rapidsai / cugraph

cuGraph - RAPIDS Graph Analytics Library
https://docs.rapids.ai/api/cugraph/stable/
Apache License 2.0
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[BUG] PageRank Values Miscalculated with Float Weights #1330

Closed andyjulin-bby closed 3 years ago

andyjulin-bby commented 3 years ago

Describe the bug When using cugraph.pagerank on a graph initialized with float values for the edge_attr parameter, the returned values are well outside the [0, 1] range expected by the PageRank calculation (often by many orders of magnitude). If the underlying values are instead of int type, the calculation works as expected. The function is currently supposed to ignore the weights column for the calculation, so it seems to purely be a bug.

Steps/Code to reproduce bug

import cudf
import cugraph
import numpy as np

data = np.array([[0, 4], [1, 0], [2, 0], [3, 1], [3, 2], [4, 2], [4, 3]])

def calc_pagerank(data, weight_val, alpha=0.85, max_iter=500, tol=1e-5):
    df = cudf.DataFrame(data, columns=['src', 'dst'])
    df['weights'] = weight_val  # Assign `dtype` to column

    g = cugraph.DiGraph()
    g.from_cudf_edgelist(df, 'src', 'dst', edge_attr='weights')  # <--- Issue when `edge_attr` is `float` type

    return cugraph.pagerank(g, alpha=alpha, max_iter=max_iter, tol=tol).sort_values('vertex')

calc_pagerank(data, 1.0)  # Using float weights

Output:

    pagerank    vertex
2   -4.211153e-12   0
3   1.635755e+00    1
4   -7.098591e-38   2
0   8.222820e+05    3
1   1.520391e+00    4

Expected behavior The returned PageRank values should all be in [0, 1], and presumably match when the weights are 1 and 1.0.

calc_pagerank(data, 1)  # Using int weights

Output:

    pagerank    vertex
2   0.284126    0
3   0.091791    1
4   0.207182    2
0   0.145391    3
1   0.271510    4

Environment overview (please complete the following information)

Environment details Please run and paste the output of the cugraph/print_env.sh script here, to gather any other relevant environment details

Click here to see environment details
     
     **git***
     print_env.sh: 10: [: true: unexpected operator
     Not inside a git repository

     ***OS Information***
     DISTRIB_ID=Ubuntu
     DISTRIB_RELEASE=18.04
     DISTRIB_CODENAME=bionic
     DISTRIB_DESCRIPTION="Ubuntu 18.04.5 LTS"
     NAME="Ubuntu"
     VERSION="18.04.5 LTS (Bionic Beaver)"
     ID=ubuntu
     ID_LIKE=debian
     PRETTY_NAME="Ubuntu 18.04.5 LTS"
     VERSION_ID="18.04"
     HOME_URL="https://www.ubuntu.com/"
     SUPPORT_URL="https://help.ubuntu.com/"
     BUG_REPORT_URL="https://bugs.launchpad.net/ubuntu/"
     PRIVACY_POLICY_URL="https://www.ubuntu.com/legal/terms-and-policies/privacy-policy"
     VERSION_CODENAME=bionic
     UBUNTU_CODENAME=bionic
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     ***GPU Information***
     Tue Jan 12 17:31:17 2021       
     +-----------------------------------------------------------------------------+
     | NVIDIA-SMI 450.51.06    Driver Version: 450.51.06    CUDA Version: 11.0     |
     |-------------------------------+----------------------+----------------------+
     | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
     | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
     |                               |                      |               MIG M. |
     |===============================+======================+======================|
     |   0  Tesla V100-SXM2...  Off  | 00000000:06:00.0 Off |                    0 |
     | N/A   35C    P0    55W / 300W |   9017MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   1  Tesla V100-SXM2...  Off  | 00000000:07:00.0 Off |                    0 |
     | N/A   35C    P0    43W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   2  Tesla V100-SXM2...  Off  | 00000000:0A:00.0 Off |                    0 |
     | N/A   33C    P0    42W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   3  Tesla V100-SXM2...  Off  | 00000000:0B:00.0 Off |                    0 |
     | N/A   31C    P0    43W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   4  Tesla V100-SXM2...  Off  | 00000000:85:00.0 Off |                    0 |
     | N/A   30C    P0    44W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   5  Tesla V100-SXM2...  Off  | 00000000:86:00.0 Off |                    0 |
     | N/A   33C    P0    43W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   6  Tesla V100-SXM2...  Off  | 00000000:89:00.0 Off |                    0 |
     | N/A   34C    P0    42W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+
     |   7  Tesla V100-SXM2...  Off  | 00000000:8A:00.0 Off |                    0 |
     | N/A   31C    P0    44W / 300W |      3MiB / 32510MiB |      0%      Default |
     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     +-----------------------------------------------------------------------------+

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     g++ (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
     Copyright (C) 2017 Free Software Foundation, Inc.
     This is free software; see the source for copying conditions.  There is NO
     warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

     ***nvcc***
     /usr/local/cuda/bin/nvcc
     nvcc: NVIDIA (R) Cuda compiler driver
     Copyright (c) 2005-2019 NVIDIA Corporation
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     Cuda compilation tools, release 10.2, V10.2.89

     ***Python***
     /opt/conda/envs/rapids/bin/python
     Python 3.7.8

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     itsdangerous              1.1.0                      py_0    conda-forge
     janome                    0.4.1                    pypi_0    pypi
     jedi                      0.17.2           py37hc8dfbb8_1    conda-forge
     jeepney                   0.4.3                      py_0    conda-forge
     jinja2                    2.11.2             pyh9f0ad1d_0    conda-forge
     jmespath                  0.10.0             pyh9f0ad1d_0    conda-forge
     joblib                    0.17.0                     py_0    conda-forge
     jpeg                      9d                   h516909a_0    conda-forge
     json-c                    0.13.1            hbfbb72e_1002    conda-forge
     json5                     0.9.5              pyh9f0ad1d_0    conda-forge
     jsondiff                  1.1.2                      py_0    conda-forge
     jsonpatch                 1.24                       py_0    conda-forge
     jsonpickle                1.4.1              pyh9f0ad1d_0    conda-forge
     jsonpointer               2.0                        py_0    conda-forge
     jsonschema                3.2.0                      py_2    conda-forge
     junit-xml                 1.9                pyh9f0ad1d_0    conda-forge
     jupyter-server-proxy      1.5.0                      py_0    conda-forge
     jupyter_client            6.1.7                      py_0    conda-forge
     jupyter_core              4.6.3            py37hc8dfbb8_2    conda-forge
     jupyter_sphinx            0.3.1            py37hc8dfbb8_1    conda-forge
     jupyterlab                2.2.9                      py_0    conda-forge
     jupyterlab-nvdashboard    0.1.11200212              py_12    rapidsai-nightly
     jupyterlab_pygments       0.1.2              pyh9f0ad1d_0    conda-forge
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     kealib                    1.4.13               h33137a7_1    conda-forge
     keras                     2.3.1                    py37_0    conda-forge
     keras-applications        1.0.8                      py_1    conda-forge
     keras-preprocessing       1.1.0                      py_0    conda-forge
     keyring                   21.4.0           py37hc8dfbb8_2    conda-forge
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     krb5                      1.17.1               hfafb76e_3    conda-forge
     lapack                    3.6.1                ha44fe06_2    conda-forge
     lcms2                     2.11                 hbd6801e_0    conda-forge
     ld_impl_linux-64          2.35                 h769bd43_9    conda-forge
     libarchive                3.4.3                hf837322_0    conda-forge
     libblas                   3.8.0                    20_mkl    conda-forge
     libcblas                  3.8.0                    20_mkl    conda-forge
     libcudf                   0.16.0          cuda10.2_g2b8298f566_0    rapidsai
     libcudf_kafka             0.16.0a201022   g2cda39b341_1979    rapidsai-nightly
     libcumlprims              0.16.0a200930   cuda10.2_g1c28023_35    rapidsai-nightly
     libcurl                   7.71.1               hcdd3856_8    conda-forge
     libcypher-parser          0.6.2                         1    rapidsai-nightly
     libdap4                   3.20.6               h1d1bd15_1    conda-forge
     libedit                   3.1.20191231         he28a2e2_2    conda-forge
     libev                     4.33                 h516909a_1    conda-forge
     libevent                  2.1.10               hcdb4288_3    conda-forge
     libfaiss                  1.6.3           he61ee18_3_cuda    conda-forge
     libffi                    3.2.1             he1b5a44_1007    conda-forge
     libgcc-ng                 7.5.0               h5dbcf3e_17    conda-forge
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     libglib                   2.66.1               h0dae87d_1    conda-forge
     libgpg-error              1.39                 he1b5a44_0    conda-forge
     libgpuarray               0.7.6             h14c3975_1003    conda-forge
     libgsasl                  1.8.0                         2    conda-forge
     libhwloc                  2.3.0                h3c4fd83_0    conda-forge
     libiconv                  1.16                 h516909a_0    conda-forge
     libkml                    1.3.0             hd79254b_1012    conda-forge
     liblapack                 3.8.0                    20_mkl    conda-forge
     liblief                   0.10.1               he1b5a44_2    conda-forge
     libllvm10                 10.0.1               he513fc3_3    conda-forge
     libllvm8                  8.0.1                hc9558a2_0    conda-forge
     libnetcdf                 4.7.4           nompi_h84807e1_105    conda-forge
     libnghttp2                1.41.0               h8cfc5f6_2    conda-forge
     libntlm                   1.4               h516909a_1002    conda-forge
     libopenblas               0.3.10          pthreads_hb3c22a3_5    conda-forge
     libpng                    1.6.37               hed695b0_2    conda-forge
     libpq                     12.3                 h5513abc_2    conda-forge
     libprotobuf               3.13.0.1             h8b12597_0    conda-forge
     librdkafka                1.5.0                h40bdf00_0    conda-forge
     librmm                    0.16.0          cuda10.2_g1bcc7b1_0    rapidsai
     libsodium                 1.0.18               h516909a_1    conda-forge
     libspatialindex           1.9.3                he1b5a44_3    conda-forge
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     libssh2                   1.9.0                hab1572f_5    conda-forge
