  This paper presents a lightweight, open-source and high-performance python
package for solving peridynamics problems in solid mechanics. The development
of this solver is motivated by the need for fast analysis tools to achieve the
large number of simulations required for `outer-loop' applications, including
sensitivity analysis, uncertainty quantification and optimisation. Our python
software toolbox utilises the heterogeneous nature of OpenCL so that it can be
executed on any platform with CPU or GPU cores. We illustrate the package use
through a range of industrially motivated examples, which should enable other
researchers to build on and extend the solver for use in their own
applications. Step improvements in execution speed and functionality over
existing techniques are presented. A comparison between this solver and an
existing OpenCL implementation in the literature is presented, tested on
benchmarks with hundreds of thousands to tens of millions of nodes. We
demonstrate the scalability of the solver on the GeForce RTX 2080 TiGPU from
NVIDIA, and the memory-bound limitations are analysed. In all test cases, the
implementation is between 1.4 and 10.0 times faster than a similar existing GPU
implementation in the literature. In particular, this improvement has been
achieved by utilising local memory on the GPU.
