diff --git a/examples/CLEO_hello_world.ipynb b/examples/CLEO_hello_world.ipynb new file mode 100644 index 00000000..a9f87463 --- /dev/null +++ b/examples/CLEO_hello_world.ipynb @@ -0,0 +1,1522 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [], + "gpuType": "T4" + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "accelerator": "GPU" + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "**to run on Google Colab, chenge to GPU runtime (menu: Runtime -> Change runtime type)**" + ], + "metadata": { + "id": "_VczECqVn7GC" + } + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "id": "4-c1H8a9dVLV" + }, + "outputs": [], + "source": [ + "!wget --quiet https://github.com/yoctoyotta1024/CLEO/archive/refs/tags/v0.33.0.zip" + ] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "om0zX7YvQXl2" + }, + "execution_count": 24, + "outputs": [] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "3SsnpxgLQXjB" + }, + "execution_count": 24, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "%%file script.sh\n", + "cd CLEO-0.33.0\n", + "\n", + "mkdir -p bin\n", + "echo \"#!/bin/bash\" > bin/module\n", + "echo \"#!/bin/bash\" > bin/spack\n", + "chmod 755 bin/*\n", + "export PATH=./bin:$PATH\n", + "export CPLUS_INCLUDE_PATH=/usr/lib/x86_64-linux-gnu/openmpi/include/\n", + "\n", + "echo -e \"levante_gxx_compiler=g++\\nlevante_gcc_compiler=gcc\" > scripts/bash/src/levante_packages.sh\n", + "\n", + ". scripts/build_compile_cleo.sh cuda gcc \\\n", + " . \\\n", + " output/box_model \\\n", + " \"golcolls longcolls\" \\\n", + " false \\\n", + " false \\\n", + " \"\" \\\n", + " false" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "EG5TNb6edsF1", + "outputId": "f4b8d99b-e52a-4580-a9b2-bd1e3346b307" + }, + "execution_count": 44, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Overwriting script.sh\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "!unzip v0.33.0.zip" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5-MhvxU_dYoh", + "outputId": "181d5219-77ca-4abf-c60b-b3eac5c54d4a" + }, + "execution_count": 45, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Archive: v0.33.0.zip\n", + "641349a806ea5dca070192ba997b08387863eb88\n", + "replace CLEO-0.33.0/.github/compare_parallel_results.sh? 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CLEO-0.33.0/setup.py \n", + " inflating: CLEO-0.33.0/tests/test_math.py \n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "!. script.sh" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "S2VQ5X9feUgy", + "outputId": "3fb5b4dc-7b01-4b0d-e1e0-943fd0c255cc" + }, + "execution_count": 46, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "### --------------- User Inputs -------------- ###\n", + "CLEO_BUILDTYPE = cuda\n", + "CLEO_COMPILERNAME = gcc\n", + "CLEO_PATH2CLEO = .\n", + "CLEO_PATH2BUILD = output/box_model\n", + "CLEO_ENABLEDEBUG = false\n", + "CLEO_ENABLEYAC = false\n", + "CLEO_YACYAXTROOT = \n", + "executables = golcolls longcolls\n", + "### ------------------------------------------- ###\n", + "./scripts/bash/build_cleo.sh\n", + "### --------------- Build Inputs -------------- ###\n", + "CLEO_BUILDTYPE: cuda\n", + "CLEO_COMPILERNAME: gcc\n", + "CLEO_PATH2CLEO: .\n", + "CLEO_PATH2BUILD: output/box_model\n", + "CLEO_CXX_COMPILER: g++\n", + "CLEO_CC_COMPILER: gcc\n", + "CLEO_CXX_FLAGS: -Werror -Wall -Wextra -pedantic -Wno-unused-parameter -O3 -mfma\n", + "CLEO_KOKKOS_BASIC_FLAGS: -DKokkos_ARCH_NATIVE=ON -DKokkos_ENABLE_SERIAL=ON\n", + "CLEO_KOKKOS_HOST_FLAGS: -DKokkos_ENABLE_OPENMP=ON\n", + "CLEO_KOKKOS_DEVICE_FLAGS: -DKokkos_ENABLE_CUDA=ON -DKokkos_ENABLE_CUDA_CONSTEXPR=ON -DKokkos_ENABLE_CUDA_RELOCATABLE_DEVICE_CODE=ON -DCUDA_ROOT= -DNVCC_WRAPPER_DEFAULT_COMPILER=g++\n", + "CLEO_ENABLEYAC: false\n", + "CLEO_YACYAXTROOT: \n", + "CLEO_YAC_FLAGS: -DENABLE_YAC_COUPLING=OFF\n", + "CLEO_MODULE_PATH: \n", + "### ------------------------------------------- ###\n", + "-- The CXX compiler identification is GNU 11.4.0\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /usr/bin/g++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "-- Found MPI_CXX: /usr/lib/x86_64-linux-gnu/openmpi/lib/libmpi_cxx.so (found version \"3.1\")\n", + "-- Found MPI: TRUE (found version \"3.1\")\n", + "\u001b[0mCLEO_SOURCE_DIR: /content/CLEO-0.33.0\u001b[0m\n", + "\u001b[0mCLEO_BINARY_DIR: /content/CLEO-0.33.0/output/box_model\u001b[0m\n", + "-- Using Kokkos installation from: /content/CLEO-0.33.0/extern/kokkos\n", + "-- Setting default Kokkos CXX standard to 20\n", + "-- Kokkos version: 4.5.0\n", + "-- The project name is: Kokkos\n", + "-- Using internal gtest for testing\n", + "-- Compiler Version: 12.5.82\n", + "-- kokkos_launch_compiler (/content/CLEO-0.33.0/output/box_model/_deps/kokkos-src/bin/kokkos_launch_compiler) is enabled...