fixed short and long description fields in meta.yaml, fixed registered sign used with Intel, i.e. Intel(R)

Author: oleksandr-pavlyk

README.md

@@ -11,5 +11,5 @@ A short example, illustrating it use:
 ```python
 import tomopy
 import mkl
-mkl.domain_set_num_threads(1, domain='fft') # Intel (R) MKL FFT functions to run sequentially
+mkl.domain_set_num_threads(1, domain='fft') # Intel(R) MKL FFT functions to run sequentially
 ```

conda-recipe/meta.yaml

@@ -34,14 +34,19 @@ test:
       - mkl
 
 about:
-    home: http://github.com/IntelPython/mkl_fft
+    home: http://github.com/IntelPython/mkl-service
     license: BSD 3-Clause
     license_file: LICENSE.txt
     description:
-        NumPy-based implementation of Fast Fourier Transform using Intel (R) Math Kernel Library.
-        Supports in-place and out-of-place, 1D and ND complex FFT on arrays of single and double precision
-        with arbitrary memory layout, so long as array strides are multiples of its itemsize.
-    summary: NumPy-based implementation of Fast Fourier Transform using Intel (R) Math Kernel Library.
+        Intel(R) Math Kernel Library (Intel(R) MKL) support functions are
+        subdivided into the following groups according to their purpose:
+            Version Information
+            Threading Control
+            Timing
+            Memory Management
+            Conditional Numerical Reproducibility Control
+            Miscellaneous
+    summary: Python hooks for Intel(R) Math Kernel Library runtime control settings.
 
 extra:
   recipe-maintainers:

mkl/_mklinitmodule.c

@@ -54,7 +54,7 @@ static void _preload_threading_layer() {
      *       
      *       if MKL_THREADING_LAYER is empty
      *            if kmp_calloc (or a suitable symbol identified by Terry) is loaded,
-     *                  we are using Intel (R) OpenMP, i.e. reinterpret as implicit value of INTEL
+     *                  we are using Intel(R) OpenMP, i.e. reinterpret as implicit value of INTEL
      *            otherwise check if other Open MP is loaded by checking get_omp_num_threads symbol
      *                  if not loaded: 
      *                         assume INTEL, and force loading of IOMP5
@@ -73,7 +73,7 @@ static void _preload_threading_layer() {
     const char *mtlayer = getenv("MKL_THREADING_LAYER");
     void *omp = dlsym(RTLD_DEFAULT, "omp_get_num_threads");
     const char *omp_name = "(unidentified)";
-    const char *iomp = NULL; /* non-zero indicates Intel OpenMP is loaded */
+    const char *iomp = NULL; /* non-zero indicates Intel(R) OpenMP is loaded */
     Dl_info omp_info;
 
     if(verbose && (verbose[0] == 0 || atoi(verbose) == 0))

setup.py

@@ -82,7 +82,7 @@ def setup_package():
         maintainer_email="[email protected]",
         description="MKL Support Functions",
         long_description="""
-            Intel (R) Math Kernel Library (Intel (R) MKL) support functions are
+            Intel(R) Math Kernel Library (Intel(R) MKL) support functions are
             subdivided into the following groups according to their purpose:
                 Version Information
                 Threading Control