From 2713ae0ae6923bbd635494eb3fa8d4bc2bed86f2 Mon Sep 17 00:00:00 2001
From: Andrew Emerson <a.emerson@cineca.it>
Date: Mon, 21 Feb 2022 13:53:51 +0000
Subject: [PATCH] Update quantum_espresso/README.md
---
quantum_espresso/README.md | 38 ++++++++++++++++----------------------
1 file changed, 16 insertions(+), 22 deletions(-)
diff --git a/quantum_espresso/README.md b/quantum_espresso/README.md
index 45adca5..636238a 100644
--- a/quantum_espresso/README.md
+++ b/quantum_espresso/README.md
@@ -9,7 +9,9 @@ Full documentation is available from the project website [QuantumEspresso](https
In this README we give information relevant for its use in the UEABS.
### Standard CPU version
-For the UEABS activity we have used mainly version v6.5 but later versions are now available.
+For the UEABS activity we have used mainly version v6.5 but we have also used versions 6.6-6.8, depending
+on availability of the software on the target architecture. We note that these later minor versions provide more functionality
+rather than significant performance enhancements.
### GPU version
The GPU port of Quantum Espresso is a version of the program which has been
@@ -18,39 +20,31 @@ experiments is v6.5a1, even though later versions may be available.
## Installation and requirements
### Standard
-The Quantum Espresso source can be downloaded from the projects GitHub repository,[QE GitHub](https://github.com/QEF/q-e/tags). Requirements can be found from the website but you will need a good FORTRAN and C compiler with an MPI library and optionally (but highly recommended) an optimised linear algebra library.
+The Quantum Espresso source can be downloaded from the projects download page [QE download](https://www.quantum-espresso.org/download-page/). Requirements can be found from the website but you will need a good FORTRAN and C compiler with an MPI library and optionally (but highly recommended) an optimised linear algebra library (see below).
### GPU version
-The GPU version, available for Nvidia GPUs, is now available from the Gitlab repository of Quantum Espresso. See here for more details [QE-GPU](https://gitlab.com/QEF/q-e-gpu/-/wikis/home)
+The GPU version, available for Nvidia GPUs is available from the same download page as the CPU code.
A short summary is given below:
-Essential
+Essential requirements
- * The PGI compiler version 17.10 or above.
+ * The NVIDIA HPC Software Development Kit (SDK) for compilation with CUDA FORTRAN (replacing the PGI compiler suite).
* You need NVIDIA TESLA GPUS such as Kepler (K20, K40, K80) or Pascal (P100) or Volta (V100).
No other cards are supported. NVIDIA TESLA P100 and V100 are strongly recommended
for their on-board memory capacity and double precision performance.
-Optional
+Optional requiremens (recommended)
* A parallel linear algebra library such as Scalapack, Intel MKL or IBM ESSL. If
none is available on your system then the installation can use a version supplied
- with the distribution.
+ with the distribution.
## Downloading the software
-### Standard
-From the website, for example:
-```bash
-wget https://github.com/QEF/q-e/archive/refs/tags/qe-6.7.0.tar.gz
-```
+### All versions
+From the website [QE download](https://www.quantum-espresso.org/download-page/). Note that as from 2022 it is now necessary to register
+to use the software.
-### GPU
-Available from the web site given above. You can use, for example, ```wget```
-to download the software:
-```bash
-wget https://gitlab.com/QEF/q-e-gpu/-/archive/qe-gpu-6.5a1/q-e-gpu-qe-gpu-6.5a1.tar.gz
-```
## Compiling and installing the application
@@ -69,7 +63,7 @@ make; make install
### GPU
The GPU version is configured similarly to the CPU version, the only exception being that the configure script
-will check for the presence of PGI and CUDA libraries.
+will check for the presence of the NVHPC SDK CUDA libraries.
A typical configure might be
```bash
@@ -83,17 +77,17 @@ For example,
```bash
./configure --with-cuda=$CUDA_HOME --with-cuda-cc=60 --with-cuda-runtime=9.2
```
-The __dev-tools/get_device_props.py__ script is available if you dont know these values.
+The __dev-tools/get_device_props.py__ script is available if you dont know these figures/.
Compilation is then performed as normal by
```
-make pw
+make -j8 pw
```
#### Example compilation of Quantum Espresso for GPU based machines
```bash
-module load pgi cuda
+module load hpc-sdk
./configure --with-cuda=$CUDA_HOME --with-cuda-cc=70 --with-cuda-runtime=10.2
make -j8 pw
```
--
GitLab