Update documentation

Author: Growl1234

docs/advanced/acceleration/cuda.md

@@ -29,7 +29,7 @@ To compile and use ABACUS in CUDA mode, you currently need to have an NVIDIA GPU
 
 Check the [Advanced Installation Options](https://abacus-rtd.readthedocs.io/en/latest/advanced/install.html#build-with-cuda-support) for the installation of CUDA version support.
 
-Setting both USE_ELPA and USE_CUDA to ON does not automatically enable ELPA to run on GPUs. ELPA support for GPUs needs to be enabled when ELPA is compiled. [enable GPU support](https://github.com/marekandreas/elpa/blob/master/documentation/INSTALL.md).
+Setting both `ENABLE_ELPA` and `USE_CUDA` to ON does not automatically enable ELPA to run on GPUs. ELPA support for GPUs needs to be enabled when ELPA is compiled. [enable GPU support](https://github.com/marekandreas/elpa/blob/master/documentation/INSTALL.md).
 
 The ABACUS program will automatically determine whether the current ELPA supports GPU based on the elpa/elpa_configured_options.h header file. Users can also check this header file to determine the GPU support of ELPA in their environment. ELPA introduced a new API elpa_setup_gpu in version 2023.11.001. So if you want to enable ELPA GPU in ABACUS, the ELPA version must be greater than or equal to 2023.11.001.
 

docs/advanced/input_files/input-main.md

@@ -1163,7 +1163,7 @@
   - scalapack_gvx: Use Scalapack to diagonalize the Hamiltonian.
   - cusolver: Use CUSOLVER to diagonalize the Hamiltonian, at least one GPU is needed.
   - cusolvermp: Use CUSOLVER to diagonalize the Hamiltonian, supporting multi-GPU devices. Note that you should set the number of MPI processes equal to the number of GPUs.
-  - elpa: The ELPA solver supports both CPU and GPU. By setting the `device` to GPU, you can launch the ELPA solver with GPU acceleration (provided that you have installed a GPU-supported version of ELPA, which requires you to manually compile and install ELPA, and the ABACUS should be compiled with -DUSE_ELPA=ON and -DUSE_CUDA=ON). The ELPA solver also supports multi-GPU acceleration.
+  - elpa: The ELPA solver supports both CPU and GPU. By setting the `device` to GPU, you can launch the ELPA solver with GPU acceleration (provided that you have installed a GPU-supported version of ELPA, which requires you to manually compile and install ELPA, and the ABACUS should be compiled with -DENABLE_ELPA=ON and -DUSE_CUDA=ON). The ELPA solver also supports multi-GPU acceleration.
 
   If you set ks_solver=`genelpa` for basis_type=`pw`, the program will stop with an error message:
 
@@ -1173,9 +1173,9 @@
 - **Default**: 
     - PW basis: cg.
     - LCAO basis:
-        - genelpa (if compiling option `USE_ELPA` has been set)
+        - genelpa (if compiling option `ENABLE_ELPA` has been set)
         - lapack (if compiling option `ENABLE_MPI` has not been set)
-        - scalapack_gvx (if compiling option `USE_ELPA` has not been set and compiling option `ENABLE_MPI` has been set)
+        - scalapack_gvx (if compiling option `ENABLE_ELPA` has not been set and compiling option `ENABLE_MPI` has been set)
         - cusolver (if compiling option `USE_CUDA` has been set)
 
 ### nbands

docs/advanced/install.md

@@ -73,7 +73,9 @@ The new EXX implementation depends on two external libraries:
 
 These two libraries are added as submodules in the [deps](https://github.com/deepmodeling/abacus-develop/tree/develop/deps) folder. Set `-DENABLE_LIBRI=ON` to build with these two libraries.
 
-If you prefer using manually downloaded libraries, provide `-DLIBRI_DIR=${path to your LibRI folder} -DLIBCOMM_DIR=${path to your LibComm folder}`.
+```{note}
+`ENABLE_LIBCOMM` is deprecated because LibComm is not a standalone ABACUS feature. CMake locates it automatically as a dependency of LibRI. If you prefer using manually downloaded libraries, enable LibRI and provide their locations via `-DLIBRI_DIR=/path/to/LibRI` and `-DLIBCOMM_DIR=/path/to/LibComm`.
+```
 
 
 ## Build with DFT-D4 support
@@ -134,13 +136,13 @@ If you are confident that your MPI supports CUDA Aware, you can add `-DUSE_CUDA_
 
 > Note: We recommend using the latest available compiler sets, since they offer faster implementations of math functions.
 
-This flag is disabled by default. To build math functions from source code, define `USE_ABACUS_LIBM` flag. It is expected to get a better performance on legacy versions of `gcc` and `clang`.
+This flag is disabled by default. To build math functions from source code, define `ENABLE_ABACUS_LIBM` flag. It is expected to get a better performance on legacy versions of `gcc` and `clang`.
 
