# Reducing computational time

**URL:** <https://ask.bioexcel.eu/t/reducing-computational-time/4945>\
**Category:** HADDOCK\
**Created:** [April 26, 2024, 11:39am UTC](https://ask.bioexcel.eu/t/reducing-computational-time/4945 "2024-04-26T11:39:16Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![stianale](https://avatars.discourse-cdn.com/v4/letter/s/71c47a/32.png) [@stianale](https://ask.bioexcel.eu/u/stianale)\
**Post date:** [April 26, 2024, 11:39am UTC](https://ask.bioexcel.eu/t/reducing-computational-time/4945/1 "2024-04-26T11:39:16Z")

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The HADDOCK category is meant to discuss any HADDOCK-related issue. For general information about HADDOCK refer to [HADDOCK – Bonvin Lab](http://www.bonvinlab.org/software/haddock2.4)

Hi, I apologize for starting so many new topics lately, but beyond setting delenph = true, how can one reduce the computational time of HADDOCK runs without compromising quality of the output? I have a massive number of docking runs to perform, because I have many proteins and DNAs to dock. And it gets worse, because I am using samples of normal modes from each of the partners in ensemble pdb files, so for each HADDOCK run I need to set the sampling parameters to a very high number and partition the normal modes into different ensemble pdb files.

I am using haddock3 locally.

Thanks in advance

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**Author:** ![VGPReys](https://dub1.discourse-cdn.com/flex013/user_avatar/ask.bioexcel.eu/vgpreys/32/960_2.png) [@VGPReys](https://ask.bioexcel.eu/u/VGPReys)\
**Post date:** [April 26, 2024, 12:15pm UTC](https://ask.bioexcel.eu/t/reducing-computational-time/4945/2 "2024-04-26T12:15:19Z")

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Dear stianale,

Thanks for your interest in using haddock3 in for your research.

Unfortunately, running computationally heavy runs will take some time.

To reduce the time, you could:

- increase the number of cores to be used (with the `ncores` parameter)
- reduce the sampling in `[rigidbody]` (at a cost of possible missing good poses)
- provide meaningful ambiguous restraints to better guide the docking and therefore safely reduce the sampling
- reduce the number of selected top models for refinements (`[seletop] select=100`)
- perform some clustering to only refine diverse models (`[clustfcc]` or `[rmsdmatrix][clustrmsd]` followed by `[seletopclusts]`)
- not do `[mdref]` step, but only rely on the `[emref]` instead

Also, please note that you can also provide ensemble pdb files as input to haddock3.

With the hope that this answer will help you.