fix

docs.it4i/software/intel/intel-xeon-phi.md → docs.it4i/software/intel/intel-xeon-phi-salomon.md

@@ -551,12 +551,6 @@ First example "CapsBasic" detects OpenCL compatible hardware, here CPU and MIC,
 
 To compile and run the example copy it to your home directory, get a PBS interactive session on of the nodes with MIC and run make for compilation. Make files are very basic and shows how the OpenCL code can be compiled on Salomon.
 
-```console
-$ cp /apps/intel/opencl-examples/CapsBasic/* .
-$ qsub -I -q qmic -A NONE-0-0
-$ make
-```
-
 The compilation command for this example is:
 
 ```console
@@ -594,21 +588,6 @@ CL_DEVICE_TYPE_ACCELERATOR[0]
 !!! note
     More information about this example can be found on Intel website: <http://software.intel.com/en-us/vcsource/samples/caps-basic/>
 
-The second example that can be found in "/apps/intel/opencl-examples" directory is General Matrix Multiply. You can follow the the same procedure to download the example to your directory and compile it.
-
-```console
-$ cp -r /apps/intel/opencl-examples/* .
-$ qsub -I -q qmic -A NONE-0-0
-$ cd GEMM
-$ make
-```
-
-The compilation command for this example is:
-
-```console
-$ g++ cmdoptions.cpp gemm.cpp ../common/basic.cpp ../common/cmdparser.cpp ../common/oclobject.cpp -I../common -lOpenCL -o gemm -I/apps/intel/opencl/include/
-```
-
 To see the performance of Intel Xeon Phi performing the DGEMM run the example as follows:
 
 ```console

mkdocs.yml

@@ -111,8 +111,8 @@ pages:
         - Intel TBB: software/intel/intel-suite/intel-tbb.md
         - Intel Trace Analyzer and Collector: software/intel/intel-suite/intel-trace-analyzer-and-collector.md
       - Intel Xeon Phi:
-        - Intel Xeon Phi Salomon: software/intel/intel-xeon-phi.md
-        - Intel Xeon Phi Anselm: software/intel/intel-xeon-phi.anselm.md
+        - Intel Xeon Phi Salomon: software/intel/intel-xeon-phi-salomon.md
+        - Intel Xeon Phi Anselm: software/intel/intel-xeon-phi-anselm.md
     - Machine Learning:
       - Introduction: software/machine-learning/introduction.md
       - TensorFlow: software/machine-learning/tensorflow.md