Devito is a Python package to implement optimized stencil computation (e.g., finite differences, image processing, machine learning) from high-level symbolic problem definitions. Devito builds on SymPy and employs automated code generation and just-in-time compilation to execute optimized computational kernels on several computer platforms, including CPUs, GPUs, and clusters thereof.
Devito provides a functional language to implement sophisticated operators that can be made up of multiple stencil computations, boundary conditions, sparse operations (e.g., interpolation), and much more. A typical use case is explicit finite difference methods for approximating partial differential equations. For example, a 2D diffusion operator may be implemented with Devito as follows
>>> grid = Grid(shape=(10, 10))
>>> f = TimeFunction(name='f', grid=grid, space_order=2)
>>> eqn = Eq(f.dt, 0.5 * f.laplace)
>>> op = Operator(Eq(f.forward, solve(