\n", + "-- Using -std=c++20 for C++20 standard as feature\n", + "-- SIMD: AVX512 detected\n", + "-- CUDA auto-detection of architecture failed with /usr/bin/g++. Enabling CUDA language ONLY to auto-detect architecture...\n", + "-- Looking for a CUDA compiler\n", + "-- Looking for a CUDA compiler - /usr/local/cuda/bin/nvcc\n", + "-- The CUDA compiler identification is NVIDIA 12.5.82 with host compiler GNU 11.4.0\n", + "-- Detecting CUDA compiler ABI info\n", + "-- Detecting CUDA compiler ABI info - done\n", + "-- Check for working CUDA compiler: /usr/local/cuda/bin/nvcc - skipped\n", + "-- Detecting CUDA compile features\n", + "-- Detecting CUDA compile features - done\n", + "-- Detected CUDA Compute Capability 75\n", + "-- Setting Kokkos_ARCH_TURING75=ON\n", + "-- Built-in Execution Spaces:\n", + "-- Device Parallel: Kokkos::Cuda\n", + "-- Host Parallel: Kokkos::OpenMP\n", + "-- Host Serial: SERIAL\n", + "-- \n", + "-- Architectures:\n", + "-- NATIVE\n", + "-- TURING75\n", + "-- Found CUDAToolkit: /usr/local/cuda/targets/x86_64-linux/include (found version \"12.5.82\")\n", + "-- Performing Test CMAKE_HAVE_LIBC_PTHREAD\n", + "-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success\n", + "-- Found Threads: TRUE\n", + "-- Found TPLLIBDL: /usr/include\n", + "-- Found OpenMP_CXX: -fopenmp (found suitable version \"4.5\", minimum required is \"3.0\")\n", + "-- Found OpenMP: TRUE (found suitable version \"4.5\", minimum required is \"3.0\") found components: CXX\n", + "-- Using internal desul_atomics copy\n", + "-- Experimental mdspan support is enabled\n", + "-- Looking for C++ include experimental/mdspan\n", + "-- Looking for C++ include experimental/mdspan - not found\n", + "-- Looking for C++ include mdspan\n", + "-- Looking for C++ include mdspan - not found\n", + "-- Using internal mdspan directory /content/CLEO-0.33.0/output/box_model/_deps/kokkos-src/tpls/mdspan/include\n", + "-- Kokkos Backends: OPENMP;SERIAL;CUDA\n", + "-- Kokkos installation in: /content/CLEO-0.33.0/output/box_model/kokkos\n", + "-- Using Kokkos nvcc wrapper (see: https://kokkos.org/kokkos-core-wiki/ProgrammingGuide/Compiling.html?highlight=wrapper#building-for-cuda)\n", + "-- CXX compiler: /usr/bin/g++\n", + "-- CC compiler: gcc\n", + "-- wrapper default (C++) compiler: g++\n", + "-- wrapper CUDA compiler: /bin/nvcc\n", + "-- Using yaml-cpp installation from: /content/CLEO-0.33.0/extern/yaml-cpp\n", + "\u001b[0mCMake Deprecation Warning at output/box_model/_deps/yaml-cpp-src/CMakeLists.txt:2 (cmake_minimum_required):\n", + " Compatibility with CMake < 3.10 will be removed from a future version of\n", + " CMake.\n", + "\n", + " Update the VERSION argument value. Or, use the ... syntax\n", + " to tell CMake that the project requires at least but has been updated\n", + " to work with policies introduced by or earlier.\n", + "\n", + "\u001b[0m\n", + "-- yaml-cpp installation in: /content/CLEO-0.33.0/output/box_model/yaml-cpp\n", + "-- CMAKE_CXX_FLAGS: -Werror -Wall -Wextra -pedantic -Wno-unused-parameter -O3 -mfma -fPIC\n", + "\u001b[0mgridboxes LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/gridboxes\u001b[0m\n", + "\u001b[0minitialise LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/initialise\u001b[0m\n", + "\u001b[0mruncleo LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/runcleo\u001b[0m\n", + "\u001b[0msuperdrops LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/superdrops\u001b[0m\n", + "\u001b[0mcollisions LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/superdrops/collisions\u001b[0m\n", + "\u001b[0mzarr LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/zarr\u001b[0m\n", + "\u001b[0mobservers LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/observers\u001b[0m\n", + "\u001b[0msdmmonitor LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/observers/sdmmonitor\u001b[0m\n", + "\u001b[0mcoupldyn_cvode LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/coupldyn_cvode\u001b[0m\n", + "-- The C compiler identification is GNU 11.4.0\n", + "-- Detecting C compiler ABI info\n", + "-- Detecting C compiler ABI info - done\n", + "-- Check for working C compiler: /usr/bin/gcc - skipped\n", + "-- Detecting C compile features\n", + "-- Detecting C compile features - done\n", + "-- SUNDIALS_GIT_VERSION: \n", + "-- Looking for sys/types.h\n", + "-- Looking for sys/types.h - found\n", + "-- Looking for stdint.h\n", + "-- Looking for stdint.h - found\n", + "-- Looking for stddef.h\n", + "-- Looking