1.1.4. 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 1.1.4.1 Modules in Molcas which benefit from parallel processing.

Module	Parallel speed-up expected for	Notable non-parallel parts
SEWARD	conventional 2-el integrals Cholesky vectors	1-el integrals 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