Initial very incomplete new README for gpaw.

gpaw/README.md

-PRACE Benchmarks for GPAW
-=========================
+Preparation PRACE Benchmarks for GPAW
+=====================================
 
 GPAW
 ----
@@ -15,32 +15,61 @@ and systematic converge properties.
 GPAW is written mostly in Python, but includes also computational kernels
 written in C as well as leveraging external libraries such as NumPy, BLAS and
 ScaLAPACK. Parallelisation is based on message-passing using MPI with no
-support for multithreading. Development branches for GPGPUs and MICs include
-support for offloading to accelerators using either CUDA or pyMIC/libxsteam,
-respectively.
+support for multithreading. 
+
+Note that GPAW version numbering changed in 2019. Version 1.5.3 is the
+last version with the old numbering. In 2019 the development team switched 
+to a version numbering scheme based on year, month and patchlevel, e.g.,
+19.8.1 for the second version released in August 2019.
+
+There have been various developments for GPGPUs and MICs in the past
+using either CUDA or pyMIC/libxstream. Many of those branches see no
+development anymore and the information on the
+[GPU page of the GPAW Wiki](https://wiki.fysik.dtu.dk/gpaw/devel/projects/gpu.html)
+is also outdated. 
+
+* Outdated branches in the [GitLab repository](https://gitlab.com/gpaw/gpaw)
+  include the branch [rpa-gpu-expt](https://gitlab.com/gpaw/gpaw/tree/rpa-gpu-expt)
+  and [cuda](https://gitlab.com/gpaw/gpaw/tree/cuda).
+* The current CUDA development version is available in a
+  [separate GitLab for CUDA development, cuda branch](https://gitlab.com/mlouhivu/gpaw/tree/cuda).
+  This version should correspond to the Aalto version mentioned on the GPAW Wiki.
+  As of early 2020, that version seems to be derived from the 1.5.2 CPU version
+  (at least, I could find a commit that claims to merge the 1.5.2 code).
 
 
 ### Download
 
-GPAW is freely available under the GPL license. The source code can be
-downloaded from the [Git repository](https://gitlab.com/gpaw/gpaw) or as
+GPAW is freely available under the GPL license. 
+
+The source code of the CPU version can be
+downloaded from the [GitLab repository](https://gitlab.com/gpaw/gpaw) or as
 a tar package for each release from [PyPi](https://pypi.org/simple/gpaw/).
 
-For example, to get version 1.4.0 using git:
+For example, to get version 19.8.1 using git:
 ```bash
-git clone -b 1.4.0 https://gitlab.com/gpaw/gpaw.git
+git clone -b 19.8.1 https://gitlab.com/gpaw/gpaw.git
+```
+
+The CUDA development version is available in 
+[the cuda branch of a separate GitLab](https://gitlab.com/mlouhivu/gpaw/tree/cuda).
+To get the current development version using git:
+```bash
+git clone -b cuda https://gitlab.com/mlouhivu/gpaw.git
 ```
 
 
 ### Install
 
-Generic [installation instructions](https://wiki.fysik.dtu.dk/gpaw/install.html)
+Official generic [installation instructions](https://wiki.fysik.dtu.dk/gpaw/install.html)
 and
 [platform specific examples](https://wiki.fysik.dtu.dk/gpaw/platforms/platforms.html)
-are provided in the [GPAW wiki](https://wiki.fysik.dtu.dk/gpaw/). For
-accelerators, architecture specific instructions and requirements are also
-provided for [Xeon Phis](build/build-xeon-phi.md) and for
-[GPGPUs](build/build-cuda.md).
+are provided in the [GPAW wiki](https://wiki.fysik.dtu.dk/gpaw/). 
+
+The UEABS repository contains additional instructions:
+* [general instructions](installation.md) - Under development
+* [GPGPUs](build/build-cuda.md) - To check
+* [Xeon Phis (KNC)](build/build-xeon-phi.md) - Outdated
 
 Example [build scripts](build/examples/) are also available for some PRACE
 systems.