for stddef.h - found\n", + "-- Check size of int64_t\n", + "-- Check size of int64_t - done\n", + "-- Using int64_t for indices\n", + "-- C standard set to 99\n", + "-- C extensions set to ON\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_SNPRINTF_AND_VA_COPY\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_SNPRINTF_AND_VA_COPY - Success\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_MATH_PRECISIONS\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_MATH_PRECISIONS - Success\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_ISINF_ISNAN\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_ISINF_ISNAN - Success\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_INLINE\n", + "-- Performing Test SUNDIALS_C_COMPILER_HAS_INLINE - Success\n", + "-- Looking for POSIX timers... found\n", + "-- Performing Test COMPILER_HAS_DEPRECATED_MSG\n", + "-- Performing Test COMPILER_HAS_DEPRECATED_MSG - Success\n", + "-- Performing Test COMPILER_HAS_HIDDEN_VISIBILITY\n", + "-- Performing Test COMPILER_HAS_HIDDEN_VISIBILITY - Success\n", + "-- Performing Test COMPILER_HAS_HIDDEN_INLINE_VISIBILITY\n", + "-- Performing Test COMPILER_HAS_HIDDEN_INLINE_VISIBILITY - Success\n", + "-- Performing Test COMPILER_HAS_DEPRECATED_ATTR\n", + "-- Performing Test COMPILER_HAS_DEPRECATED_ATTR - Failed\n", + "-- Performing Test COMPILER_HAS_DEPRECATED\n", + "-- Performing Test COMPILER_HAS_DEPRECATED - Failed\n", + "-- Added NVECTOR_SERIAL module\n", + "-- Added NVECTOR_MANYVECTOR module\n", + "-- Added SUNMATRIX_BAND module\n", + "-- Added SUNMATRIX_DENSE module\n", + "-- Added SUNMATRIX_SPARSE module\n", + "-- Added SUNLINSOL_BAND module\n", + "-- Added SUNLINSOL_DENSE module\n", + "-- Added SUNLINSOL_PCG module\n", + "-- Added SUNLINSOL_SPBCGS module\n", + "-- Added SUNLINSOL_SPFGMR module\n", + "-- Added SUNLINSOL_SPGMR module\n", + "-- Added SUNLINSOL_SPTFQMR module\n", + "-- Added SUNNONLINSOL_NEWTON module\n", + "-- Added SUNNONLINSOL_FIXEDPOINT module\n", + "-- Added CVODES module\n", + "\u001b[0mcoupldyn_fromfile LIBRARY_SOURCE_DIR: /content/CLEO-0.33.0/libs/coupldyn_fromfile\u001b[0m\n", + "\u001b[0mcartesiandomain LIBRARY_SOURCE_DIR: 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__device__ function is not allowed\n", + " c1nghbrs = correct_neighbor_indices(c1nghbrs, ndims, domain_decomposition);\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(221)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " c1nghbrs = correct_neighbor_indices(c1nghbrs, ndims, domain_decomposition);\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(228)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " c2nghbrs = correct_neighbor_indices(c2nghbrs, ndims, domain_decomposition);\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(228)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " c2nghbrs = correct_neighbor_indices(c2nghbrs, ndims, domain_decomposition);\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(203)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " Kokkos::parallel_for(\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(201)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " Kokkos::parallel_for(\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(308)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " Kokkos::parallel_for(\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(306)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20014-D: calling a __host__ function from a __host__ __device__ function is not allowed\n", + " Kokkos::parallel_for(\n", + " ^\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::~GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::~GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(158)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mGbxBoundsFromBinary::~GbxBoundsFromBinary\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(202)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(236)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(236)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::~[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(236)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::~[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(307)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(322)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(322)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::~[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(322)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::~[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(204)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(235)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(235)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(309)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(321)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(321)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(205)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mget_index_from_coordinates(const ::std::vector > &, unsigned long, unsigned long, unsigned long)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(209)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::global_to_local_gridbox_index(unsigned long) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(211)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mGbxBoundsFromBinary::get_coord3gbxbounds(unsigned int) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(213)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mDoublyPeriodicDomain::cartesian_coord3nghbrs(unsigned int, const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(214)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(214)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mcorrect_neighbor_indices( ::Kokkos::pair , ::std::vector > , const ::CartesianDecomposition &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(214)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(218)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mGbxBoundsFromBinary::get_coord1gbxbounds(unsigned int) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(220)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mDoublyPeriodicDomain::cartesian_coord1nghbrs(unsigned int, const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(221)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(221)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mcorrect_neighbor_indices( ::Kokkos::pair , ::std::vector > , const ::CartesianDecomposition &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(221)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(225)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mGbxBoundsFromBinary::get_coord2gbxbounds(unsigned int) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(227)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mDoublyPeriodicDomain::cartesian_coord2nghbrs(unsigned int, const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(228)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(228)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mcorrect_neighbor_indices( ::Kokkos::pair , ::std::vector > , const ::CartesianDecomposition &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(228)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(232)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mGbxBoundsFromBinary::gbxarea(unsigned int) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(233)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mGbxBoundsFromBinary::gbxvol(unsigned int) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(234)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(234)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(310)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mget_index_from_coordinates(const ::std::vector > &, unsigned long, unsigned long, unsigned long)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(314)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::global_to_local_gridbox_index(unsigned long) const\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(316)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mnullbounds()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(317)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mnullnghbrs(unsigned int)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::operator () const\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(320)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/createcartesianmaps.cpp(320)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::~vector()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mset_null_cartesian_maps(unsigned int, const ::GbxBoundsFromBinary &, ::CartesianMaps &)::[lambda(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) (instance 1)]::operator ()(const ::Kokkos::Impl::HostThreadTeamMember< ::Kokkos::OpenMP> &) const::[lambda(unsigned long) (instance 1)]::operator ()(unsigned long) const::[lambda(unsigned long) (instance 1)]::~[lambda(unsigned long) (instance 1)]\u001b[0m\") is not allowed\n", + "\n", + "[ 94%] \u001b[32m\u001b[1mLinking CXX static library libobservers.a\u001b[0m\n", + "[ 94%] Built target observers\n", + "[ 94%] \u001b[32mBuilding CXX object