1.4 Parallelization efforts for MOLCAS modules

Presented below is a table of modules in MOLCAS that can benifit from parallel execution through distribution of work and/or resources. If a module is not listed in this table, and the module-specific documentation does not mention anything about parallelization, then you have to assume the module is not (efficiently) parallelized. This means that even though it will get executed in parallel, all processes will perform the same serial calculation! Be aware that for parallel modules with serial components, the use of the serial components (indirectly or through the use of a keyword) might adversely affect CPU and memory usage for large calculations. In that case, you might have to increase the runtime or memory, or avoid/use keywords that activate/deactivate the serial components.

**Table:** Modules in MOLCAS which benefit from parallel processing.
Module	Parallel speed-up expected for	Notable non-parallel parts
`seward`	conventional 2-el integrals	1-el integrals
	Cholesky vectors	Douglas-Kroll-Hess
		properties
`scf`	orbital optimization	properties
`rasscf`	orbital optimization	CI optimization
		properties
`mbpt2`
`caspt2`	Cholesky vectors	conventional 2-el integrals
		properties
		multi-state interaction
`alaska`	displacements (if using numerical gradients)
`geo`	displacements