图像采集和GPU处理应用,采用IRIO技术和FlexRIO器件

J. Nieto, M. Ruiz, S. Esquembri, G. de Arcas, E. Barrera, A. Gracia
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引用次数: 1

摘要

大型物理实验中使用的图像诊断产生的大量数据需要在实时数据采集和处理应用中有效地利用硬件技术。为了获得最佳的硬件性能,有必要提供硬件和软件工具,以便快速简便地部署这些解决方案。IRIO技术可以轻松开发先进的数据采集应用程序,并使用美国国家仪器公司可重构输入/输出(RIO) fpga卡将其集成到EPICS中。使用IRIO软件工具,可以最大限度地减少为不同硬件配置构建特定应用程序的开发时间。IRIO使用开源版本的NI-RIO Linux设备驱动程序,支持从FlexRIO设备到NVIDIA gpu的直接DMA访问。为了开发图像处理应用程序,所选择的硬件平台已经使用带有相机链路适配器模块和NVIDIA Kepler架构GPU的FlexRIO设备实现。在IRIO工具的帮助下,用户必须专注于使用LabVIEW/FPGA实现FlexRIO设备的FPGA应用程序和使用NVIDIA CUDA工具实现GPU算法的开发。此外,IRIO使用由ITER和Cosylab开发的软件模型为这些应用提供EPICS集成,通过标称设备支持方法简化了EPICS设备支持的开发。这是一组带有c++类的库,简化了这些设备支持的开发。为了演示完整的开发周期,使用具有ITER快速控制器硬件目录中定义的相同元素的硬件配置,对基于JPEG标准的图像压缩算法进行了评估和测试。该图像标准允许高压缩比,并且可以包含与图像相关的附加元数据信息。这些软件工具已经在ITER CCS (Codac核心系统)中进行了测试。
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Image acquisition and GPU processing application using IRIO technology and FlexRIO devices
The large amount of data generated by image diagnostics used in big physics experiments requires an efficient use of hardware technologies in real time data acquisition and processing applications. In order to get the best performance of the hardware, it is necessary to provide the hardware and software tools that enable a fast and easy way to deployment these kind of solutions. IRIO technology allows an easy development of advanced data acquisition applications and their integration in EPICS using National Instruments Reconfigurable Input/Output (RIO) FPGA-based cards. Using IRIO software tools, it is possible to minimize the development time to build specific application for different hardware configurations. IRIO uses the open source version of NI-RIO Linux device driver supporting direct DMA access from FlexRIO devices to NVIDIA GPUs. For the development of image processing applications the hardware platform selected has been implemented using a FlexRIO device with a cameralink adapter module and a NVIDIA Kepler architecture GPU. With the help of IRIO tools the user have to focus the development exclusively in the implementation of the FPGA application for the FlexRIO device using LabVIEW/FPGA and the GPU algorithm using NVIDIA CUDA tools. Additionally IRIO provides the EPICS integration for these applications using the software model developed by ITER and Cosylab that simplifies the development of EPICS device support by mean of Nominal Device Support approach. This is a set of libraries with C++ classes simplifying the development of these device supports. To demonstrate the full development cycle an algorithm for image compression based on JPEG standard has been evaluated and tested using a hardware configuration with the same elements defined in the ITER fast controllers hardware catalog. This image standard allows high compression ratios and can include additional metadata information related to the image. These software tools has been tested in ITER CCS (Codac Core System).
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