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Devito: Towards a Generic Finite Difference DSL Using Symbolic Python., , , , , , , , and . PyHPC@SC, page 67-75. IEEE, (2016)Combining Checkpointing and Data Compression to Accelerate Adjoint-Based Optimization Problems., , , , and . Euro-Par, volume 11725 of Lecture Notes in Computer Science, page 87-100. Springer, (2019)Automatic Differentiation for Adjoint Stencil Loops., , , , , and . ICPP, page 83:1-83:10. ACM, (2019)Training on the Edge: The why and the how., , , , , , and . IPDPS Workshops, page 899-903. IEEE, (2019)Devito: Automated Fast Finite Difference Computation., , , , , and . WOLFHPC@SC, page 11-19. IEEE Computer Society, (2016)Towards Self-Verification in Finite Difference Code Generation., , , , , , , , and . CORRECTNESS@SC, page 42-49. ACM, (2017)Performance prediction of finite-difference solvers for different computer architectures., , , , and . CoRR, (2016)Optimised finite difference computation from symbolic equations., , , , , , and . SciPy, page 89-97. scipy.org, (2017)Combining checkpointing and data compression for large scale seismic inversion., , , , , , and . CoRR, (2018)High-level python abstractions for optimal checkpointing in inversion problems., , , , , , and . CoRR, (2018)