libs/runcleo/CMakeFiles/runcleo.dir/creategbxs.cpp.o\u001b[0m\n", + "[ 97%] \u001b[32mBuilding CXX object libs/runcleo/CMakeFiles/runcleo.dir/createsupers.cpp.o\u001b[0m\n", + "[ 97%] \u001b[32mBuilding CXX object libs/runcleo/CMakeFiles/runcleo.dir/gensuperdrop.cpp.o\u001b[0m\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/./../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01;36m\u001b[0m\u001b[01;36mRemark\u001b[0m: The warnings can be suppressed with \"-diag-suppress \"\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/./../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/./../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/cartesiandomain/cartesianmaps.hpp(193)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianMaps::~CartesianMaps\u001b[0m\") is not allowed\n", + "\n", + "[ 97%] \u001b[32m\u001b[1mLinking CXX static library libcartesiandomain.a\u001b[0m\n", + "[ 97%] Built target cartesiandomain\n", + "[ 97%] \u001b[32m\u001b[1mLinking CXX static library libruncleo.a\u001b[0m\n", + "[ 97%] Built target runcleo\n", + "[100%] \u001b[32mBuilding CXX object examples/boxmodelcollisions/golovin/src/CMakeFiles/golcolls.dir/main_golcolls.cpp.o\u001b[0m\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01;36m\u001b[0m\u001b[01;36mRemark\u001b[0m: The warnings can be suppressed with \"-diag-suppress \"\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianMaps::~CartesianMaps\u001b[0m\") is not allowed\n", + "\n", + "[100%] \u001b[32m\u001b[1mLinking CXX executable golcolls\u001b[0m\n", + "[100%] Built target golcolls\n", + "[ 2%] Built target kokkossimd\n", + "[ 31%] Built target yaml-cpp\n", + "[ 54%] Built target kokkoscore\n", + "[ 54%] Built target kokkoscontainers\n", + "[ 60%] Built target zarr\n", + "[ 62%] Built target sdmmonitor\n", + "[ 68%] Built target collisions\n", + "[ 77%] Built target initialise\n", + "[ 82%] Built target superdrops\n", + "[ 88%] Built target gridboxes\n", + "[ 91%] Built target observers\n", + "[ 94%] Built target cartesiandomain\n", + "[ 97%] Built target runcleo\n", + "[ 97%] \u001b[32mBuilding CXX object examples/boxmodelcollisions/long/src/CMakeFiles/longcolls.dir/main_longcolls.cpp.o\u001b[0m\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector > ::vector(const ::std::vector > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01;36m\u001b[0m\u001b[01;36mRemark\u001b[0m: The warnings can be suppressed with \"-diag-suppress \"\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mstd::vector< ::std::array , ::std::allocator< ::std::array > > ::vector(const ::std::vector< ::std::array , ::std::allocator< ::std::array > > &)\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianDecomposition::CartesianDecomposition\u001b[0m\") is not allowed\n", + "\n", + "\u001b[01m\u001b[0m\u001b[01m/content/CLEO-0.33.0/libs/zarr/../gridboxes/gridbox.hpp(58)\u001b[0m: \u001b[01;35mwarning\u001b[0m #20011-D: calling a __host__ function(\"\u001b[01mCartesianDecomposition::~CartesianDecomposition()\u001b[0m\") from a __host__ __device__ function(\"\u001b[01mCartesianMaps::~CartesianMaps\u001b[0m\") is not allowed\n", + "\n", + "[100%] \u001b[32m\u001b[1mLinking CXX executable longcolls\u001b[0m\n", + "[100%] Built target longcolls\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "!pip install --quiet awkward ruamel.yaml zarr" + ], + "metadata": { + "id": "FEr2-XU_3oiv" + }, + "execution_count": 47, + "outputs": [] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "qSHFdYMEW7V2" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "!cd CLEO-0.33.0; \\\n", + " python3 \\\n", + " examples/boxmodelcollisions/shima2009.py \\\n", + " /content/CLEO-0.33.0 \\\n", + " /content/CLEO-0.33.0/output/box_model/ \\\n", + " /content/CLEO-0.33.0/examples/boxmodelcollisions/shima2009_config.yaml \\\n", + " golovin" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "Ux4-6J0rnaoM", + "outputId": "68794f40-28f5-48d1-f51b-ac9f8e00f5e8" + }, + "execution_count": 49, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "created boundaries for 1 gridboxes\n", + "Writing gridbox boundaries binary file to:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Metadata: \n", + " '4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are ndims in (z,x,y), then the 1 gridbox indicies followed by the [zmin, zmax, xmin, xmax, ymin, ymax] coordinates for each gridbox's boundaries. Grid has dimensions 1x1x1'\n", + "zhalf: [ 0. 100.]\n", + "xhalf: [ 0. 100.]\n", + "yhalf: [ 0. 100.]