From Event: SPIE Optical Engineering + Applications, 2016
With ever-increasing data rates due to stronger light sources and better detectors, X-ray imaging experiments conducted at synchrotron beamlines face bandwidth and processing limitations that inhibit efficient workflows and prevent real-time operations. We propose an experiment platform comprised of programmable hardware and optimized software to lift these limitations and make beamline setups future-proof. The hardware consists of an FPGA-based data acquisition system with custom logic for data pre-processing and a PCIe data connection for transmission of currently up to 6.6 GB/s. Moreover, the accompanying firmware supports pushing data directly into GPU memory using AMD’s DirectGMA technology without crossing system memory first. The GPUs are used to pre-process projection data and reconstruct final volumetric data with OpenCL faster than possible with CPUs alone. Besides, more efficient use of resources this enables a real-time preview of a reconstruction for early quality assessment of both experiment setup and the investigated sample. The entire system is designed in a modular way and allows swapping all components, e.g. replacing our custom FPGA camera with a commercial system but keep reconstructing data with GPUs. Moreover, every component is accessible using a low-level C library or using a high-level Python interface in order to integrate these components in any legacy environment.
Matthias Vogelgesang, Lorenzo Rota, Luis Eduardo Ardila Perez, Michele Caselle, Suren Chilingaryan, and Andreas Kopmann, "High-throughput data acquisition and processing for real-time x-ray imaging," Proc. SPIE 9967, Developments in X-Ray Tomography X, 996715 (Presented at SPIE Optical Engineering + Applications: August 31, 2016; Published: 3 October 2016); https://doi.org/10.1117/12.2237611.
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