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Ultrasound computed tomography techniques like full-waveform inversion are mathematically and computationally challenging, while existing codes are closed source, difficult to maintain, and slow to adapt to new research. Consequently, we present Stride, an open-source Python library for the solution of large-scale ultrasound tomography problems. Stride combines high-level, intuitive interfaces with high-performance wave-equation solvers based on Devito, a framework for automatic finite-difference code generation. We show how Stride can achieve state-of-the-art modelling accuracy and can switch seamlessly between 2D and 3D, while easily scaling from a workstation to a high-performance cluster.