long runtime/slow simulation when simulating NMMs with jansen rit model.

[michiel aten]

Hi,

I am using TVB to generate NMM data, which is then used to train a DL model (DeepSIF). The code used is from github (https://github.com/bfinl/DeepSIF), called generate_tvb_data.py.

When I run the code, it takes about 2 hours to run 200 sec of simulation.
When using run in parallel (given in the code), it still takes 3 hours to generate data for 4 regions (each 200 sec). I find this a long time, so wanted to check if maybe something is wrong.

I ran

python3 generate_tvb_data.py --a_start 0 --a_end 3, were generate_tvb_data can be found here (https://github.com/bfinl/DeepSIF/tree/main/forward).

The code in Github contains the connectivity file for 76 regions, but I used the file for 998 regions (called connectivity_998.zip), which can be found here (https://github.com/bfinl/DeepSIF/tree/main/anatomy). I uncommented the following lines (60-64) in the code.

                # data[:, 7] = data[:, 994]
                # data[:, 325] = data[:, 997]
                # data[:, 921] = data[:, 996]
                # data[:, 949] = data[:, 995]
                # data = data[:, :994]

Is it normal that it takes so long to generate NMM data? And would anyone be able to take a look and tell if there is a way to speed up the generation of data? Thanks in advance.

Best regards,

Michiel Aten

[WOODMAN Michael]

hi,

The generic TVB implementation is not optimized, and there are a lot of ways to speed up the generation of the data, is it just parameter sweeps?  Do you have GPU(s) available?

cheers,

Marmaduke

---

From: tvb-...@googlegroups.com <tvb-...@googlegroups.com> on behalf of michiel aten <michie...@gmail.com>
Sent: Friday, May 24, 2024 12:27:17 PM
To: TVB Users
Subject: [RESEAUX SOCIAUX] [TVB] long runtime/slow simulation when simulating NMMs with jansen rit model.

 

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