Closed
Description
Test tests/test_linalg.py::test_eig_arange raises 2 issues on CPU.
- Call of
const std::int64_t scratchpad_size = mkl_lapack::syevd_scratchpad_size<double>(DPNP_QUEUE, oneapi::mkl::job::vec, oneapi::mkl::uplo::upper, size, lda);in the functiondpnp_eigvals_creturns wrong value that causesout of memoryissue. - Call of the function
oneapi::mkl::lapack::syevdindpnp_eigvals_ccauses segfault.
event = mkl_lapack::syevd(DPNP_QUEUE, // queue
oneapi::mkl::job::vec, // jobz
oneapi::mkl::uplo::upper, // uplo
size, // The order of the matrix A (0 <= n)
result_vec_kern,
lda,
result_val_kern,
scratchpad,
scratchpad_size);
event.wait();Example of the command to reproduce the issues:
SYCL_DEVICE_FILTER=cpu pytest tests/test_linalg.py::test_eig_arange[2-float64]
High-level reason of the issues is numpy is imported before dpnp in third party tests. E.g. change #1004 gets around the issue.
Low-level reason of the issues could be related to MKL runtime library loaded during numpy import that needs to be investigated.
DPNP was built from source on commit 61ae592 with below environment:
attrs 21.2.0 pyhd3eb1b0_0 intel
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 py_2 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
bzip2 1.0.8 hb9a14ef_8 intel
ca-certificates 2020.12.5 0 intel
certifi 2020.12.5 py38he139614_0 intel
cmake 3.19.6 h973ab73_0
cython 0.29.23 py38hb3b8d61_0 intel
decorator 5.0.9 pyhd3eb1b0_0 intel
dpcpp-cpp-rt 2021.4.0 intel_3561 intel
dpcpp_cpp_rt 2021.4.0 intel_3561 intel
dpcpp_impl_linux-64 2021.4.0 intel_3561 intel
dpcpp_linux-64 2021.4.0 intel_3561 intel
dpctl 0.11.0dev0 py38h2bc3f7f_34 dppy/label/dev
dpl-include 2021.4.0 intel_0 intel
expat 2.4.1 h9c3ff4c_0 conda-forge
icc_rt 2021.4.0 intel_3561 intel
iniconfig 1.1.1 pyh9f0ad1d_0 conda-forge
intel-cmplr-lib-rt 2021.4.0 intel_3561 intel
intel-cmplr-lic-rt 2021.4.0 intel_3561 intel
intel-opencl-rt 2021.4.0 intel_3561 intel
intel-openmp 2021.4.0 intel_3561 intel
intelpython 2021.4.0 0 intel
ipython 7.27.0 py38hb070fc8_0
jedi 0.18.0 py38h578d9bd_2 conda-forge
libcurl 7.78.0 h471713a_2 intel
libffi 3.3 13 intel
libgcc-ng 9.3.0 hdf63c60_101 intel
libssh2 1.9.0 h4b1ad09_1 intel
libstdcxx-ng 9.3.0 hdf63c60_101 intel
libuv 1.40.0 h7b6447c_0 intel
lz4-c 1.9.3 h688b341_1 intel
matplotlib-inline 0.1.3 pyhd8ed1ab_0 conda-forge
mkl 2021.4.0 intel_640 intel
mkl-devel 2021.4.0 intel_640 intel
mkl-devel-dpcpp 2021.4.0 intel_640 intel
mkl-dpcpp 2021.4.0 intel_640 intel
mkl-include 2021.4.0 intel_640 intel
mkl-service 2.4.0 py38h76adbe5_0 intel
mkl_fft 1.3.0 py38h6d51d7b_1 intel
mkl_random 1.2.2 py38hd4cd407_1 intel
mkl_umath 0.1.1 py38hff32f8b_9 intel
more-itertools 8.10.0 pyhd8ed1ab_0 conda-forge
ncurses 6.2 hf61fa16_1 intel
numpy 1.20.3 py38h699e47d_1 intel
numpy-base 1.20.3 py38hf45626f_1 intel
openssl 1.1.1k h14c3975_3 intel
packaging 21.0 pyhd8ed1ab_0 conda-forge
parso 0.8.2 pyhd8ed1ab_0 conda-forge
pexpect 4.8.0 pyh9f0ad1d_2 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pip 21.1.1 py38ha59826b_0 intel
pluggy 1.0.0 py38h578d9bd_1 conda-forge
prompt-toolkit 3.0.20 pyha770c72_0 conda-forge
ptyprocess 0.7.0 pyhd3deb0d_0 conda-forge
py 1.10.0 pyhd3deb0d_0 conda-forge
pygments 2.10.0 pyhd8ed1ab_0 conda-forge
pyparsing 2.4.7 py38h0618fa2_2 intel
pytest 6.2.5 py38h578d9bd_0 conda-forge
python 3.8.11 ha27d850_1 intel
python_abi 3.8 2_cp38 conda-forge
rhash 1.4.1 h7f98852_0 conda-forge
setuptools 52.0.0 py38h0d5a7d4_0 intel
six 1.16.0 py38h7c2029b_0 intel
sqlite 3.36.0 hb9a14ef_2 intel
tbb 2021.4.0 intel_643 intel
tbb-devel 2021.4.0 intel_643 intel
tbb4py 2021.4.0 py38_intel_643 intel
tcl 8.6.10 1 intel
tk 8.6.10 h8e2d9d6_3 intel
toml 0.10.2 pyhd8ed1ab_0 conda-forge
traitlets 5.1.0 pyhd8ed1ab_0 conda-forge
wcwidth 0.2.5 pyh9f0ad1d_2 conda-forge
wheel 0.36.2 py38ha11c92b_0 intel
xz 5.2.5 h74280d8_2 intel
zlib 1.2.11.1 h1e99aa7_4 intel
zstd 1.4.5 h3f200d0_0 intel