monolish
0.15.3
MONOlithic LInear equation Solvers for Highly-parallel architecture
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10 #include <initializer_list>
13 #define MONOLISH_SOLVER_SUCCESS 0
14 #define MONOLISH_SOLVER_SIZE_ERROR -1
15 #define MONOLISH_SOLVER_MAXITER -2
16 #define MONOLISH_SOLVER_BREAKDOWN -3
17 #define MONOLISH_SOLVER_RESIDUAL_NAN -4
18 #define MONOLISH_SOLVER_NOT_IMPL -10
292 template <
typename T>
301 template <
typename T,
typename U>
317 template <
typename T>
333 template <
typename T>
348 template <
typename T>
363 template <
typename T>
378 template <
typename T>
386 template <
typename T,
typename... types>
388 const types &... args) {
403 template <
typename T,
typename U>
405 return x.size() == y.size();
419 template <
typename T>
434 template <
typename T>
449 template <
typename T>
464 template <
typename T>
472 template <
typename T,
typename U,
typename... types>
474 const types &... args) {
486 template <
typename T,
typename U>
488 return arg1.get_device_mem_stat() == arg2.get_device_mem_stat();
499 template <
typename T,
typename U,
typename... types>
501 const types &... args) {
521 template <
typename T>
523 const T diag_val,
const T val);
537 template <
typename T>
574 template <
typename T>
588 template <
typename T>
604 template <
typename T>
617 template <
typename T>
630 template <
typename T>
644 template <
typename T>
661 template <
typename T>
678 template <
typename T>
680 T a0, T a1, T a2, T b0,
689 template <
typename T>
auto send(T &x) { x.send(); }
695 template <
typename T,
typename... Types>
auto send(T &x, Types &... args) {
705 template <
typename T>
auto recv(T &x) { x.recv(); }
711 template <
typename T,
typename... Types>
auto recv(T &x, Types &... args) {
728 template <
typename T,
typename... Types>
void random_vector(vector< T > &vec, const T min, const T max)
create random vector
matrix::COO< T > random_structure_matrix(const int M, const int N, const int nnzrow, const T val)
create random structure matrix (column number is decided by random)
Linear Operator imitating Matrix.
bool build_with_mkl()
get build option (true: with intel mkl, false: without intel mkl)
void min(const matrix::CRS< double > &A, const matrix::CRS< double > &B, matrix::CRS< double > &C)
Create a new CRS matrix with smallest elements of two matrices (C[0:nnz] = min(A[0:nnz],...
void max(const matrix::CRS< double > &A, const matrix::CRS< double > &B, matrix::CRS< double > &C)
Create a new CRS matrix with greatest elements of two matrices (C[0:nnz] = max(A[0:nnz],...
bool build_with_avx512()
get build option (true: with avx512, false: without avx512)
bool build_with_avx2()
get build option (true: with avx2, false: without avx2)
double get_residual_l2(const matrix::Dense< double > &A, const vector< double > &x, const vector< double > &y)
get nrm |b-Ax|_2
matrix::COO< T > eye(const int M)
create band matrix
bool is_same_size(const T &x, const U &y)
compare size of vector or 1Dview (same as is_same_structure())
matrix::COO< T > frank_matrix(const int &M)
create Frank matrix
auto size() const
get vector size
matrix::COO< T > tridiagonal_toeplitz_matrix(const int &M, T a, T b)
create tridiagonal Toeplitz matrix
bool build_with_avx()
get build option (true: with avx, false: without avx)
matrix::COO< T > laplacian_matrix_2D_5p(const int M, const int N)
create two dimensional Laplacian matrix using the five point central difference scheme
bool build_with_cblas()
get build option (true: with cblas, false: without cblas (=with intel mkl))
auto recv(T &x)
recv. and free data from GPU
matrix::COO< T > band_matrix(const int M, const int N, const int W, const T diag_val, const T val)
create band matrix
auto send(T &x)
send data to GPU
void set_log_level(const size_t Level)
Specifying the log level.
matrix::COO< T > toeplitz_plus_hankel_matrix(const int &M, T a0, T a1, T a2)
create Toeplitz-plus-Hankel matrix
T laplacian_matrix_1D_eigenvalue(const int &M, int N)
Nth smallest eigenvalue of 1D Laplacian matrix.
auto device_free(T &x)
free data of GPU
bool solver_check(const int err)
check error
T toeplitz_plus_hankel_matrix_eigenvalue(const int &M, int N, T a0, T a1, T a2, T b0, T b1, T b2)
Nth smallest eigenvalue of GEVP Ax=lBx of Toeplitz-plus-Hankel matrixes A, B.
Coodinate (COO) format Matrix (need to sort)
bool build_with_mpi()
get build option (true: enable MPI, false: disable MPI)
bool build_with_lapack()
get build option (true: with lapack, false: without lapack (=with intel mkl))
bool build_with_gpu()
get build option (true: enable gpu, false: disable gpu)
bool is_same_device_mem_stat(const T &arg1, const U &arg2)
compare same device memory status
T tridiagonal_toeplitz_matrix_eigenvalue(const int &M, int N, T a, T b)
Nth smallest eigenvalue of MxM tridiagonal Toeplitz matrix.
matrix::COO< T > laplacian_matrix_1D(const int &M)
create 1D Laplacian matrix
int get_num_devices()
get the number of devices
bool is_same_structure(const T A, const U B)
compare matrix structure
T frank_matrix_eigenvalue(const int &M, const int &N)
Nth eigenvalue from the bottom of MxM Frank matrix.
int get_default_device()
get default device number
Compressed Row Storage (CRS) format Matrix.
void set_log_filename(const std::string filename)
Specifying the log finename.
bool set_default_device(size_t device_num)
set default device number