Update README_ACC.md

quantum_espresso/README_ACC.md

@@ -48,16 +48,24 @@ git clone https://github.com/fspiga/qe-gpu.git
 
 ## 4. Compiling and installing the application
 
-This distribution does not have a ```configure``` command. Instead you make
-changes directly in the ```make.inc``` file.
+Check the __README.md__ file in the downloaded files since the
+procedure varies from distribution to distribution.
+Most distributions do not have a ```configure``` command. Instead you copy a __make.inc__
+file from the __install__ directory, and modify that directly before running make.
+A number of templates are available in the distribution:
+- make.inc_x86-64
+- make.inc_CRAY_PizDaint
+- make.inc_POWER_DAVIDE
+- make.inc_POWER_SUMMITDEV
+
+The second and third are particularly relevant in the PRACE infrastructure (ie. for CSCS
+PizDaint and CINECA DAVIDE).
+Run __make__ to see the options available. For the UEABS you should select the
+pw program (the only module currently available)
 
-make -f Makefile.gpu pw-gpu
 ```
-
-In this example we are compiling with the Intel FORTRAN compiler so we
-can use the Intel MKL version of Scalapack.  Note also that in the
-above it is assumed that the CUDA library has been installed in the
-directory `/usr/local/cuda/7.0.1`.
+make pw
+```
  
 The QE-GPU executable will appear in the directory `GPU/PW` and is called `pw-gpu.x`.
 
@@ -100,57 +108,8 @@ A couple of examples for PRACE systems are given in the next section.
 ## 6. Examples
 We now give a build and 2 run examples. 
 
-### Computer System: Cartesius GPU partition, SURFSARA.
-
-#### Build
-
-``` shell
-wget http://www.qe-forge.org/gf/download/frsrelease/204/912/espresso-5.4.0.tar.gz
-tar zxvf espresso-5.4.0.tar.gz
-cd espresso-5.4.0
-wget https://github.com/fspiga/QE-GPU/archive/5.4.0.tar.gz
-tar zxvf 5.4.0.tar.gz
-
-ln -s QE-GPU-5.4.0 GPU
-
-cd GPU
-module load mpi
-module load mkl
-module load cuda
-./configure --enable-parallel --enable-openmp --with-scalapack=intel \
-  --enable-cuda --with-gpu-arch=sm_35 \
-  --with-cuda-dir=$CUDA_HOME \
-  --without-magma --with-phigemm
-cd ..
-make -f Makefile.gpu pw-gpu
-```
-
-#### Running
-Cartesius uses the SLURM scheduler. An example batch script is given below,
-
-``` shell
-#!/bin/bash 
-#SBATCH -N 6 --ntasks-per-node=16
-#SBATCH -p gpu
-#SBATCH -t 01:00:00
-
-module load fortran mkl mpi/impi cuda
-
-export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:${SURFSARA_MKL_LIB}
-srun  pw-gpu.x -input pw.in >job.out
-```
-
-You should create a file containing the above commands
-(e.g. myjob.sub) and then submit to the batch system, e.g. 
-
-``` shell
-sbatch myjob.sub 
-```
-
-Please check the SURFSara documentation for more information on how to
-use the batch system. 
 
-### Computer System: Marconi KNL partition (A2), Cineca
+### Computer System: DAVIDE P100 cluster, cineca
 
 
 #### Running