\n", + "\n", + "------ DOMAIN / GRIDBOXES INFO ------\n", + "------------- 0-D MODEL -------------\n", + "domain dimensions: (100x100x100)m^3\n", + "domain no. gridboxes: 1x1x1\n", + "domain z limits: ( 0,100)m\n", + "domain x limits: ( 0, 100)m\n", + "domain y limits: ( 0, 100)m\n", + "mean gridbox z spacing: 100 m\n", + "mean gridbox x spacing: 100 m\n", + "mean gridbox y spacing: 100 m\n", + "mean gridbox volume: 1e+06 m^3\n", + "total domain volume: 1e+06 m^3\n", + "total no. gridboxes: 1\n", + "------------------------------------\n", + "\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Metadata: \n", + " '4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are ndims in (z,x,y), then the 1 gridbox indicies followed by the [zmin, zmax, xmin, xmax, ymin, ymax] coordinates for each gridbox's boundaries. Grid has dimensions 1x1x1'\n", + "zhalf: [ 0. 100.]\n", + "xhalf: [ 0. 100.]\n", + "yhalf: [ 0. 100.]\n", + "Figure .png saved as: /content/CLEO-0.33.0/output/box_model/bin/gridboxboundaries.png\n", + "Figure(1000x500)\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "4096\n", + "--- total droplet concentration = 8.38861cm^-3 => 1g/m^3, in 1e+06m^3 volume --- \n", + "Writing gridbox boundaries binary file to:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "attribute shapes: (4096,) (4096,) (4096,) (4096,) (0,) (0,) (0,)\n", + "\n", + "------ DOMAIN SUPERDROPLETS INFO ------\n", + "total droplet number conc: 8.38861 /cm^3\n", + "total droplet mass: 7.0856e-35 g/m^3\n", + " as if water: 0.996791 g/m^3\n", + "------------------------------------\n", + "\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "attribute shapes: (4096,) (4096,) (4096,) (4096,) (0,) (0,) (0,)\n", + "Figure .png saved as: /content/CLEO-0.33.0/output/box_model/bin/initallGBxs_distribs_1.png\n", + "Figure(1400x400)\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "attribute shapes: (4096,) (4096,) (4096,) (4096,) (0,) (0,) (0,)\n", + "Figure .png saved as: /content/CLEO-0.33.0/output/box_model/bin/initallGBxs_dropletmasses_1.png\n", + "Figure(1400x400)\n", + "/content/CLEO-0.33.0/output/box_model\n", + "Executable: /content/CLEO-0.33.0/output/box_model/examples/boxmodelcollisions/golovin/src/golcolls\n", + "Config file: /content/CLEO-0.33.0/examples/boxmodelcollisions/shima2009_config.yaml\n", + "\n", + "-------- Required Configuration Parameters --------------\n", + "constants_filename : \"../../libs/cleoconstants.hpp\"\n", + "grid_filename : \"./share/shima2009_dimlessGBxboundaries.dat\"\n", + "setup_filename : \"./bin/shima2009_setup.txt\"\n", + "zarrbasedir : \"./bin/shima2009_sol.zarr\"\n", + "maxchunk : 2500000\n", + "nspacedims : 0\n", + "ngbxs : 1\n", + "maxnsupers : 4096\n", + "CONDTSTEP : 200\n", + "COLLTSTEP : 1\n", + "MOTIONTSTEP : 200\n", + "COUPLTSTEP : 2000\n", + "OBSTSTEP : 200\n", + "T_END : 3800\n", + "---------------------------------------------------------\n", + "\n", + "-------- Kokkos Configuration Parameters --------------\n", + "using default kokkos settings (bool): 0\n", + "num_threads: 128\n", + "---------------------------------------------------------\n", + "\n", + "-------- InitSupersFromBinary Configuration Parameters --------------\n", + "maxnsupers: 4096\n", + "nspacedims: 0\n", + "initsupers_filename: \"/content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\"\n", + "initnsupers: 4096\n", + "---------------------------------------------------------\n", + "\n", + "--- configuration ---\n", + "----- writing to new setup file: ./bin/shima2009_setup.txt -----\n", + " copying /content/CLEO-0.33.0/examples/boxmodelcollisions/shima2009_config.yaml to setup file\n", + " copying ../../libs/cleoconstants.hpp to setup file\n", + "---- copy complete, setup file closed -----\n", + "--- configuration: success ---\n", + "Kokkos::OpenMP::initialize WARNING: OMP_PROC_BIND environment variable not set\n", + " In general, for best performance with OpenMP 4.0 or better set OMP_PROC_BIND=spread and OMP_PLACES=threads\n", + " For best performance with OpenMP 3.1 set OMP_PROC_BIND=true\n", + " For unit testing set OMP_PROC_BIND=false\n", + "\n", + "Kokkos::OpenMP::initialize WARNING: You are likely oversubscribing your CPU cores.\n", + " process threads available : 2, requested thread : 128\n", + "Kokkos::OpenMP::initialize WARNING: You are likely oversubscribing your CPU cores.\n", + " Detected: 2 cores per node.\n", + " Detected: 1 MPI_ranks per node.\n", + " Requested: 128 threads per process.