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I have an issue with the GPU memory. I'm using google colab with a A100 GPU, and apparently it is a GPU memory management issue, but I can't solve it. Could you help me?
When I run the prediction:
#@title Run Prediction
from geodock.GeoDockRunner import GeoDockRunner
torch.cuda.empty_cache()
ckpt_file = "/content/GeoDock/geodock/weights/dips_0.3.ckpt"
geodock = GeoDockRunner(ckpt_file=ckpt_file)
pred = geodock.dock(
partner1=partner1,
partner2=partner2,
out_name=out_name,
do_refine=do_refine,
use_openmm=True,
)
OutOfMemoryError: CUDA out of memory. Tried to allocate 994.00 MiB. GPU 0 has a total capacty of 39.56 GiB of which 884.81 MiB is free. Process 85668 has 38.69 GiB memory in use. Of the allocated memory 37.87 GiB is allocated by PyTorch, and 336.05 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Thanks!
The text was updated successfully, but these errors were encountered:
Looks like you literally run out of GPU memory. Geodock is a LLM and it uses a large amount of memory for the processing. For instance, I cannot run a prediction for a 300 aminocid protein docking to a 550 aminoacid protein in a 24Gb GPU.
As alternative to get a larger GPU or paralellise GPU, you could:
open each of the partners in e.g. pymol, look at where their intramolecular contacts are, and cut them in fragments that do not look like they would mangle the structure. Re-predict structures of the fragments, compare to originals, and if they match run the docking with the pairs of fragments hoping they fit in memory.
use a different docking software, (eg alphafold multimer, alphapulldown...) that can run on CPU. The docking will take considerably longer, but providing you have enough RAM, it will pull through.
Hi all,
I have an issue with the GPU memory. I'm using google colab with a A100 GPU, and apparently it is a GPU memory management issue, but I can't solve it. Could you help me?
When I run the prediction:
#@title Run Prediction
from geodock.GeoDockRunner import GeoDockRunner
torch.cuda.empty_cache()
ckpt_file = "/content/GeoDock/geodock/weights/dips_0.3.ckpt"
geodock = GeoDockRunner(ckpt_file=ckpt_file)
pred = geodock.dock(
partner1=partner1,
partner2=partner2,
out_name=out_name,
do_refine=do_refine,
use_openmm=True,
)
Appears this error:
OutOfMemoryError Traceback (most recent call last)
in <cell line: 6>()
4 ckpt_file = "/content/GeoDock/geodock/weights/dips_0.3.ckpt"
5 geodock = GeoDockRunner(ckpt_file=ckpt_file)
----> 6 pred = geodock.dock(
7 partner1=partner1,
8 partner2=partner2,
23 frames
/usr/local/lib/python3.10/dist-packages/torch/nn/functional.py in relu(input, inplace)
1469 result = torch.relu_(input)
1470 else:
-> 1471 result = torch.relu(input)
1472 return result
1473
OutOfMemoryError: CUDA out of memory. Tried to allocate 994.00 MiB. GPU 0 has a total capacty of 39.56 GiB of which 884.81 MiB is free. Process 85668 has 38.69 GiB memory in use. Of the allocated memory 37.87 GiB is allocated by PyTorch, and 336.05 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
Thanks!
The text was updated successfully, but these errors were encountered: