title: AlphaFold out of memory error with 15 GB of RAM and 95 GB of disc space unused?
body: <p>I'm trying to use <a href="https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb" rel="nofollow noreferrer">this</a> notebook to run AlphaFold to predict the structure of a large protein. I've used this notebook many times for proteins of reasonable size (300-800 aa, if that's helpful) without any problems, but this protein is almost 2,400 aa. I first tried to run it on a free Colab account, which obviously didn't have nearly enough RAM. I switched to Colab Pro and tried it again today, but got a very similar error message, this time only in the code itself rather than that little pop-up prompt from colab to buy Pro. The strange part is that the whole run never uses more than 9 GB of RAM and 60 GB of disc space (of 25 GB RAM and 155 GB disc space available), so it doesn't seem like I'm even close to the resource limit when it fails and flashes the error.</p>
  <p>I'm new to colab, so I'm not sure what could be going on, but it seems like the program may be somehow &quot;self-sabotaging&quot; and imposing a different resource limit than colab's actual limit on a Pro account. Any thoughts on that or some other possibilities and potential solutions?</p>
  <p>Thanks in advance!</p>
  <p>Here's the exact error message:</p>
  <pre><code>running model_1
  ---------------------------------------------------------------------------
  UnfilteredStackTrace                      Traceback (most recent call last)
  &lt;ipython-input-15-af48741e914e&gt; in &lt;module&gt;()
       50                          model_params=model_params, use_model=use_model,
  ---&gt; 51                          do_relax=use_amber)
  
  13 frames
  UnfilteredStackTrace: RuntimeError: RESOURCE_EXHAUSTED: Out of memory while trying to 
  allocate 1465970944 bytes.
  
  The stack trace below excludes JAX-internal frames.
  The preceding is the original exception that occurred, unmodified.
  
  --------------------
  
  The above exception was the direct cause of the following exception:
  
  RuntimeError                              Traceback (most recent call last)
  /usr/local/lib/python3.7/dist-packages/jax/interpreters/xla.py in 
  _execute_compiled(compiled, avals, handlers, kept_var_idx, *args)
      958           for i, x in enumerate(args)
      959           if x is not token and i in kept_var_idx))
  --&gt; 960   out_bufs = compiled.execute(input_bufs)
      961   check_special(xla_call_p.name, out_bufs)
      962   return [handler(*bs) for handler, bs in zip(handlers, 
  _partition_outputs(avals, out_bufs))]
  
  RuntimeError: RESOURCE_EXHAUSTED: Out of memory while trying to allocate 1465970944 
  bytes.
  </code></pre>