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The rapid evolution of artificial intelligence (AI) is leading to a new generation of hardware accelerators optimized for deep learning. Some of the designs of these accelerators are general enough to allow their use for other computationally intensive tasks beyond AI. Cloud tensor processing units (TPUs) are one such example. Here, we demonstrate a novel approach using TensorFlow on Cloud TPUs to implement a high-resolution imaging technique called full-waveform inversion. Higher-order numerical stencils leverage the efficient matrix multiplication offered by the Cloud TPU, and the halo exchange benefits from the dedicated high-speed interchip connection. The performance is competitive when compared with Tesla V100 graphics processing units and shows promise for future computation- and memory-intensive imaging applications.
The advanced magnetic resonance (MR) image reconstructions such as the compressed sensing and subspace-based imaging are considered as large-scale, iterative, optimization problems. Given the large number of reconstructions required by the practical
The last ten years have witnessed fast spreading of massively parallel computing clusters, from leading supercomputing facilities down to the average university computing center. Many companies in the private sector have undergone a similar evolution
In this work, we present two parallel algorithms for the large-scale discrete Fourier transform (DFT) on Tensor Processing Unit (TPU) clusters. The two parallel algorithms are associated with two formulations of DFT: one is based on the Kronecker pro
The Jaccard similarity index is an important measure of the overlap of two sets, widely used in machine learning, computational genomics, information retrieval, and many other areas. We design and implement SimilarityAtScale, the first communication-
Commercial graphics processors (GPUs) have high compute capacity at very low cost, which makes them attractive for general purpose scientific computing. In this paper we show how graphics processors can be used for N-body simulations to obtain improv