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Hi Team,
I'm getting CUDA memory error when I call cudf.Series method from the hlca_lung_gpu_analysis-visualization notebook.
Error Log:
--------------------------------------------------------------------------- ArrowTypeError Traceback (most recent call last) ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/utils/utils.py in pyarrow_buffer_to_cudf_buffer(arrow_buf, mask_size) 157 try: --> 158 arrow_cuda_buf = arrowCudaBuffer.from_buffer(arrow_buf) 159 buf = Buffer( ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/pyarrow/_cuda.pyx in pyarrow._cuda.CudaBuffer.from_buffer() ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status() ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status() ArrowTypeError: buffer is not backed by a CudaBuffer During handling of the above exception, another exception occurred: MemoryError Traceback (most recent call last) <timed exec> in <module> ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/series.py in __init__(self, data, index, dtype, name, nan_as_null) 186 187 if not isinstance(data, column.ColumnBase): --> 188 data = column.as_column(data, nan_as_null=nan_as_null, dtype=dtype) 189 190 if index is not None and not isinstance(index, Index): ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/column/column.py in as_column(arbitrary, nan_as_null, dtype, length) 1552 elif arb_dtype.kind in ("O", "U"): 1553 data = as_column( -> 1554 pa.Array.from_pandas(arbitrary), dtype=arbitrary.dtype 1555 ) 1556 # There is no cast operation available for pa.Array from int to ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/column/column.py in as_column(arbitrary, nan_as_null, dtype, length) 1352 elif isinstance(arbitrary, pa.Array): 1353 if isinstance(arbitrary, pa.StringArray): -> 1354 data = cudf.core.column.StringColumn.from_arrow(arbitrary) 1355 elif isinstance(arbitrary, pa.NullArray): 1356 if type(dtype) == str and dtype == "empty": ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/column/string.py in from_arrow(cls, array) 4515 @classmethod 4516 def from_arrow(cls, array): -> 4517 pa_size, pa_offset, nbuf, obuf, sbuf = buffers_from_pyarrow(array) 4518 children = ( 4519 column.build_column(data=obuf, dtype="int32"), ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/utils/utils.py in buffers_from_pyarrow(pa_arr) 129 130 if buffers[1]: --> 131 padata = pyarrow_buffer_to_cudf_buffer(buffers[1]) 132 else: 133 padata = Buffer.empty(0) ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/utils/utils.py in pyarrow_buffer_to_cudf_buffer(arrow_buf, mask_size) 172 dbuf.copy_from_host(np.asarray(arrow_buf).view("u1")) 173 return Buffer(dbuf) --> 174 return Buffer(arrow_buf) 175 176 ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/buffer.py in __init__(self, data, size, owner) 55 except TypeError: 56 raise TypeError("data must be Buffer, array-like or integer") ---> 57 self._init_from_array_like(np.asarray(data), owner) 58 59 def __len__(self): ~/anaconda3/envs/rapidgenomics/lib/python3.7/site-packages/cudf/core/buffer.py in _init_from_array_like(self, data, owner) 95 data.__array_interface__ 96 ) ---> 97 dbuf = DeviceBuffer(ptr=ptr, size=size) 98 self._init_from_array_like(dbuf, owner) 99 else: rmm/_lib/device_buffer.pyx in rmm._lib.device_buffer.DeviceBuffer.__cinit__() MemoryError: std::bad_alloc: CUDA error at: ../include/rmm/mr/device/managed_memory_resource.hpp:72: cudaErrorIllegalAddress an illegal memory access was encountered
Please find the SW details, Conda Version = conda 4.8.5 Yaml - rapidgenomics_cuda10.1.yml CUDA on disk - cuda-10.1 Ubuntu - 18.04
Regards, Jegathesan S
The text was updated successfully, but these errors were encountered:
Hi Jegathesan,
Please point us to the cell in the notebook where this issue appears.
Regards, Rajesh K Ilango
Sorry, something went wrong.
@rilango I'm having an issue with Cell number 8 in this Notebook. The code snippet is,
genes = cudf.Series(adata.var_names) barcodes = cudf.Series(adata.obs_names) sparse_gpu_array = cp.sparse.csr_matrix(adata.X)
@nullbyte91 I could not reproduce this issue. Can you please try using the container at https://hub.docker.com/r/claraparabricks/single-cell-examples_rapids_cuda10.2. Please let us know if it is still a problem.
rilango
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Hi Team,
I'm getting CUDA memory error when I call cudf.Series method from the hlca_lung_gpu_analysis-visualization notebook.
Error Log:
Please find the SW details,
Conda Version = conda 4.8.5
Yaml - rapidgenomics_cuda10.1.yml
CUDA on disk - cuda-10.1
Ubuntu - 18.04
Regards,
Jegathesan S
The text was updated successfully, but these errors were encountered: