Sorter\",\"authors\":\"Elsayed A. Elsayed, Kenji Kise\",\"doi\":\"10.1109/MCSoC.2019.00043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sorting is widely used in several practical applications such as searching and database. This paper proposes two improved FPGA-based architectures for merge sorter that use less hardware resources compared to the state-of-the-art. For instance, with 64 sorted records are output per cycle, implementation results of our first proposal show an improvement in the required number of Flip Flops (FFs) and Look-Up Tables (LUTs) by 84.4% and 77.7%, respectively over the state-of-the-art. In addition, the throughput of our merge sorter is 1.065x higher than that of state-of-the-art. As for the second proposal, a significant improvement is achieved by 66.3% and 84.6% for the needed FFs and LUTs, respectively. Moreover, while our second proposed merge sorter uses significant less resources, it achieves about 95.9% of the performance of state-of-the-art merge sorter.\",\"PeriodicalId\":104240,\"journal\":{\"name\":\"2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MCSoC.2019.00043\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 13th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MCSoC.2019.00043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards an Efficient Hardware Architecture for Odd-Even Based Merge Sorter
Sorting is widely used in several practical applications such as searching and database. This paper proposes two improved FPGA-based architectures for merge sorter that use less hardware resources compared to the state-of-the-art. For instance, with 64 sorted records are output per cycle, implementation results of our first proposal show an improvement in the required number of Flip Flops (FFs) and Look-Up Tables (LUTs) by 84.4% and 77.7%, respectively over the state-of-the-art. In addition, the throughput of our merge sorter is 1.065x higher than that of state-of-the-art. As for the second proposal, a significant improvement is achieved by 66.3% and 84.6% for the needed FFs and LUTs, respectively. Moreover, while our second proposed merge sorter uses significant less resources, it achieves about 95.9% of the performance of state-of-the-art merge sorter.