JAX uses Accelerated Linear Algebra (XLA), a domain specific compiler for linear algebra, to achieve hardware portability. Using XLA, JAX-ReaxFF can easily run on multi-core CPUs, GPUs or TPUs without any code changes. JAX offers vectorization (vmap) and parallelization (pmap) support to take full advantage of the underlying architecture. While vmap is aimed at Single Instruction Multiple Data (SIMD) parallelism using which multiple small computations can be merged into batches to achieve high device utilization; pmap targets Multiple Instruction Multiple Data (MIMD) parallelism.