title: reading a huge csv file using cudf
body: <p>I am trying to read a huge csv file CUDF but gets memory issues.</p>
  <pre><code>import cudf
  cudf.set_allocator(&quot;managed&quot;)
  cudf.__version__
  user_wine_rate_df = cudf.read_csv('myfile.csv',
                                   sep = &quot;\t&quot;,
                                   parse_dates = ['created_at'])
  
  
  '0.17.0a+382.gbd321d1e93'
  
  terminate called after throwing an instance of 'thrust::system::system_error'
    what():  parallel_for failed: cudaErrorIllegalAddress: an illegal memory access was encountered
  Aborted (core dumped)
  </code></pre>
  <p>If I remove <code>cudf.set_allocator(&quot;managed&quot;)</code>
  I get</p>
  <pre><code>MemoryError: std::bad_alloc: CUDA error at: /opt/conda/envs/rapids/include/rmm/mr/device/cuda_memory_resource.hpp:69: cudaErrorMemoryAllocation out of memory
  </code></pre>
  <p>I am using CUDF through <code>rapidsai/rapidsai:cuda11.0-runtime-ubuntu16.04-py3.8</code></p>
  <p>I wonder whar could be the reason of hitting memory, while I can read this big file with pandas</p>
  <p>**Update</p>
  <p>I installed <em>dask_cudf</em></p>
  <p>and used <code>dask_cudf.read_csv('myfile.csv')</code> - but still get the</p>
  <p><code>parallel_for failed: cudaErrorIllegalAddress: an illegal memory access was encountered</code></p>