rename gpu options, update docs

.github/workflows/c-cpp.yaml

@@ -18,7 +18,7 @@ jobs:
     strategy:
       matrix:
         os: 
-          - [self-hosted, ubuntu18]
+          - [self-hosted, ubuntu22]
           - [self-hosted, macos]
         backend:
           - ga
@@ -36,31 +36,31 @@ jobs:
         use_scalapack:
           - no-scalapack         
         include:
-          - os: [self-hosted, ubuntu18]
+          - os: [self-hosted, ubuntu22]
             mpi_impl: openmpi
             cxx: clang++
             cc: clang
             fc: gfortran
             backend: ga
             use_cuda: no-cuda
             use_scalapack: no-scalapack
-          - os: [self-hosted, ubuntu18]
+          - os: [self-hosted, ubuntu22]
             mpi_impl: openmpi
             cxx: g++
             cc: gcc
             fc: gfortran
             backend: ga
             use_cuda: cuda
             use_scalapack: no-scalapack
-          - os: [self-hosted, ubuntu18]
+          - os: [self-hosted, ubuntu22]
             mpi_impl: openmpi
             cxx: g++
             cc: gcc
             fc: gfortran
             backend: upcxx
             use_cuda: cuda
             use_scalapack: no-scalapack      
-          - os: [self-hosted, ubuntu18]
+          - os: [self-hosted, ubuntu22]
             mpi_impl: openmpi
             cxx: g++
             cc: gcc
@@ -110,7 +110,7 @@ jobs:
       shell: bash
 
     - name: Set cache path linux
-      if: ${{ matrix.os[1] == 'ubuntu18' }}
+      if: ${{ matrix.os[1] == 'ubuntu22' }}
       id: set-cache-path-linux
       run: |
         echo "exachem_cache_path=/hpc/software/CI/cache/exachem_cache" >> $GITHUB_ENV
@@ -139,7 +139,7 @@ jobs:
         echo "USE_SCALAPACK=ON" >> $GITHUB_ENV
 
     - name: load llvm
-      if: ${{ matrix.cc == 'clang' && matrix.cxx == 'clang++' && matrix.os[1] == 'ubuntu18' }}
+      if: ${{ matrix.cc == 'clang' && matrix.cxx == 'clang++' && matrix.os[1] == 'ubuntu22' }}
       shell: bash
       run: |
         module load llvm/11.1.0
@@ -220,7 +220,7 @@ jobs:
         # TAMM build
         git clone https://github.com/NWChemEx/TAMM $GITHUB_WORKSPACE/TAMM
         cd $GITHUB_WORKSPACE/TAMM
-        cmake -H. -Bbuild -DCMAKE_INSTALL_PREFIX=${{ env.INSTALL_PATH }} -DLINALG_VENDOR=${{ env.LA_VENDOR }} -DGPU_ARCH=70 -DMODULES="CC" -DUSE_CUDA=${{ env.USE_CUDA }} -DUSE_SCALAPACK=${{ env.USE_SCALAPACK }}
+        cmake -H. -Bbuild -DCMAKE_INSTALL_PREFIX=${{ env.INSTALL_PATH }} -DLINALG_VENDOR=${{ env.LA_VENDOR }} -DGPU_ARCH=70 -DMODULES="CC" -DTAMM_ENABLE_CUDA=${{ env.USE_CUDA }} -DUSE_SCALAPACK=${{ env.USE_SCALAPACK }}
         cd build
         make -j${{ env.EC_NPROC }}
         make install
@@ -250,7 +250,7 @@ jobs:
         # TAMM build
         git clone https://github.com/NWChemEx/TAMM $GITHUB_WORKSPACE/TAMM
         cd $GITHUB_WORKSPACE/TAMM
-        UPCXX_CODEMODE=O3 CXX=upcxx cmake -H. -Bbuild -DCMAKE_INSTALL_PREFIX=${{ env.INSTALL_PATH }} -DGPU_ARCH=70 -DMODULES="CC" -DUSE_UPCXX=ON -DMPIRUN_EXECUTABLE=${{ env.CI_MPIEXEC }}
+        UPCXX_CODEMODE=O3 CXX=upcxx cmake -H. -Bbuild -DCMAKE_INSTALL_PREFIX=${{ env.INSTALL_PATH }} -DGPU_ARCH=70 -DMODULES="CC" -DTAMM_ENABLE_CUDA=${{ env.USE_CUDA }} -DUSE_UPCXX=ON -DMPIRUN_EXECUTABLE=${{ env.CI_MPIEXEC }}
         cd build
         UPCXX_NETWORK=smp UPCXX_CODEMODE=O3 make -j${{ env.EC_NPROC }}
         UPCXX_NETWORK=smp UPCXX_CODEMODE=O3 make install

