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Developing medical ultrasound beamforming application on GPU and FPGA using oneAPI

机译:使用ONEAPI在GPU和FPGA上开发医用超声波形成应用

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oneAPI is based on Data Parallel C++ (DPC++) and incorporates SYCL from the Khronos Group to support a cross-architecture programming environment. It delivers the freedom to choose suitable hardware for specific applications. In this paper, we developed a cross-architecture real-time medical ultrasound imaging application using oneAPI based on an open-source project SUPRA [1]. The application takes raw ultrasound data from ultrasound equipment as input and processes it to obtain B-mode images. The ultrasound processing pipeline contains four modules: Beamforming, Envelope Detection, Log-compression, and Scan-conversion. The proposed ultrasound medical beamforming algorithms are implemented with Intel’s oneAPI, which enables the algorithms to target multiple hardware architectures: GPU, FPGA, and CPU. In this paper, we show how to migrate and optimize these medical ultrasound algorithms on the GPU and FPGA in a unified programming language supported by DPC++. We also compare the GPU and FPGA performance of the algorithms. The results show that the ultrasound application achieved 140.0, 176.1 and 168.4 FPS using Intel Iris Xe integrated graphics, DG1 GPU and Arria 10 FPGA, respectively. Finally, we also evaluate the computation results correctness of our implementations with the original SUPRA application.
机译:ONEAPI基于数据并行C ++(DPC ++),并从khronos组中包含SYCL以支持跨体系结构编程环境。它提供了为特定应用选择合适的硬件的自由。在本文中,我们开发了使用基于开源项目的ONEAPI的跨架构实时医学超声成像应用程序[1]。应用程序从超声设备中获取原始超声数据作为输入,处理它以获得B模式图像。超声处理管道包含四个模块:波束成形,包络检测,记录压缩和扫描转换。所提出的超声医疗波束成形算法与英特尔的ONEAPI实现,这使得算法能够以多个硬件架构定位:GPU,FPGA和CPU。在本文中,我们展示了如何在DPC ++支持的统一编程语言中迁移和优化GPU和FPGA上的这些医学超声算法。我们还比较算法的GPU和FPGA性能。结果表明,超声应用,使用英特尔虹膜XE集成图形,DG1 GPU和Arria 10 FPGA实现了140.0,176.1和168.4 FPS。最后,我们还评估了与原始Supra应用程序的计算结果正确性。

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