Updates based on the review and recent experiences at LRZ.

gpaw/README.md

@@ -116,7 +116,7 @@ interpreter is used and the MPI functionality is included in the `_gpaw.so` shar
 ### Available instructions
 
 The [GPAW wiki](https://wiki.fysik.dtu.dk/gpaw/) only contains the
-[installation instructions](https://wiki.fysik.dtu.dk/gpaw/index.html) for the current version.
+[installation instructions](https://wiki.fysik.dtu.dk/gpaw/install.html) for the current version.
 For the installation instructions with a list of dependencies for older versions,
 download the code (see below) and look for the file `doc/install.rst` or go to the
 [GPAW GitLab](https://gitlab.com/gpaw), select the tag for the desired version and
@@ -205,7 +205,7 @@ may not offer optimal performance and the automatic detection of the libraries a
 fails on some systems.
 
 The UEABS repository contains additional instructions:
-  * [general instructions](build/build-cpu.md)
+  * [general instructions](build/build-CPU.md)
 
 Example [build scripts](build/examples/) are also available.
 
@@ -297,11 +297,17 @@ on one hand and version 21.1.0 on the other hand.
 
 The expected values are:
   * Number of iterations: Between 30 and 35
-  * Dipole (3rd component):
-      * 20.1.0 and 20.10.0: between -0.493 and -0.491
-      * 21.1.0: between -0.462 and -0.461
-  * Fermi level:
-      * 20.1.0 and 20.10.0: between -2.67 and -2.66
-      * 21.1.0: between -2.59 and -2.58
+  * Dipole (3rd component):between -0.493 and -0.491
+  * Fermi level:between -2.67 and -2.66
+  * Extrapolated energy: Between -3784 and -3783
+
+Note: Though not used for the benchmarking in the final report, some testing was done
+with version 21.1.0 also. In this version, some external library routines were replaced
+by new internal implementations that cause changes in some results. For 21.1.0, the
+expected values are:
+
+  * Number of iterations: Between 30 and 35
+  * Dipole (3rd component): between -0.462 and -0.461
+  * Fermi level: between -2.59 and -2.58
   * Extrapolated energy: Between -3784 and -3783
 

gpaw/build/build-CPU.md

@@ -126,6 +126,14 @@ GPAW that were tested:
 |:--------|:--------|:-------|:-------|:------|
 | 20.1.0  | 3.19.3  | 3.8.7  | 1.18.5 | 1.5.4 |
 | 20.10.0 | 3.20.1  | 3.9.4  | 1.19.5 | 1.5.4 |
+
+Note: On some systems compiling SciPy 1.5.4 with NumPy 1.19.5 produced errors. On those
+systems NumPy 1.18.5 was used.
+
+Other configurations that were only tested on a limited number of clusters:
+
+| GPAW    | ASE     | Python | NumPy  | SciPy |
+|:--------|:--------|:-------|:-------|:------|
 | 21.1.0  | 3.21.1  | 3.9.4  | 1.19.5 | 1.5.4 |
 
 
@@ -162,8 +170,6 @@ Other prerequisites:
   * Untar the file in the build directory.
 
 
-
-
 ### Installing Python from scratch
 
 The easiest way to get Python on your system is to download an existing distribution

gpaw/build/build-cuda.md

 GPGPUs
 ======
 
+**These instructions were not updated for UEABS release 2.2 as the GPU version
+was in full redevelopment at that time to also work for the AMD GPUs used in the
+LUMI pre-exascale system. They may or may not be useful anymore for the new
+versions once they are finished.**
+
 GPAW has a separate CUDA version available for NVIDIA GPGPUs. Source code is
 available in GPAW's repository as a separate branch called 'cuda'.
 An up-to-date development version is currently available at

gpaw/build/build-xeon-phi.md

-Xeon Phi MICs
-=============
-
-Intel's MIC architecture includes two distinct generations of processors:
-1st generation Knights Corner (KNC) and 2nd generation Knights Landing (KNL).
-KNCs require a specific offload version of GPAW, whereas KNLs use standard
-GPAW.
-
-
-KNC (Knights Corner)
---------------------
-
-For KNCs, GPAW has adopted an offload-to-the-MIC-coprocessor approach similar
-to GPGPUs. The offload version of GPAW uses the stream-based offload module
-pyMIC (https://github.com/01org/pyMIC) to offload computationally intensive
-matrix calculations to the MIC co-processors.
-
-Source code is available in GPAW's repository as a separate branch called
-'mic'. To obtain the code, use e.g. the following commands:
-```
-git clone https://gitlab.com/gpaw/gpaw.git
-cd gpaw
-git checkout mic
-```
-or download it from: https://gitlab.com/gpaw/gpaw/tree/mic
-
-A ready-to-use install package with examples and instructions is also
-available at:
-  https://github.com/mlouhivu/gpaw-mic-install-pack.git
-
-
-### Software requirements
-
-The offload version of GPAW is roughly equivalent to the 0.11.0 version of
-GPAW and thus has similar requirements (for software and versions).
-
-For example, the following versions are known to work:
-* Python (2.7.x)
-* ASE (3.9.1)
-* NumPy (1.9.2)
-* Libxc (2.1.x)
-
-In addition, pyMIC requires:
-* Intel compile environment with Intel MKL and Intel MPI
-* Intel MPSS (Manycore Platform Software Stack)
-
-### Install instructions
-
-In addition to using Intel compilers, there are three additional steps apart
-from standard installation:
-
-1. Compile and install Numpy with a suitable `site.cfg` to use MKL, e.g.
-
-   ```
-   [mkl]
-   library_dirs = /path/to/mkl/lib/intel64
-   include_dirs = /path/to/mkl/include
-   lapack_libs =
-   mkl_libs = mkl_rt
-   ```
-
-2. Compile and install [pyMIC](https://github.com/01org/pyMIC) before GPAW.
-
-3. Edit your GPAW setup script (`customize.py`) to add correct link and
-   compile options for offloading. The relevant lines are e.g.:
-
-   ```python
-   # offload to KNC
-   extra_compile_args += ['-qoffload-option,mic,compiler,"-qopenmp"']
-   extra_compile_args += ['-qopt-report-phase=offload']
-
-   # linker settings for MKL on KNC
-   mic_mkl_lib = '/path/to/mkl/lib/mic/'
-   extra_link_args += ['-offload-option,mic,link,"-L' + mic_mkl_lib \
-           + ' -lmkl_intel_lp64 -lmkl_intel_thread -lmkl_core -lpthread"']
-   ```
-
-
-KNL (Knights Landing)
----------------------
-
-For KNLs, one can use the standard version of GPAW, instead of the offload
-version used for KNCs. Please refer to the generic installation instructions
-for GPAW.
-
-### Software requirements
-  - https://wiki.fysik.dtu.dk/gpaw/install.html
-
-### Install instructions
-  - https://wiki.fysik.dtu.dk/gpaw/install.html
-  - https://wiki.fysik.dtu.dk/gpaw/platforms/platforms.html
-
-It is advisable to use Intel compile environment with Intel MKL and Intel MPI
-to take advantage of their KNL optimisations. To enable the AVX512 vector
-sets supported by KNLs, one needs to use the compiler option `-xMIC-AVX512`
-when installing GPAW.
-
-To improve performance, one may also link to Intel TBB to benefit from an
-optimised memory allocator (tbbmalloc). This can be done during installation
-or at run-time by setting environment variable LD_PRELOAD to point to the
-correct libraries, i.e. for example:
-```bash
-export LD_PRELOAD=$TBBROOT/lib/intel64/gcc4.7/libtbbmalloc_proxy.so.2
-export LD_PRELOAD=$LD_PRELOAD:$TBBROOT/lib/intel64/gcc4.7/libtbbmalloc.so.2
-```
-
-It may also be beneficial to use hugepages together with tbbmalloc
-(`export TBB_MALLOC_USE_HUGE_PAGES=1`).
-