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Merge pull request #13585 from iyamazaki/tacho-blk
Tacho : new options (dofs-per-node, pivot-tol, amd)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -16,6 +16,7 @@ | |
| /// \author Kyungjoo Kim ([email protected]) | ||
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| #include "Tacho.hpp" | ||
| #include "Tacho_Util.hpp" | ||
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| #include <Kokkos_Core.hpp> | ||
| #include <Kokkos_Timer.hpp> | ||
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@@ -24,7 +25,7 @@ namespace Tacho { | |
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| /// forward decl | ||
| class Graph; | ||
| #if defined(TACHO_HAVE_METIS) | ||
| #if defined(TACHO_HAVE_METIS) || defined(TACHO_HAVE_TRILINOS_SS) | ||
| class GraphTools_Metis; | ||
| #else | ||
| class GraphTools; | ||
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@@ -42,6 +43,7 @@ template <typename ValueType, typename DeviceType, int Var> class NumericToolsLe | |
| template <typename ValueType, typename DeviceType> struct Driver { | ||
| public: | ||
| using value_type = ValueType; | ||
| using mag_type = typename ArithTraits<ValueType>::mag_type; | ||
| using device_type = DeviceType; | ||
| using exec_space = typename device_type::execution_space; | ||
| using exec_memory_space = typename device_type::memory_space; | ||
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@@ -63,7 +65,7 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| using crs_matrix_type = CrsMatrixBase<value_type, device_type>; | ||
| using crs_matrix_type_host = CrsMatrixBase<value_type, host_device_type>; | ||
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| #if defined(TACHO_HAVE_METIS) | ||
| #if defined(TACHO_HAVE_METIS) || defined(TACHO_HAVE_TRILINOS_SS) | ||
| using graph_tools_type = GraphTools_Metis; | ||
| #else | ||
| using graph_tools_type = GraphTools; | ||
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@@ -111,6 +113,7 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| ordinal_type_array_host _h_peri_graph; | ||
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| // ** symbolic factorization output | ||
| ordinal_type _nnz_u; | ||
| // supernodes output | ||
| ordinal_type _nsupernodes; | ||
| ordinal_type_array _supernodes; | ||
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@@ -160,6 +163,8 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| ordinal_type _variant; // algorithmic variant in levelset 0: naive, 1: invert diagonals | ||
| ordinal_type _nstreams; // on cuda, multi streams are used | ||
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| mag_type _pivot_tol; // tolerance for tiny pivot perturbation | ||
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| // parallelism and memory constraint is made via this parameter | ||
| ordinal_type _max_num_superblocks; // # of superblocks in the memoyrpool | ||
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@@ -206,9 +211,14 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| void setLevelSetOptionNumStreams(const ordinal_type nstreams); | ||
| void setLevelSetOptionAlgorithmVariant(const ordinal_type variant); | ||
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| void setPivotTolerance(const mag_type pivot_tol); | ||
| void useNoPivotTolerance(); | ||
| void useDefaultPivotTolerance(); | ||
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| /// | ||
| /// get interface | ||
| /// | ||
| ordinal_type getNumNonZerosU() const; | ||
| ordinal_type getNumSupernodes() const; | ||
| ordinal_type_array getSupernodes() const; | ||
| ordinal_type_array getPermutationVector() const; | ||
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@@ -222,6 +232,7 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| template <typename arg_size_type_array, typename arg_ordinal_type_array> | ||
| int analyze(const ordinal_type m, const arg_size_type_array &ap, const arg_ordinal_type_array &aj, | ||
| const bool duplicate = false) { | ||
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| _m = m; | ||
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| if (duplicate) { | ||
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@@ -270,6 +281,7 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| const arg_perm_type_array &perm, const arg_perm_type_array &peri, const bool duplicate = false) { | ||
| _m = m; | ||
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| // this takes the user-specified perm, such that analyze() won't call graph partitioner | ||
| if (duplicate) { | ||
| /// for most cases, ap and aj are from host; so construct ap and aj and mirror to device | ||
| _h_ap = size_type_array_host(Kokkos::ViewAllocateWithoutInitializing("h_ap"), ap.extent(0)); | ||
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@@ -375,6 +387,46 @@ template <typename ValueType, typename DeviceType> struct Driver { | |
| return analyze(); | ||
| } | ||
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| template <typename arg_size_type_array, typename arg_ordinal_type_array> | ||
| int analyze(const ordinal_type m, const ordinal_type blk_size, | ||
| const arg_size_type_array &ap, const arg_ordinal_type_array &aj, | ||
| const bool duplicate = false) { | ||
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| if (blk_size > 1) { | ||
| //condense graph before calling analyze | ||
| const size_type nnz = ap(m); | ||
| ordinal_type m_graph = m / blk_size; | ||
| size_type nnz_graph = nnz / (blk_size*blk_size); | ||
| TACHO_TEST_FOR_EXCEPTION((m != blk_size * m_graph || nnz != size_type(blk_size*blk_size) * nnz_graph), | ||
| std::logic_error, "Failed to initialize the condensed graph"); | ||
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| size_type_array_host ap_graph | ||
| (Kokkos::ViewAllocateWithoutInitializing("ap_graph"), 1+m_graph); | ||
| ordinal_type_array_host aj_graph | ||
| (Kokkos::ViewAllocateWithoutInitializing("aj_graph"), nnz_graph); | ||
| ordinal_type_array_host aw_graph | ||
| (Kokkos::ViewAllocateWithoutInitializing("wgs"), m_graph); | ||
| // condense the graph | ||
| nnz_graph = 0; | ||
| ap_graph(0) = 0; | ||
| for (ordinal_type i = 0; i < m; i += blk_size) { | ||
| for (size_type k = ap(i); k < ap(i+1); k++) { | ||
| if (aj(k)%blk_size == 0) { | ||
| aj_graph(nnz_graph) = aj(k)/blk_size; | ||
| nnz_graph++; | ||
| } | ||
| aw_graph(i/blk_size) = blk_size; | ||
| ap_graph((i/blk_size)+1) = nnz_graph; | ||
| } | ||
| } | ||
| TACHO_TEST_FOR_EXCEPTION((nnz != size_type(blk_size*blk_size) * nnz_graph), | ||
| std::logic_error, "Failed to condense graph"); | ||
| return analyze(m, ap, aj, m_graph, ap_graph, aj_graph, aw_graph, duplicate); | ||
| } else { | ||
| return analyze(m, ap, aj, duplicate); | ||
| } | ||
| } | ||
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| int initialize(); | ||
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| int factorize(const value_type_array &ax); | ||
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