README.md

@@ -18,7 +18,7 @@
 
 ## Build 
 
-Build instructions are available [here](docs/install.md)
+Build instructions are available [here](https://exachem.readthedocs.io/en/latest/install.html)
 
 ## ExaChem Citation
 #### Please cite the following reference when publishing results obtained with ExaChem. 

docs/index.rst

@@ -6,6 +6,7 @@ ExaChem Documentation
    :caption: Contents:
 
    introduction
+   install
    user_guide/user
    developer_guide/developer
 

docs/install.rst

@@ -0,0 +1,62 @@
+
+The installation instructions for this repository are the same as those
+for the `TAMM Library <https://github.com/NWChemEx/TAMM>`__.
+
+Installation
+============
+
+-  `Software
+   Requirements <https://tamm.readthedocs.io/en/latest/prerequisites.html>`__
+
+-  `Build
+   Instructions <https://tamm.readthedocs.io/en/latest/install.html>`__
+
+Dependencies
+------------
+
+In addition to the TAMM `dependencies <https://tamm.readthedocs.io/en/latest/install.html>`__, the following ExaChem dependencies are also automatically built by TAMM.
+
+* Libint
+* Libecpint
+
+Build instructions for a quick start
+------------------------------------
+
+Step 1
+
+::
+
+   git clone https://github.com/NWChemEx/TAMM.git
+   cd TAMM && mkdir build && cd build
+
+-  .. rubric:: A detailed list of the cmake build options available are
+      listed
+      `here <https://tamm.readthedocs.io/en/latest/install.html>`__
+      :name: a-detailed-list-of-the-cmake-build-options-available-are-listed-here
+
+::
+
+   CC=gcc CXX=g++ FC=gfortran cmake -DCMAKE_INSTALL_PREFIX=<exachem-install-path> -DMODULES="CC;DFT" ..
+   make -j4 install
+
+Step 2
+
+::
+
+   git clone https://github.com/ExaChem/exachem.git
+   cd exachem && mkdir build && cd build
+   CC=gcc CXX=g++ FC=gfortran cmake -DCMAKE_INSTALL_PREFIX=<exachem-install-path> -DMODULES="CC;DFT" ..
+   make -j4
+
+``NOTE:`` The cmake configure line in Steps 1 and 2 should be the same.
+
+
+Running the code
+----------------
+
+::
+
+   export OMP_NUM_THREADS=1
+   export INPUT_FILE=$REPO_ROOT_PATH/inputs/ozone.json
+
+   mpirun -n 3 $REPO_INSTALL_PATH/bin/ExaChem $INPUT_FILE

docs/user_guide/cholesky_decomposition.rst

@@ -33,6 +33,4 @@ Options used in the Cholesky decomposition of atomic-orbital based two-electron
 
 The following options are applicable only for calculations involving :math:`\geq` 1000 basis functions. They are used for restarting the cholesky decomposition procedure.
 
-:write_cv: ``[default=[false,5000]]`` When enabled, it performs parallel IO to write the tensor containing the AO cholesky vectors to disk. Enabling this option implies restart.
-The integer represents a count, indicating that the Cholesky vectors should be written to disk after every *count* vectors are computed.
-
+:write_cv: ``[default=[false,5000]]`` When enabled, it performs parallel IO to write the tensor containing the AO cholesky vectors to disk. Enabling this option implies restart. The integer represents a count, indicating that the Cholesky vectors should be written to disk after every *count* vectors are computed.

exachem/cc/ccsd_t/ccsd_t.cmake

@@ -11,20 +11,20 @@ set(CCSD_T_COMMON_SRCS
     ${CCSD_T_SRCDIR}/fused_common.hpp
     )
 