 Currently supported math functions:
  `sin`, `cos`, `sincos`, `exp`, `cexp`
 
 ```bash
-cmake -B build -DUSE_ABACUS_LIBM=1
+cmake -B build -DENABLE_ABACUS_LIBM=1
 ```
 
 ## Build with PEXSI support

docs/parameters.yaml

@@ -544,14 +544,14 @@ parameters:
       * scalapack_gvx: Use Scalapack to diagonalize the Hamiltonian.
       * cusolver: Use CUSOLVER to diagonalize the Hamiltonian, at least one GPU is needed.
       * cusolvermp: Use CUSOLVER to diagonalize the Hamiltonian, supporting multi-GPU devices. Note that you should set the number of MPI processes equal to the number of GPUs.
-      * elpa: The ELPA solver supports both CPU and GPU. By setting the `device` to GPU, you can launch the ELPA solver with GPU acceleration (provided that you have installed a GPU-supported version of ELPA, which requires you to manually compile and install ELPA, and the ABACUS should be compiled with -DUSE_ELPA=ON and -DUSE_CUDA=ON). The ELPA solver also supports multi-GPU acceleration.
+      * elpa: The ELPA solver supports both CPU and GPU. By setting the `device` to GPU, you can launch the ELPA solver with GPU acceleration (provided that you have installed a GPU-supported version of ELPA, which requires you to manually compile and install ELPA, and the ABACUS should be compiled with -DENABLE_ELPA=ON and -DUSE_CUDA=ON). The ELPA solver also supports multi-GPU acceleration.
 
       If you set ks_solver=`genelpa` for basis_type=`pw`, the program will stop with an error message:
 
       ``text genelpa can not be used with plane wave basis. ``
 
       Then the user has to correct the input file and restart the calculation.
-    default_value: "\n    - PW basis: cg.\n    - LCAO basis:\n        - genelpa (if compiling option `USE_ELPA` has been set)\n        - lapack (if compiling option `ENABLE_MPI` has not been set)\n        - scalapack_gvx (if compiling option `USE_ELPA` has not been set and compiling option `ENABLE_MPI` has been set)\n        - cusolver (if compiling option `USE_CUDA` has been set)"
+    default_value: "\n    - PW basis: cg.\n    - LCAO basis:\n        - genelpa (if compiling option `ENABLE_ELPA` has been set)\n        - lapack (if compiling option `ENABLE_MPI` has not been set)\n        - scalapack_gvx (if compiling option `ENABLE_ELPA` has not been set and compiling option `ENABLE_MPI` has been set)\n        - cusolver (if compiling option `USE_CUDA` has been set)"
     unit: ""
     availability: ""
   - name: nbands

docs/quick_start/easy_install.md

@@ -163,7 +163,7 @@ Here, 'build' is the path for building ABACUS; and '-D' is used for setting up s
 
   - `FFTW3_DIR`: Path to FFTW3.
   - `LIBRI_DIR`: (Optional) Path to LibRI.
-  - `LIBCOMM_DIR`: (Optional) Path to LibComm.
+  - `LIBCOMM_DIR`: (Optional) Path to LibComm when `ENABLE_LIBRI=ON`.
 
 ```{important}
 For some dependencies built with CMake, such as Libxc, dftd4, cereal, and RapidJSON, you'll have to add their prefix paths to the environment variable `CMAKE_PREFIX_PATH` so that CMake can correctly find and use their CMake configuration files. A non-general variable such as `PKG_DIR` is discouraged for these packages.
@@ -172,14 +172,14 @@ For some dependencies built with CMake, such as Libxc, dftd4, cereal, and RapidJ
 - Components: The values of these variables should be 'ON', '1' or 'OFF', '0'. The default values are given below.
   - `ENABLE_LCAO=ON`: Enable LCAO calculation. If SCALAPACK, ELPA or CEREAL is absent and only require plane-wave calculations, the feature of calculating LCAO basis can be turned off.
   - `ENABLE_LIBXC=OFF`: [Enable Libxc](../advanced/install.md#add-libxc-support) to suppport variety of functionals.
-  - `ENABLE_LIBRI=OFF`: [Enable LibRI](../advanced/install.md#add-libri-support) to suppport variety of functionals. If `LIBRI_DIR` and `LIBCOMM_DIR` are defined, `ENABLE_LIBRI` will set to 'ON'.
-  - `USE_OPENMP=ON`: Enable OpenMP support. Building ABACUS without OpenMP is not fully tested yet.
+  - `ENABLE_LIBRI=OFF`: [Enable LibRI](../advanced/install.md#add-libri-support) and its LibComm dependency for hybrid-functional calculations. Set `LIBRI_DIR` and `LIBCOMM_DIR` to use manually installed libraries.
+  - `ENABLE_OPENMP=ON`: Enable OpenMP support. Building ABACUS without OpenMP is not fully tested yet.
   - `BUILD_TESTING=OFF`: [Build unit tests](../advanced/install.md#build-unit-tests).
   - `ENABLE_GOOGLEBENCH=OFF`: [Build performance tests](../advanced/install.md#build-performance-tests)
   - `ENABLE_MPI=ON`: Enable MPI parallel compilation. If set to `OFF`, a serial version of ABACUS will be compiled. It now supports both PW and LCAO.
   - `ENABLE_COVERAGE=OFF`: Build ABACUS executable supporting [coverage analysis](../CONTRIBUTING.md#generating-code-coverage-report). This feature has a drastic impact on performance.
   - `ENABLE_ASAN=OFF`: Build with Address Sanitizer. This feature would help detecting memory problems.
-  - `USE_ELPA=ON`: Use ELPA library in LCAO calculations. If this value is set to OFF, ABACUS can be compiled without ELPA library.
+  - `ENABLE_ELPA=ON`: Use ELPA library in LCAO calculations. If this value is set to OFF, ABACUS can be compiled without ELPA library.
 
 Here is an example: