Document PPCG device bridge status

Author: cheerly-pku

docs/advanced/input_files/input-main.md

@@ -1116,7 +1116,7 @@
   - bpcg: The BPCG method, which is a block-parallel Conjugate Gradient (CG) method, typically exhibits higher acceleration in a GPU environment.
   - dav: The Davidson algorithm.
   - dav_subspace: The Davidson algorithm without orthogonalization operation, this method is the most recommended for efficiency. pw_diag_ndim can be set to 2 for this method.
-  - ppcg: The projection preconditioned conjugate-gradient method, currently available for CPU plane-wave calculations.
+  - ppcg: The projection preconditioned conjugate-gradient method. It is optimized and validated for CPU plane-wave calculations; non-CPU devices use a transitional host/device bridge.
 
   For numerical atomic orbitals basis,
 

docs/advanced/scf/hsolver.md

@@ -4,7 +4,7 @@
 
 Method of explicit solving KS-equation can be chosen by variable "ks_solver" in INPUT file.
 
-When "basis_type = pw", `ks_solver` can be `cg`, `bpcg`, `dav`, `dav_subspace`, or `ppcg`. The default setting `cg` is recommended, which is a band-by-band conjugate-gradient diagonalization method. The `dav` and `dav_subspace` settings use Davidson-style subspace diagonalization and can be tried to improve performance. The `ppcg` setting uses the projection preconditioned conjugate-gradient method and is currently available for CPU plane-wave calculations.
+When "basis_type = pw", `ks_solver` can be `cg`, `bpcg`, `dav`, `dav_subspace`, or `ppcg`. The default setting `cg` is recommended, which is a band-by-band conjugate-gradient diagonalization method. The `dav` and `dav_subspace` settings use Davidson-style subspace diagonalization and can be tried to improve performance. The `ppcg` setting uses the projection preconditioned conjugate-gradient method. It is optimized and validated for CPU plane-wave calculations; non-CPU devices use a transitional host/device bridge.
 
 When "basis_type = lcao", `ks_solver` can be `genelpa` or `scalapack_gvx`. The default setting `genelpa` is recommended, which is based on ELPA (EIGENVALUE SOLVERS FOR PETAFLOP APPLICATIONS) (https://elpa.mpcdf.mpg.de/) and the kernel is auto choosed by GENELPA(https://github.com/pplab/GenELPA), usually faster than the setting of "scalapack_gvx", which is based on ScaLAPACK(Scalable Linear Algebra PACKage)  
 

docs/parameters.yaml

@@ -521,7 +521,7 @@ parameters:
       * bpcg: The BPCG method, which is a block-parallel Conjugate Gradient (CG) method, typically exhibits higher acceleration in a GPU environment.
       * dav: The Davidson algorithm.
       * dav_subspace: The Davidson algorithm without orthogonalization operation, this method is the most recommended for efficiency. `pw_diag_ndim` can be set to 2 for this method.
-      * ppcg: The projection preconditioned conjugate-gradient method, currently available for CPU plane-wave calculations.
+      * ppcg: The projection preconditioned conjugate-gradient method. It is optimized and validated for CPU plane-wave calculations; non-CPU devices use a transitional host/device bridge.
 
       For numerical atomic orbitals basis,
 

source/source_io/module_parameter/read_input_item_elec_stru.cpp

@@ -56,7 +56,7 @@ For plane-wave basis,
 * bpcg: The BPCG method, which is a block-parallel Conjugate Gradient (CG) method, typically exhibits higher acceleration in a GPU environment.
 * dav: The Davidson algorithm.
 * dav_subspace: The Davidson algorithm without orthogonalization operation, this method is the most recommended for efficiency. `pw_diag_ndim` can be set to 2 for this method.
-* ppcg: The projection preconditioned conjugate-gradient method, currently available for CPU plane-wave calculations.
+* ppcg: The projection preconditioned conjugate-gradient method. It is optimized and validated for CPU plane-wave calculations; non-CPU devices use a transitional host/device bridge.
 
 For numerical atomic orbitals basis,