     libstdcxx-ng              7.5.0               h2ae2ef3_17    conda-forge
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     libtool                   2.4.6             hebb1f50_1006    conda-forge
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     libuv                     1.34.0               h516909a_0    conda-forge
     libwebp                   1.1.0                h56121f0_4    conda-forge
     libwebp-base              1.1.0                h516909a_3    conda-forge
     libxcb                    1.13              h14c3975_1002    conda-forge
     libxml2                   2.9.10               hee79883_0    conda-forge
     lightgbm                  3.0.0            py37h3340039_1    conda-forge
     llvm-openmp               11.0.0               hfc4b9b4_1    conda-forge
     llvmlite                  0.34.0           py37h5202443_2    conda-forge
     locket                    0.2.0                      py_2    conda-forge
     lz4-c                     1.9.2                he1b5a44_3    conda-forge
     lzo                       2.10              h516909a_1000    conda-forge
     m4                        1.4.18            h516909a_1001    conda-forge
     make                      4.3                  hd18ef5c_1    conda-forge
     mako                      1.1.3              pyh9f0ad1d_0    conda-forge
     markdown                  3.3.2              pyh9f0ad1d_0    conda-forge
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     matplotlib                3.3.2            py37hc8dfbb8_1    conda-forge
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     mkl                       2020.2                      256    conda-forge
     mock                      4.0.2            py37hc8dfbb8_1    conda-forge
     mockito                   1.2.2                    pypi_0    pypi
     more-itertools            8.5.0                      py_0    conda-forge
     moto                      1.3.14                     py_0    conda-forge
     mpld3                     0.3                      pypi_0    pypi
     msgpack-python            1.0.0            py37h99015e2_2    conda-forge
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     nest-asyncio              1.4.1                      py_0    conda-forge
     networkx                  2.5                        py_0    conda-forge
     ninja                     1.10.1               hfc4b9b4_2    conda-forge
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     nodejs                    13.13.0              hf5d1a2b_0    conda-forge
     notebook                  6.1.4            py37hc8dfbb8_1    conda-forge
     numba                     0.51.2           py37h9fdb41a_0    conda-forge
     numpy                     1.19.4                   pypi_0    pypi
     numpydoc                  1.1.0                      py_1    conda-forge
     nvtx                      0.2.1            py37h8f50634_2    conda-forge
     oauthlib                  3.0.1                      py_0    conda-forge
     olefile                   0.46               pyh9f0ad1d_1    conda-forge
     openjdk                   8.0.152              h7b6447c_3  
     openjpeg                  2.3.1                h981e76c_3    conda-forge
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     pip                       20.2.4                     py_0    conda-forge
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     python-confluent-kafka    1.5.0            py37h8f50634_0    conda-forge
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     python-libarchive-c       2.9              py37he5f6b98_2    conda-forge
     python-louvain            0.13                       py_0    conda-forge
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     xorg-libxdmcp             1.1.3                h516909a_0    conda-forge
     xorg-libxext              1.3.4                h516909a_0    conda-forge
     xorg-libxpm               3.5.13               h516909a_0    conda-forge
     xorg-libxrender           0.9.10            h516909a_1002    conda-forge
     xorg-libxt                1.1.5             h516909a_1003    conda-forge
     xorg-renderproto          0.11.1            h14c3975_1002    conda-forge
     xorg-xextproto            7.3.0             h14c3975_1002    conda-forge
     xorg-xproto               7.0.31            h14c3975_1007    conda-forge
     xz                        5.2.5                h516909a_1    conda-forge
     yaml                      0.2.5                h516909a_0    conda-forge
     yarl                      1.5.1                    pypi_0    pypi
     zeromq                    4.3.3                he1b5a44_2    conda-forge
     zict                      2.0.0                    pypi_0    pypi
     zipp                      3.3.1                      py_0    conda-forge
     zlib                      1.2.11            h516909a_1010    conda-forge
     zstd                      1.4.5                h6597ccf_2    conda-forge

afender commented 3 years ago

Thanks for reporting this. Sounds like a bug as the current single GPU version should ignore weights. We are looking into it.

One option is to use the new multi-GPU version which uses edge weights if the input graph is weighted. https://github.com/rapidsai/cugraph/issues/1313#issuecomment-747636762. The single GPU variant of this new version should also be accessible at the C++ layer https://github.com/rapidsai/cugraph/blob/branch-0.18/cpp/tests/experimental/pagerank_test.cpp#L251

afender commented 3 years ago

Also, we are going to connect the upgraded PageRank backend (which accepts weights) to the single-GPU API in this release (0.18). This bug should go away as we do so. I opened #1331 to track the progress of this effort. Hope that helps!

andyjulin-bby commented 3 years ago

Glad to hear it! Thank you for looking into this so quickly.

BradReesWork commented 3 years ago

closed by #1332 and #1331