viclafargue
commented
3 years ago Thanks for opening the issue. Here's my explanation for what happens. It looks like multiple RAFT utility functions make use of the matrixVectorOp operation. The matrixVectorOp will, under most conditions, opt for operations to run on 16 bytes aligned addresses. However, it does not check memory alignment. This is because RMM allocations are supposed to be aligned by default.
Instead it will check other conditions :
1) That the type has at most 16 bytes -> float64 has 8 bytes
2) That the number of bytes in a stride is a multiple of 16 -> (10 8) % 16 == 0 but (11 8) % 16 != 0 (here the stride is the number of rows)
If the conditions are satisfied it will launch the operation on 16 bytes despite the fact that the memory may not be correctly aligned for it, causing the error. If the conditions are unmet it will launch the operations on 8 bytes which should always work fine as memory should always be aligned on 8 bytes with float64 data.
cjnolet
Describe the bug Related to https://github.com/rapidsai/cuml/issues/4199 It looks like when a view of a cuDF series passed through cuML's LinearRegression fit call, the memory seems to be misaligned. Code to reproduce it is below.
But, there are certain cases where using the view works. It does not error:
lr.fit(X, y.copy())yis passed as a DataFramestart=2(or any even number, in this case)andend=start+10start=1andend=12fit_intercept=False, the code works, which leads us to believe the error is coming from raft/linalg/matrix_vector_op.cuh but it's still not clear why it happens only with a pointer offset, and not all cases. From the debugging so far, the pointers seem to be aligned properly in the Python layer.cc: @cjnolet @dantegd @viclafargue @beckernick for visibility.
Steps/Code to reproduce bug
Expected behavior The shouldn't be a memory misalignment.
Environment overview (please complete the following information)
docker pull rapidsai/rapidsai-core-dev-nightly:21.10-cuda11.0-devel-ubuntu18.04-py3.8Environment 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 18.04.6 LTS" NAME="Ubuntu" VERSION="18.04.6 LTS (Bionic Beaver)" ID=ubuntu ID_LIKE=debian PRETTY_NAME="Ubuntu 18.04.6 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 Linux 97b55137744e 5.4.0-65-generic #73~18.04.1-Ubuntu SMP Tue Jan 19 09:02:24 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux ***GPU Information*** Tue Sep 21 20:37:16 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 Quadro RTX 8000 Off | 00000000:15:00.0 Off | Off | | 33% 37C P8 36W / 260W | 1304MiB / 48601MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 1 Quadro RTX 8000 Off | 00000000:2D:00.0 Off | Off | | 33% 39C P8 23W / 260W | 3MiB / 48592MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| +-----------------------------------------------------------------------------+ ***CPU*** Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian CPU(s): 12 On-line CPU(s) list: 0-11 Thread(s) per core: 2 Core(s) per socket: 6 Socket(s): 1 NUMA node(s): 1 Vendor ID: GenuineIntel CPU family: 6 Model: 85 Model name: Intel(R) Xeon(R) Gold 6128 CPU @ 3.40GHz Stepping: 4 CPU MHz: 1200.111 CPU max MHz: 3700.0000 CPU min MHz: 1200.0000 BogoMIPS: 6800.00 Virtualization: VT-x L1d cache: 32K L1i cache: 32K L2 cache: 1024K L3 cache: 19712K NUMA node0 CPU(s): 0-11 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req pku ospke md_clear flush_l1d ***CMake*** /opt/conda/envs/rapids/bin/cmake cmake version 3.20.5 CMake suite maintained and supported by Kitware (kitware.com/cmake). ***g++*** /usr/local/bin/g++ g++ (Ubuntu 9.4.0-1ubuntu1~18.04) 9.4.0 Copyright (C) 2019 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) 2005-2020 NVIDIA Corporation Built on Wed_Jul_22_19:09:09_PDT_2020 Cuda compilation tools, release 11.0, V11.0.221 Build cuda_11.0_bu.TC445_37.28845127_0 ***Python*** /opt/conda/envs/rapids/bin/python Python 3.8.12 ***Environment Variables*** PATH : /opt/conda/envs/rapids/bin:/opt/conda/condabin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin LD_LIBRARY_PATH : /usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/lib:/opt/conda/envs/rapids/lib NUMBAPRO_NVVM : NUMBAPRO_LIBDEVICE : CONDA_PREFIX : /opt/conda/envs/rapids PYTHON_PATH : ***conda packages*** conda is /opt/conda/envs/rapids/bin/conda /opt/conda/envs/rapids/bin/conda # packages in environment at /opt/conda/envs/rapids: # # Name Version Build Channel 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xgboost 1.4.2 pypi_0 pypi xmltodict 0.12.0 py_0 conda-forge xorg-kbproto 1.0.7 h7f98852_1002 conda-forge xorg-libice 1.0.10 h7f98852_0 conda-forge xorg-libsm 1.2.3 hd9c2040_1000 conda-forge xorg-libx11 1.7.2 h7f98852_0 conda-forge xorg-libxau 1.0.9 h7f98852_0 conda-forge xorg-libxdmcp 1.1.3 h7f98852_0 conda-forge xorg-libxext 1.3.4 h7f98852_1 conda-forge xorg-libxrender 0.9.10 h7f98852_1003 conda-forge xorg-renderproto 0.11.1 h7f98852_1002 conda-forge xorg-xextproto 7.3.0 h7f98852_1002 conda-forge xorg-xproto 7.0.31 h7f98852_1007 conda-forge xz 5.2.5 h516909a_1 conda-forge yaml 0.2.5 h516909a_0 conda-forge yarl 1.6.3 py38h497a2fe_2 conda-forge zeromq 4.3.4 h9c3ff4c_1 conda-forge zfp 0.5.5 h9c3ff4c_6 conda-forge zict 2.0.0 pypi_0 pypi zipp 3.5.0 pyhd8ed1ab_0 conda-forge zlib 1.2.11 h516909a_1010 conda-forge zstd 1.5.0 ha95c52a_0 conda-forgeAdditional context Finally, this https://github.com/rapidsai/raft/pull/325 fixes it, but there might be an underlying issue this could be masking, so it might warrant further investigation.