Lbfgs0

.github/workflows/build_test_cmake.yml

@@ -17,10 +17,10 @@ jobs:
             name: "Build with Intel toolchain"
 
           - tag: gnu
-            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_LIBRI=1 -DENABLE_PAW=1"
+            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_MLKEDF=1 -DENABLE_LIBRI=1 -DENABLE_PAW=1"
             name: "Build extra components with GNU toolchain"
           - tag: intel
-            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_LIBRI=1"
+            build_args: "-DENABLE_LIBXC=1 -DENABLE_DEEPKS=1 -DENABLE_MLKEDF=1 -DENABLE_LIBRI=1"
             name: "Build extra components with Intel toolchain"
 
           - tag: cuda

.github/workflows/coverage.yml

@@ -15,7 +15,7 @@ jobs:
         uses: actions/checkout@v4
       - name: Install Requirements for Coverage Testing
         run: |
-          apt update && apt install -y lcov gpg
+          apt update && apt install -y lcov gpg curl jq ca-certificates
       - name: Building
         run: |
           cmake -B build -DENABLE_COVERAGE=ON -DBUILD_TESTING=ON -DENABLE_DEEPKS=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_PAW=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON
@@ -27,8 +27,10 @@ jobs:
         run: |
           cmake --build build --target test ARGS="-V --timeout 21600" || exit 0
       - name: Upload Coverage to Codecov
-        uses: codecov/codecov-action@v4
+        uses: codecov/codecov-action@v5
         if: ${{ ! cancelled() }}
         with:
-          gcov: true
+          fail_ci_if_error: true
           token: ${{ secrets.CODECOV_TOKEN }}
+          skip_validation: true
+          verbose: true

.github/workflows/test.yml

@@ -31,15 +31,18 @@ jobs:
 
       - name: Configure
         run: |
-          cmake -B build -DBUILD_TESTING=ON -DENABLE_DEEPKS=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_PAW=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON  -DCMAKE_EXPORT_COMPILE_COMMANDS=1
+          cmake -B build -DBUILD_TESTING=ON -DENABLE_DEEPKS=ON -DENABLE_MLKEDF=ON -DENABLE_LIBXC=ON -DENABLE_LIBRI=ON -DENABLE_PAW=ON -DENABLE_GOOGLEBENCH=ON -DENABLE_RAPIDJSON=ON  -DCMAKE_EXPORT_COMPILE_COMMANDS=1
 
-      - uses: pre-commit/[email protected]
-        with:
-          extra_args:
-            --from-ref ${{ github.event.pull_request.base.sha }}
-              --to-ref ${{ github.event.pull_request.head.sha }}
-        continue-on-error: true
-      - uses: pre-commit-ci/[email protected]
+# Temporarily removed because no one maintains this now.
+# And it will break the CI test workflow.
+
+#      - uses: pre-commit/[email protected]
+#        with:
+#          extra_args:
+#            --from-ref ${{ github.event.pull_request.base.sha }}
+#              --to-ref ${{ github.event.pull_request.head.sha }}
+#        continue-on-error: true
+#      - uses: pre-commit-ci/[email protected]
 
       - name: Build
         run: |

.gitignore

@@ -17,9 +17,10 @@ STRU_READIN_ADJUST.cif
 build
 dist
 .idea
-toolchain.tar.gz
 time.json
 *.pyc
 __pycache__
 abacus.json
 *.npy
+toolchain/install/
+toolchain/abacus_env.sh

CMakeLists.txt

@@ -12,6 +12,7 @@ project(
 
 option(ENABLE_LCAO "Enable LCAO calculation." ON)
 option(ENABLE_DEEPKS "Enable DeePKS functionality" OFF)
+option(ENABLE_MLKEDF "Enable Machine Learning based KEDF for OFDFT" OFF)
 option(ENABLE_LIBXC "Enable LibXC functionality" OFF)
 option(USE_CUDA "Enable support to CUDA for ABACUS." OFF)
 option(ENABLE_FLOAT_FFTW "Enable support to single precision FFTW library." OFF)
@@ -41,6 +42,7 @@ option(ENABLE_PEXSI "Enable support for PEXSI." OFF)
 option(ENABLE_CUSOLVERMP "Enable cusolvermp." OFF)
 option(USE_DSP "Enable DSP usage." OFF)
 option(USE_CUDA_ON_DCU "Enable CUDA on DCU" OFF)
+option(USE_CUDA_MPI "Enable CUDA-aware MPI" OFF)
 
 # enable json support
 if(ENABLE_RAPIDJSON)
@@ -131,6 +133,10 @@ if (USE_CUDA_ON_DCU)
   add_compile_definitions(__CUDA_ON_DCU)
 endif()
 
