{"title":"基于pcie的高性能FPGA-GPU-CPU异构通信方法","authors":"Su ZhaoPeng, Zhou Kuanjiu, Cui Kai, Hu Shaoqi","doi":"10.1109/IWECAI50956.2020.00020","DOIUrl":null,"url":null,"abstract":"Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.","PeriodicalId":364789,"journal":{"name":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"PCIE-Based High-Performance FPGA-GPU-CPU Heterogeneous Communication Method\",\"authors\":\"Su ZhaoPeng, Zhou Kuanjiu, Cui Kai, Hu Shaoqi\",\"doi\":\"10.1109/IWECAI50956.2020.00020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.\",\"PeriodicalId\":364789,\"journal\":{\"name\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWECAI50956.2020.00020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Workshop on Electronic Communication and Artificial Intelligence (IWECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWECAI50956.2020.00020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PCIE-Based High-Performance FPGA-GPU-CPU Heterogeneous Communication Method
Heterogeneous computing, as a kind of special parallel computing method, can exert the ability of different computing resources based on the characteristics of computing tasks and is much advantageous in improving server computing performance, energy efficiency ratio (EER) and real time performance. FPGA-GPU-CPU heterogeneous computing was born for the real-time processing of massive of data. However, the communication bottlenecks between different computing units have set restrictions on the computing capabilities of heterogeneous platform. In view of the above issues, this article connects GPU and FPGA devices through the PCI Express bus, so that data can be transmitted between these heterogeneous computing units without the assistance of the system CPU memory. And, we have realized that the PCIe communication by taking FPGA as the main controller through GPUDirect RDMA, which improves the weakness of slow reading in PCle communication where the GPU as the main controller. Experiments show that we have improved the efficiency by 1.4 times compared to the memory sharing-based communication and the data rate has been made closest to the maximum theoretical bandwidth.