\n", + " Kokkos Version: 4.5.0\n", + "Compiler:\n", + " KOKKOS_COMPILER_GNU: 1140\n", + " KOKKOS_COMPILER_NVCC: 1250\n", + "Architecture:\n", + " CPU architecture: none\n", + " Default Device: Cuda\n", + " GPU architecture: TURING75\n", + " platform: 64bit\n", + "Atomics:\n", + "Vectorization:\n", + " KOKKOS_ENABLE_PRAGMA_IVDEP: no\n", + " KOKKOS_ENABLE_PRAGMA_LOOPCOUNT: no\n", + " KOKKOS_ENABLE_PRAGMA_UNROLL: no\n", + " KOKKOS_ENABLE_PRAGMA_VECTOR: no\n", + "Memory:\n", + "Options:\n", + " KOKKOS_ENABLE_ASM: yes\n", + " KOKKOS_ENABLE_CXX17: no\n", + " KOKKOS_ENABLE_CXX20: yes\n", + " KOKKOS_ENABLE_CXX23: no\n", + " KOKKOS_ENABLE_CXX26: no\n", + " KOKKOS_ENABLE_DEBUG_BOUNDS_CHECK: no\n", + " KOKKOS_ENABLE_HWLOC: no\n", + " KOKKOS_ENABLE_LIBDL: yes\n", + "Host Parallel Execution Space:\n", + " KOKKOS_ENABLE_OPENMP: yes\n", + "\n", + "OpenMP Runtime Configuration:\n", + "Kokkos::OpenMP thread_pool_topology[ 1 x 128 x 1 ]\n", + "Host Serial Execution Space:\n", + " KOKKOS_ENABLE_SERIAL: yes\n", + "\n", + "Serial Runtime Configuration:\n", + "Device Execution Space:\n", + " KOKKOS_ENABLE_CUDA: yes\n", + "Cuda Options:\n", + " KOKKOS_ENABLE_CUDA_RELOCATABLE_DEVICE_CODE: yes\n", + " KOKKOS_ENABLE_CUDA_UVM: no\n", + " KOKKOS_ENABLE_IMPL_CUDA_MALLOC_ASYNC: no\n", + "\n", + "Cuda Runtime Configuration:\n", + "macro KOKKOS_ENABLE_CUDA : defined\n", + "macro CUDA_VERSION = 12050 = version 12.5\n", + "Kokkos::Cuda[ 0 ] Tesla T4 capability 7.5, Total Global Memory: 14.74 GiB, Shared Memory per Block: 48 KiB : Selected\n", + "couldn't open \"./bin/shima2009_sol.zarr/.zgroup\",\n", + " making directory \"./bin/shima2009_sol.zarr\"\n", + "\n", + "--- create cartesian gridbox maps ---\n", + "opening binary file: ./share/shima2009_dimlessGBxboundaries.dat\n", + "----------------- gridfile global metastring -----------------\n", + "4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are ndims in (z,x,y), then the 1 gridbox indicies followed by the [zmin, zmax, xmin, xmax, ymin, ymax] coordinates for each gridbox's boundaries. Grid has dimensions 1x1x1\n", + "--------------------------------------------------------------\n", + "--- create cartesian gridbox maps: success ---\n", + "couldn't open \"./bin/shima2009_sol.zarr/time/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/time\"\n", + "couldn't open \"./bin/shima2009_sol.zarr/sdId/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/sdId\"\n", + "couldn't open \"./bin/shima2009_sol.zarr/xi/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/xi\"\n", + "couldn't open \"./bin/shima2009_sol.zarr/radius/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/radius\"\n", + "couldn't open \"./bin/shima2009_sol.zarr/msol/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/msol\"\n", + "couldn't open \"./bin/shima2009_sol.zarr/raggedcount/.zarray\",\n", + " making directory \"./bin/shima2009_sol.zarr/raggedcount\"\n", + "opening binary file: /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "----------------- gridfile global metastring -----------------\n", + "4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are Superdroplet attributes: [sdgbxindex, xi, radius, msol]\n", + "--------------------------------------------------------------\n", + "\n", + "--- create superdrops ---\n", + "initialising\n", + "opening binary file: /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "----------------- gridfile global metastring -----------------\n", + "4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are Superdroplet attributes: [sdgbxindex, xi, radius, msol]\n", + "--------------------------------------------------------------\n", + "opening binary file: /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessSDsinit_1.dat\n", + "----------------- gridfile global metastring -----------------\n", + "4 unsigned ints before this metadata string are [1. position of first byte of data (after all the metadata), 2. no. bytes of (this) global metadata string, 3. no. bytes per variable specific metadata, 4. no. of variables in data]. After this global metadata string comes variable specific metadata. For each variable, this is 3 unsigned ints, 2 chars and then a double; it states: [1. position of first databyte, 2. size (in bytes) of one datapoint, 3. no. of datapoints, 4. char to indicate python struct type, 5. char to indicate the units once multiplied by, 6. the scale factor]. Variables in this file are Superdroplet attributes: [sdgbxindex, xi, radius, msol]\n", + "--------------------------------------------------------------\n", + "sorting and finding superdrops in domain\n", + "checking initialisation\n", + "--- create superdrops: success ---\n", + "\n", + "--- create gridboxes ---\n", + "initialising\n", + "checking initialisation\n", + "--- create gridboxes: success ---\n", + "\n", + "--- prepare timestepping ---\n", + "observer includes write in dataset observer\n", + "observer includes time observer\n", + "observer includes StreamOutObserver\n", + "--- prepare timestepping: success ---\n", + "\n", + "--- timestepping ---\n", + "t=0.