+if (USE_CUDA_MPI)
+  add_compile_definitions(__CUDA_MPI)
+endif()
+
 list(APPEND CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake)
 
 if(ENABLE_COVERAGE)
@@ -235,6 +241,9 @@ if(ENABLE_LCAO)
     add_compile_definitions(__PEXSI)
     set(CMAKE_CXX_STANDARD 14)
   endif()
+  if(NEW_GINT)
+    add_compile_definitions(__NEW_GINT)
+  endif()
 else()
   set(ENABLE_DEEPKS OFF)
   set(ENABLE_LIBRI OFF)
@@ -253,8 +262,12 @@ if(ENABLE_MPI)
 endif()
 
 if (USE_DSP)
-  target_link_libraries(${ABACUS_BIN_NAME} ${DIR_MTBLAS_LIBRARY})
   add_compile_definitions(__DSP)
+  target_link_libraries(${ABACUS_BIN_NAME} ${OMPI_LIBRARY1})
+  include_directories(${MTBLAS_FFT_DIR}/libmtblas/include)
+  include_directories(${MT_HOST_DIR}/include)
+  target_link_libraries(${ABACUS_BIN_NAME} ${MT_HOST_DIR}/hthreads/lib/libhthread_device.a)
+  target_link_libraries(${ABACUS_BIN_NAME} ${MT_HOST_DIR}/hthreads/lib/libhthread_host.a)
 endif()
 
 find_package(Threads REQUIRED)
@@ -339,9 +352,19 @@ if(USE_CUDA)
     endif()
     if (ENABLE_CUSOLVERMP)
       add_compile_definitions(__CUSOLVERMP)
+      find_library(CAL_LIBRARY
+          NAMES cal
+          PATHS ${CAL_CUSOLVERMP_PATH}
+          NO_DEFAULT_PATH
+      )
+      find_library(CUSOLVERMP_LIBRARY
+          NAMES cusolverMp
+          PATHS ${CAL_CUSOLVERMP_PATH}
+          NO_DEFAULT_PATH
+      )
       target_link_libraries(${ABACUS_BIN_NAME}
-          cal
-          cusolverMp
+          ${CAL_LIBRARY}
+          ${CUSOLVERMP_LIBRARY}
       )
     endif()
   endif()
@@ -425,10 +448,8 @@ else()
   find_package(Lapack REQUIRED)
   include_directories(${FFTW3_INCLUDE_DIRS})
   list(APPEND math_libs FFTW3::FFTW3 LAPACK::LAPACK BLAS::BLAS)
-
   find_package(ScaLAPACK REQUIRED)
   list(APPEND math_libs ScaLAPACK::ScaLAPACK)
-
   if(USE_OPENMP)
     list(APPEND math_libs FFTW3::FFTW3_OMP)
   endif()
@@ -469,10 +490,29 @@ if(ENABLE_DEEPKS)
   add_compile_definitions(__DEEPKS)
 endif()
 
+if(ENABLE_MLKEDF)
+  target_link_libraries(${ABACUS_BIN_NAME} hamilt_mlkedf)
+
+  find_path(libnpy_SOURCE_DIR npy.hpp HINTS ${libnpy_INCLUDE_DIR})
+  if(NOT libnpy_SOURCE_DIR)
+    include(FetchContent)
+    FetchContent_Declare(
+      libnpy
+      GIT_REPOSITORY https://github.com/llohse/libnpy.git
+      GIT_SHALLOW TRUE
+      GIT_PROGRESS TRUE)
+    FetchContent_MakeAvailable(libnpy)
+  else()
+    include_directories(${libnpy_INCLUDE_DIR})
+  endif()
+  include_directories(${libnpy_SOURCE_DIR}/include)
+  add_compile_definitions(__MLKEDF)
+endif()
+
 # Torch uses outdated components to detect CUDA arch, causing failure on
 # latest CUDA kits. Set CMake variable TORCH_CUDA_ARCH_LIST in the form of
 # "major.minor" if required.
-if(ENABLE_DEEPKS OR DEFINED Torch_DIR)
+if(ENABLE_DEEPKS OR ENABLE_MLKEDF OR DEFINED Torch_DIR)
   find_package(Torch REQUIRED)
   if(NOT Torch_VERSION VERSION_LESS "2.1.0")
     set_if_higher(CMAKE_CXX_STANDARD 17)

Dockerfile.intel

@@ -44,6 +44,9 @@ RUN source /opt/intel/oneapi/setvars.sh && \
     ln -s /usr/local/include/elpa_openmp-$ELPA_VER/elpa /usr/local/include/ && \
     cd /tmp && rm -rf elpa-$ELPA_VER
 
+RUN cd /tmp && git clone https://github.com/Tencent/rapidjson.git && cp -r rapidjson/include/rapidjson /usr/include/ \
+    && rm -rf rapidjson
+
 RUN wget https://download.pytorch.org/libtorch/cpu/libtorch-cxx11-abi-shared-with-deps-2.0.0%2Bcpu.zip \
         --no-check-certificate --quiet -O libtorch.zip && \
     unzip -q libtorch.zip -d /opt  && rm libtorch.zip