gpaw/README.old.md

+PRACE Benchmarks for GPAW
+=========================
+
+GPAW
+----
+
+### Code description
+
+[GPAW](https://wiki.fysik.dtu.dk/gpaw/) is a density-functional theory (DFT)
+program for ab initio electronic structure calculations using the projector
+augmented wave method. It uses a uniform real-space grid representation of the
+electronic wavefunctions that allows for excellent computational scalability
+and systematic converge properties.
+
+GPAW is written mostly in Python, but includes also computational kernels
+written in C as well as leveraging external libraries such as NumPy, BLAS and
+ScaLAPACK. Parallelisation is based on message-passing using MPI with no
+support for multithreading. Development branches for GPGPUs and MICs include
+support for offloading to accelerators using either CUDA or pyMIC/libxsteam,
+respectively.
+
+
+### Download
+
+GPAW is freely available under the GPL license. The source code can be
+downloaded from the [Git repository](https://gitlab.com/gpaw/gpaw) or as
+a tar package for each release from [PyPi](https://pypi.org/simple/gpaw/).
+
+For example, to get version 1.4.0 using git:
+```bash
+git clone -b 1.4.0 https://gitlab.com/gpaw/gpaw.git
+```
+
+
+### Install
+
+Generic [installation instructions](https://wiki.fysik.dtu.dk/gpaw/install.html)
+and
+[platform specific examples](https://wiki.fysik.dtu.dk/gpaw/platforms/platforms.html)
+are provided in the [GPAW wiki](https://wiki.fysik.dtu.dk/gpaw/). For
+accelerators, architecture specific instructions and requirements are also
+provided for [Xeon Phis](build/build-xeon-phi.md) and for
+[GPGPUs](build/build-cuda.md).
+
+Example [build scripts](build/examples/) are also available for some PRACE
+systems.
+
+
+Benchmarks
+----------
+
+### Download
+
+The benchmark set is available in the [benchmark/](benchmark/) directory or
+alternatively, for download, either directly from the development
+[Git repository](https://github.com/mlouhivu/gpaw-benchmarks/tree/prace)
+or from the PRACE RI website (http://www.prace-ri.eu/ueabs/).
+
+To download the benchmarks, use e.g. the following command:
+```
+git clone -b prace https://github.com/mlouhivu/gpaw-benchmarks
+```
+
+
+### Benchmark cases
+
+#### Case S: Carbon nanotube
+
+A ground state calculation for a carbon nanotube in vacuum. By default uses a
+6-6-10 nanotube with 240 atoms (freely adjustable) and serial LAPACK with an
+option to use ScaLAPACK. Expected to scale up to 10 nodes and/or 100 MPI
+tasks.
+
+Input file: [benchmark/carbon-nanotube/input.py](benchmark/carbon-nanotube/input.py)
+
+#### Case M: Copper filament
+
+A ground state calculation for a copper filament in vacuum. By default uses a
+2x2x3 FCC lattice with 71 atoms (freely adjustable) and ScaLAPACK for
+parallelisation. Expected to scale up to 100 nodes and/or 1000 MPI tasks.
+
+Input file: [benchmark/carbon-nanotube/input.py](benchmark/copper-filament/input.py)
+
+#### Case L: Silicon cluster
+
+A ground state calculation for a silicon cluster in vacuum. By default the
+cluster has a radius of 15Å (freely adjustable) and consists of 702 atoms,
+and ScaLAPACK is used for parallelisation. Expected to scale up to 1000 nodes
+and/or 10000 MPI tasks.
+
+Input file: [benchmark/carbon-nanotube/input.py](benchmark/silicon-cluster/input.py)
+
+
+### Running the benchmarks
+
+No special command line options or environment variables are needed to run the
+benchmarks on most systems. One can simply say e.g.
+```
+srun gpaw-python input.py
+```
+
+#### Special case: KNC
+
+For KNCs (Xeon Phi Knights Corner), one needs to use a wrapper script to set
+correct affinities for pyMIC (see
+[scripts/affinity-wrapper.sh](scripts/affinity-wrapper.sh) for an example)
+and to set two environment variables for GPAW:
+```shell
+GPAW_OFFLOAD=1  # (to turn on offloading)
+GPAW_PPN=<no. of MPI tasks per node>
+```
+
+For example, in a SLURM system, this could be:
+```shell
+GPAW_PPN=12 GPAW_OFFLOAD=1 mpirun -np 256 -bootstrap slurm \
+  ./affinity-wrapper.sh 12 gpaw-python input.py
+```
+
+#### Examples
+
+Example [job scripts](scripts/) (`scripts/job-*.sh`) are provided for
+different PRACE systems that may offer a helpful starting point.