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=200.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=400.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=600.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=800.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=1000.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=1200.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=1400.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=1600.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=1800.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=2000.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=2200.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=2400.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=2600.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=2800.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=3000.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=3200.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=3400.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=3600.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "t=3800.00s, totnsupers=4096, ngbxs=1, (Gbx0: [T, p, qv, qc] = [0.00K, 0.00Pa, 0.0000e+00, 0.0000e+00], nsupers = 4096)\n", + "--- timestepping: success ---\n", + "-----\n", + " Total Program Duration: 9.3076e+00s \n", + "-----\n", + "\n", + "---- config from /content/CLEO-0.33.0/output/box_model/bin/shima2009_setup.txt -----\n", + "num_threads = 128.0\n", + "nspacedims = 0\n", + "ngbxs = 1.0\n", + "maxnsupers = 4096.0\n", + "CONDTSTEP = 200.0\n", + "COLLTSTEP = 1.0\n", + "MOTIONTSTEP = 200.0\n", + "COUPLTSTEP = 2000.0\n", + "OBSTSTEP = 200.0\n", + "T_END = 3800.0\n", + "maxchunk = 2500000.0\n", + "numSDattrs = 3\n", + "ntime = 20\n", + "---------------------------------------------\n", + "\n", + "\n", + "---- consts from /content/CLEO-0.33.0/output/box_model/bin/shima2009_setup.txt -----\n", + "G = 9.80665\n", + "RGAS_UNIV = 8.314462618\n", + "MR_WATER = 0.01801528\n", + "MR_DRY = 0.028966216\n", + "LATENT_V = 2500930.0\n", + "CP_DRY = 1004.64\n", + "CP_V = 1865.01\n", + "C_L = 4192.664\n", + "RHO_DRY = 1.177\n", + "RHO_L = 998.203\n", + "RHO_SOL = 2016.5\n", + "MR_SOL = 0.05844277\n", + "IONIC = 2.0\n", + "SURFSIGMA = 0.0728\n", + "W0 = 1.0\n", + "TIME0 = 1000.0\n", + "R0 = 1e-06\n", + "P0 = 100000.0\n", + "TEMP0 = 273.15\n", + "COORD0 = 1000.0\n", + "RGAS_DRY = 287.0399992183998\n", + "RGAS_V = 461.52280830495\n", + "CP0 = 1004.64\n", + "Mr_ratio = 0.6219410916496653\n", + "RHO0 = 0.36440835810508476\n", + "MASS0 = 3.644083581050847e-19\n", + "---------------------------------------------\n", + "\n", + "Reading binary file:\n", + " /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat\n", + "\n", + "---- gbxs from /content/CLEO-0.33.0/output/box_model/share/shima2009_dimlessGBxboundaries.dat -----\n", + "ngrid = 1\n", + "ndims = [1 1 1]\n", + "domainvol = 1000000.0\n", + "domainarea = 10000.0\n", + "gbxvols = [[[1000000.]]]\n", + "zhalf = [ 0. 100.]\n", + "zfull = [50.]\n", + "xhalf = [ 0. 100.]\n", + "xfull = [50.]\n", + "yhalf = [ 0. 100.]\n", + "yfull = [50.]\n", + "xxh = [[ 0. 0.]\n", + " [100. 100.]]\n", + "zzh = [[ 0. 100.]\n", + " [ 0. 100.]]\n", + "xxf = [[50.]]\n", + "zzf = [[50.]]\n", + "---------------------------------------------\n", + "\n", + "time from dataset: /content/CLEO-0.33.0/output/box_model/bin/shima2009_sol.zarr\n", + "---- Superdrop Properties -----\n", + "RHO_L = 998.203 Kg/m^3\n", + "RHO_SOL = 2016.5 Kg/m^3\n", + "MR_SOL = 0.05844277 Kg/mol\n", + "IONIC = 2.0\n", + "-------------------------------\n", + "supers dataset: /content/CLEO-0.33.0/output/box_model/bin/shima2009_sol.zarr\n", + "/content/CLEO-0.33.0/examples/exampleplotting/plotssrc/shima2009fig.py:140: RuntimeWarning: invalid value encountered in multiply\n", + " bsl_exp = iv(1, 2 * x * np.sqrt(tau)) * np.exp(-(1 + tau) * x)\n", + "Figure .png saved as: /content/CLEO-0.33.0/output/box_model/bin/golovin_validation.png\n", + "Figure(800x700)\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from IPython.display import Image\n", + "display(Image('CLEO-0.33.0/output/box_model/bin/golovin_validation.png'))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 851 + }, + "id": "cDFkmIaKqQjo", + "outputId": "cc57a9bc-b404-40f9-e4ff-7e9bd0e004c5" + }, + "execution_count": 50, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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