Large-scale Tomography Computation

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We present a novel approach to address the memory and computation challenges in ptychographic image reconstruction, a high-resolution microscopic imaging technique. Our method involves decomposing image gradients and diffraction measurements into tiles, resulting in a reduced memory footprint. Furthermore, we propose a parallel processing technique that facilitates efficient communication and parallel pipelining across a large number of GPUs, such as up to 4000 GPUs.In addition to GPU acceleration, we explore the use of FPGA accelerators to achieve improved computing and energy efficiency in Computed Tomography image reconstruction.