# Parallelizing CyRK

:::{note}
The discussion on this page only pertains to CyRK's `cysolve_ivp`, `pysolve_ivp`, and related methods.
`nbsolve_ivp` and `nbsolve2_ivp` may support parallelization but it has not been tested thoroughly and is not
officially supported at this time.
:::

The inner workings of CySolver are not parallelized on purpose: generally the performance gains of parallelizing the
integration steps are far out weighed by the complexity, errors, and most importantly, overhead of distributed work.
However, the functions that interact with that backend (`pysolve_ivp`, `cysolve_ivp`, and their derivatives) can
be use in parallelized loops. This can greatly speed up programs that perform many, slow integrations.

## Parallel `pysolve_ivp`
`pysolve_ivp` function can be parallelized using Python's
[multiprocessing](https://docs.python.org/3/library/multiprocessing.html) package.
Note that it can not utilize multithreading because `pysolve_ivp` requires a reference to the user-provided,
Python differential equation. This would be shared across threads leading to inadvertent serialization if not just
crashing. Examples on how this is done can be found in the
[Getting Started notebook](https://cyrk.readthedocs.io/en/latest/Demos/1_-_Getting_Started.html#Parallelizing-pysolve_ivp).

## Parallel `cysolve_ivp`
`cysolve_ivp` function can be parallelized using Cython's
[prange](https://cython.readthedocs.io/en/latest/src/userguide/parallelism.html) which makes use of OpenMP.
Examples on how this is done can be found in the
[Advanced CySolver Examples notebook](https://cyrk.readthedocs.io/en/latest/Demos/2_-_Advanced_CySolver_Examples.html#Parallelizing-cysolve_ivp)
or in `CyRK.cy.prange_test`.