Alphafold-Multimer was run for more than 48h, I still couldn't get the structure of a complex with 4 subunits (total aa length: 2222+689+201+196). 
Hi, author
python3 docker/run_docker.py \
  --fasta_paths=complex1.fasta \
  --max_template_date=2022-12-30 \
  --model_preset=multimer \
  --data_dir=/data  --gpu_devices=0,1,2,3 > complex1.log &

1) The program was always calculating the model until now.
I0107 01:49:08.176561 140086208259904 run_docker.py:255] I0107 01:49:08.175831 140502687897408 run_alphafold.py:191] Running model model_1_multimer_v3_pred_0 on complex1
I0107 01:49:08.178550 140086208259904 run_docker.py:255] I0107 01:49:08.178094 140502687897408 model.py:165] Running predict with shape(feat) = {'aatype': (3308,), 'residue_index': (3308,), 'seq_length': (), 'msa': (5799, 3308), 'num_alignments': (), 'template_aatype': (4, 3308), 'template_all_atom_mask': (4, 3308, 37), 'template_all_atom_positions': (4, 3308, 37, 3), 'asym_id': (3308,), 'sym_id': (3308,), 'entity_id': (3308,), 'deletion_matrix': (5799, 3308), 'deletion_mean': (3308,), 'all_atom_mask': (3308, 37), 'all_atom_positions': (3308, 37, 3), 'assembly_num_chains': (), 'entity_mask': (3308,), 'num_templates': (), 'cluster_bias_mask': (5799,), 'bert_mask': (5799, 3308), 'seq_mask': (3308,), 'msa_mask': (5799, 3308)}

2) The instance (p3.8xlarge) has four GPUs (4xNVIDIA V100).  All GPUs are available to calculate the model (--gpu_devices=0,1,2,3). But I noticed that 'run_alphafold.py' seems to use four GPUs, but why only the first one GPU memory is fulfilled?

![image](https://user-images.githubusercontent.com/22016970/211168401-e7fa4b22-3321-490b-b727-4cf7da0ee94a.png)
How can I use the four GPUs with maximum memory usage at the same time to speed up the prediction?

