When I use C pointers in python and try to process it using dask, it working like a pro. But when I try to use python's multiprocessing module, it splits the pointer reference error.
How is dask able to overcome the multiprocessing module when using C pointers
The default scheduler for dask ("threaded") works with threads in the same process where you have defined your graph, so each worker has access to the original memory space - the C pointers are therefore valid. In a new process, whether using the builtin multiprocessing module or otherwise, you would need to recreate whatever C structures you need, and make new pointers to them; this can be done either in de/serialisation (dask-distributed has a lot of logic dedicated to this), or by reloading modules/data in the worker.