README.md

@@ -12,7 +12,7 @@
 
 # About ABACUS
 
-ABACUS (Atomic-orbital Based Ab-initio Computation at UStc) is an open-source package based on density functional theory (DFT). The package utilizes both plane wave and numerical atomic basis sets with the usage of norm-conserving pseudopotentials to describe the interactions between nuclear ions and valence electrons. ABACUS supports LDA, GGA, meta-GGA, and hybrid functionals. Apart from single-point calculations, the package allows geometry optimizations and ab-initio molecular dynamics with various ensembles. The package also provides a variety of advanced functionalities for simulating materials, including the DFT+U, VdW corrections, and implicit solvation model, etc. In addition, ABACUS strives to provide a general infrastructure to facilitate the developments and applications of novel machine-learning-assisted DFT methods (DeePKS, DP-GEN, DeepH, DeePTB etc.) in molecular and material simulations.
+ABACUS (**A**tomic-orbital **B**ased **A**b-initio **C**omputation at **US**tc) is an open-source package based on density functional theory (DFT). The package utilizes both plane wave and numerical atomic basis sets with the usage of pseudopotentials to describe the interactions between nuclear ions and valence electrons. ABACUS supports LDA, GGA, meta-GGA, and hybrid functionals. Apart from single-point calculations, the package allows geometry optimizations and ab-initio molecular dynamics with various ensembles. The package also provides a variety of advanced functionalities for simulating materials, including the DFT+U, VdW corrections, and implicit solvation model, etc. In addition, ABACUS strives to provide a general infrastructure to facilitate the developments and applications of novel machine-learning-assisted DFT methods (DeePKS, DP-GEN, DeepH, DeePTB etc.) in molecular and material simulations.
 
 # Online Documentation
 For detailed documentation, please refer to [our documentation website](https://abacus.deepmodeling.com/).

cmake/FindMKL.cmake

@@ -83,7 +83,7 @@ endif()
 endif() # MKL::MKL
 
 # For compatibility with legacy libpaw_interface CMakeLists.txt
-if(TARGET MKL::MKL)
+if(TARGET MKL::MKL AND NOT TARGET IntelMKL::MKL)
   add_library(IntelMKL::MKL ALIAS MKL::MKL)
 endif()
 

docs/CITATIONS.md

@@ -4,10 +4,18 @@ The following references are required to be cited when using ABACUS. Specificall
 
 - **For general purpose:**
 
+    *For LCAO basis:*
+
     Mohan Chen, G. C. Guo, and Lixin He. "Systematically improvable optimized atomic basis sets for ab initio calculations." Journal of Physics: Condensed Matter 22.44 (2010): 445501.
 
     Pengfei Li, et al. "Large-scale ab initio simulations based on systematically improvable atomic basis." Computational Materials Science 112 (2016): 503-517.
 
+    Peize Lin, Xinguo Ren, Xiaohui Liu, Lixin He. Ab initio electronic structure calculations based on numerical atomic orbitals: Basic fomalisms and recent progresses. Wiley Interdisciplinary Reviews: Computational Molecular Science, 2024, 14(1): e1687.
+
+    *For LCAO and PW basis:*
+
+    Weiqing Zhou, Deye Zheng, Qianrui Liu, et al. ABACUS: An Electronic Structure Analysis Package for the AI Era. arXiv preprint arXiv:2501.08697, 2025.
+
 - **If Stochastic DFT is used:**
 
     Qianrui Liu, and Mohan Chen. "Plane-Wave-Based Stochastic-Deterministic Density Functional Theory for Extended Systems." <https://arxiv.org/abs/2204.05662>.
@@ -33,3 +41,9 @@ The following references are required to be cited when using ABACUS. Specificall
     Peize Lin, Xinguo Ren, and Lixin He. "Efficient Hybrid Density Functional Calculations for Large Periodic Systems Using Numerical Atomic Orbitals." Journal of Chemical Theory and Computation 2021, 17(1), 222–239.
 
     Peize Lin, Xinguo Ren, and Lixin He. "Accuracy of Localized Resolution of the Identity in Periodic Hybrid Functional Calculations with Numerical Atomic Orbitals." Journal of Physical Chemistry Letters 2020, 11, 3082-3088.
+
+- **If ML-KEDF is used:**
+
+    Sun, Liang, and Mohan Chen. "Machine learning based nonlocal kinetic energy density functional for simple metals and alloys." Physical Review B 109.11 (2024): 115135.
+
+    Sun, Liang, and Mohan Chen. "Multi-channel machine learning based nonlocal kinetic energy density functional for semiconductors." Electronic Structure 6.4 (2024): 045006.

docs/DevelopingTeam.md

@@ -4,5 +4,5 @@ The current development team consists the following research groups/affiliations
 - University of Science and Technology of China (Dr. Lixin He)
 - Peking University (Dr. Mohan Chen)
 - Institute of Physics, Chinese Academy of Sciences (Dr. Xinguo Ren)
-- Beijing AI for Science Institute
-- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. 
+- Beijing AI for Science Institute (Dr. Daye Zheng)
+- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center (Dr. Lixin He).