change to dynamic linking and add interface and threading layers

Author: Vahid Tavanashad

.github/workflows/build_pip.yaml

@@ -42,7 +42,7 @@ jobs:
 
       - name: Install Compiler and MKL
         run: |
-          conda install mkl-devel mkl-service dpcpp_linux-64
+          conda install mkl-devel - tbb-devel mkl-service dpcpp_linux-64
           python -c "import sys; print(sys.executable)"
           which python
           python -c "import mkl; print(mkl.__file__)"

CMakeLists.txt

@@ -23,7 +23,11 @@ cmake_print_variables(Python_NumPy_INCLUDE_DIRS)
 set(CYTHON_FLAGS "-t -w \"${CMAKE_SOURCE_DIR}\"")
 find_package(Cython REQUIRED)
 
-set(MKL_LINK sdl)
+find_package(TBB REQUIRED)
+set(MKL_ARCH "intel64")
+set(MKL_INTERFACE ilp64)
+set(MKL_THREADING tbb_thread)
+set(MKL_LINK dynamic) 
 find_package(MKL REQUIRED)
 
 if(WIN32)

README.md

@@ -47,6 +47,7 @@ If these are installed as part of a `oneAPI` installation, the following package
 
 If build dependencies are to be installed with Conda, the following packages must be installed from the Intel(R) channel
 - `mkl-devel`
+- `tbb-devel`
 - `dpcpp_linux-64` (or `dpcpp_win-64` for Windows)
 - `numpy-base`
 
@@ -56,7 +57,7 @@ then the remaining dependencies
 - `cython`
 - `scikit-build`
 
-and for `mkl-devel` and `dpcpp_linux-64` in a Conda environment, `MKLROOT` environment variable must be set
+and for `mkl-devel`, `tbb-devel` and `dpcpp_linux-64` in a Conda environment, `MKLROOT` environment variable must be set
 On Linux
 ```sh
 export MKLROOT=$CONDA_PREFIX

conda-recipe-cf/meta.yaml

@@ -28,6 +28,7 @@ requirements:
       - scikit-build
       - python
       - mkl-devel
+      - tbb-devel
       - numpy
     run:
       - python

conda-recipe/meta.yaml

@@ -28,6 +28,7 @@ requirements:
       - scikit-build
       - python
       - mkl-devel
+      - tbb-devel
       - numpy-base
     run:
       - python

mkl_umath/tests/test_basic.py

@@ -85,3 +85,10 @@ def test_umath(case):
 def test_cases_count():
     print("Test cases count:", len(test_cases))
     assert len(test_cases) > 0, "No test cases found"
+
+def test_large():
+    n = 2**31
+    data = np.ones(n)
+    mkl_res = mu.absolute(data)  
+    assert np.allclose(mkl_res, 1.0)
+