-if(USE_CUDA)
+if(TAMM_HAS_CUDA)
     set(CCSD_T_SRCS ${CCSD_T_COMMON_SRCS}
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused.hpp
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused_gpu.cu
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused_nontcCuda_Hip_Sycl.cpp)
 
     set_source_files_properties(${CCSD_T_SRCDIR}/ccsd_t_all_fused_nontcCuda_Hip_Sycl.cpp PROPERTIES LANGUAGE CUDA)
-elseif(USE_HIP)
+elseif(TAMM_HAS_HIP)
     set(CCSD_T_SRCS ${CCSD_T_COMMON_SRCS}
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused.hpp
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused_nontcCuda_Hip_Sycl.cpp)
 
     set_source_files_properties(${CCSD_T_SRCDIR}/ccsd_t_all_fused_nontcCuda_Hip_Sycl.cpp PROPERTIES LANGUAGE HIP)
-elseif(USE_DPCPP)
+elseif(TAMM_HAS_DPCPP)
     set(CCSD_T_SRCS ${CCSD_T_COMMON_SRCS}
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused.hpp
             ${CCSD_T_SRCDIR}/ccsd_t_all_fused_nontcCuda_Hip_Sycl.cpp)

support/spack/packages/exachem/package.py

@@ -1,4 +1,4 @@
-# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
+# Copyright 2013-2024 Lawrence Livermore National Security, LLC and other
 # Spack Project Developers. See the top-level COPYRIGHT file for details.
 #
 # SPDX-License-Identifier: (Apache-2.0 OR MIT)
@@ -20,22 +20,23 @@ class Exachem(CMakePackage,CudaPackage):
     depends_on('mpi')
     depends_on('intel-oneapi-mkl +cluster')
     depends_on('[email protected]:')
-    depends_on('cuda@11.5:', when='+cuda')
+    depends_on('cuda@11.8:', when='+cuda')
     depends_on('hdf5 +mpi')
-    # Still need to update libint recipe for 2.7.x
-    #depends_on('[email protected]:')
+    # Still need to update libint recipe for 2.9.x
+    #depends_on('[email protected]:')
+    conflicts("+cuda", when="cuda_arch=none")
 
     def cmake_args(self):
         args = [
             # This was not able to detect presence of libint in first test
             #'-DLibInt2_ROOT=%s' % self.spec['libint'].prefix,
-            '-DMODULES=CC',
+            '-DMODULES=CC;DFT',
             '-DHDF5_ROOT=%s' % self.spec['hdf5'].prefix,
             '-DLINALG_VENDOR=IntelMKL',
             '-DLINALG_PREFIX=%s' % join_path(self.spec['intel-oneapi-mkl'].prefix, 'mkl', 'latest'),
         ]
         if '+cuda' in self.spec:
-            args.extend([ '-DUSE_CUDA=ON',
-             ])
+            args.append( "-DTAMM_ENABLE_CUDA=ON" )
+            args.append("-DGPU_ARCH=" + self.spec.variants["cuda_arch"].value)
 
         return args

support/spack/packages/tamm/package.py

@@ -1,4 +1,4 @@
-# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
+# Copyright 2013-2024 Lawrence Livermore National Security, LLC and other
 # Spack Project Developers. See the top-level COPYRIGHT file for details.
 #
 # SPDX-License-Identifier: (Apache-2.0 OR MIT)
@@ -23,22 +23,23 @@ class Tamm(CMakePackage,CudaPackage):
     depends_on('mpi')
     depends_on('intel-oneapi-mkl +cluster')
     depends_on('[email protected]:')
-    depends_on('cuda@11.5:', when='+cuda')
+    depends_on('cuda@11.8:', when='+cuda')
     depends_on('hdf5 +mpi')
-    # Still need to update libint recipe for 2.7.x
-    #depends_on('[email protected]:')
+    # Still need to update libint recipe for 2.9.x
+    #depends_on('[email protected]:')
+    conflicts("+cuda", when="cuda_arch=none")
 
     def cmake_args(self):
         args = [
             # This was not able to detect presence of libint in first test
             #'-DLibInt2_ROOT=%s' % self.spec['libint'].prefix,
-            '-DMODULES=CC',
+            '-DMODULES=CC;DFT',
             '-DHDF5_ROOT=%s' % self.spec['hdf5'].prefix,
             '-DLINALG_VENDOR=IntelMKL',
             '-DLINALG_PREFIX=%s' % join_path(self.spec['intel-oneapi-mkl'].prefix, 'mkl', 'latest'),
         ]
         if '+cuda' in self.spec:
-            args.extend([ '-DUSE_CUDA=ON',
-             ])
+            args.append( "-DTAMM_ENABLE_CUDA=ON" )
+            args.append("-DGPU_ARCH=" + self.spec.variants["cuda_arch"].value)
 
         return args