int main( int argc, char* argv[] )
{
int N = -1; // number of rows 2^12
int M = -1; // number of columns 2^10
int S = -1; // total size 2^22
int nrepeat = 100; // number of repeats of the test
// Read command line arguments.
for ( int i = 0; i < argc; i++ ) {
if ( ( strcmp( argv[ i ], "-N" ) == 0 ) || ( strcmp( argv[ i ], "-Rows" ) == 0 ) ) {
N = pow( 2, atoi( argv[ ++i ] ) );
printf( " User N is %d\n", N );
}
else if ( ( strcmp( argv[ i ], "-M" ) == 0 ) || ( strcmp( argv[ i ], "-Columns" ) == 0 ) ) {
M = pow( 2, atof( argv[ ++i ] ) );
printf( " User M is %d\n", M );
}
else if ( ( strcmp( argv[ i ], "-S" ) == 0 ) || ( strcmp( argv[ i ], "-Size" ) == 0 ) ) {
S = pow( 2, atof( argv[ ++i ] ) );
printf( " User S is %d\n", S );
}
else if ( strcmp( argv[ i ], "-nrepeat" ) == 0 ) {
nrepeat = atoi( argv[ ++i ] );
}
else if ( ( strcmp( argv[ i ], "-h" ) == 0 ) || ( strcmp( argv[ i ], "-help" ) == 0 ) ) {
printf( " y^T*A*x Options:\n" );
printf( " -Rows (-N) <int>: exponent num, determines number of rows 2^num (default: 2^12 = 4096)\n" );
printf( " -Columns (-M) <int>: exponent num, determines number of columns 2^num (default: 2^10 = 1024)\n" );
printf( " -Size (-S) <int>: exponent num, determines total matrix size 2^num (default: 2^22 = 4096*1024 )\n" );
printf( " -nrepeat <int>: number of repetitions (default: 100)\n" );
printf( " -help (-h): print this message\n\n" );
exit( 1 );
}
}
// Check sizes.
checkSizes( N, M, S, nrepeat );
Kokkos::initialize( argc, argv );
// EXERCISE give-away: Choose an Execution Space.
// typedef Kokkos::Serial ExecSpace;
// typedef Kokkos::Threads ExecSpace;
// typedef Kokkos::OpenMP ExecSpace;
// typedef Kokkos::Cuda ExecSpace;
// EXERCISE: Choose device memory space.
// typedef Kokkos::HostSpace MemSpace;
// typedef Kokkos::OpenMP MemSpace;
// typedef Kokkos::CudaSpace MemSpace;
// typedef Kokkos::CudaUVMSpace MemSpace;
// EXERCISE give-away: Choose a Layout.
// EXERCISE: When exercise is correctly implemented, then
// either layout will generate the correct answer.
// However, performance will be different!
// typedef Kokkos::LayoutLeft Layout;
// typedef Kokkos::LayoutRight Layout;
// EXERCISE give-away: Use a RangePolicy.
// typedef Kokkos::RangePolicy<ExecSpace> range_policy;
// Allocate y, x vectors and Matrix A on device.
// EXERCISE: Use MemSpace and Layout.
typedef Kokkos::View<double*> ViewVectorType;
typedef Kokkos::View<double**> ViewMatrixType;
ViewVectorType y( "y", N );
ViewVectorType x( "x", M );
ViewMatrixType A( "A", N, M );
// Create host mirrors of device views.
ViewVectorType::HostMirror h_y = Kokkos::create_mirror_view( y );
ViewVectorType::HostMirror h_x = Kokkos::create_mirror_view( x );
ViewMatrixType::HostMirror h_A = Kokkos::create_mirror_view( A );
// Initialize y vector on host.
for ( int i = 0; i < N; ++i ) {
h_y( i ) = 1;
}
// Initialize x vector on host.
for ( int i = 0; i < M; ++i ) {
h_x( i ) = 1;
}
// Initialize A matrix on host.
for ( int j = 0; j < N; ++j ) {
for ( int i = 0; i < M; ++i ) {
h_A( j, i ) = 1;
}
}
// Deep copy host views to device views.
Kokkos::deep_copy( y, h_y );
Kokkos::deep_copy( x, h_x );
Kokkos::deep_copy( A, h_A );
// Timer products.
struct timeval begin, end;
gettimeofday( &begin, NULL );
for ( int repeat = 0; repeat < nrepeat; repeat++ ) {
// Application: <y,Ax> = y^T*A*x
double result = 0;
// EXERCISE: Use Kokkos::RangePolicy<ExecSpace> to execute parallel_reduce
// in the correct space.
Kokkos::parallel_reduce( N, KOKKOS_LAMBDA ( int j, double &update ) {
double temp2 = 0;
for ( int i = 0; i < M; ++i ) {
temp2 += A( j, i ) * x( i );
}
update += y( j ) * temp2;
}, result );
int main(int argc, char* argv[])
{
int N = -1 ; // number of rows 2^12
int M = -1 ; // number of columns 2^10
int S = -1 ; // total size 2^22
int nrepeat = 100 ; // number of repeats of the test
// Read command line arguments
for(int i=0; i<argc; i++) {
if( (strcmp(argv[i], "-N") == 0) || (strcmp(argv[i], "-Rows") == 0) ) {
N = pow( 2, atoi(argv[++i]) );
printf(" User N is %d\n",N);
} else if( (strcmp(argv[i], "-M") == 0) || (strcmp(argv[i], "-Columns") == 0)) {
M = pow( 2, atof(argv[++i]) );
printf(" User M is %d\n",M);
} else if( (strcmp(argv[i], "-S") == 0) || (strcmp(argv[i], "-Size") == 0)) {
S = pow( 2, atof(argv[++i]) );
printf(" User S is %d\n",S);
} else if( strcmp(argv[i], "-nrepeat") == 0) {
nrepeat = atoi(argv[++i]);
} else if( (strcmp(argv[i], "-h") == 0) || (strcmp(argv[i], "-help") == 0) ) {
printf(" y^T*A*x Options:\n");
printf(" -Rows (-N) <int>: exponent num, determines number of rows 2^num (default: 2^12 = 4096)\n");
printf(" -Columns (-M) <int>: exponent num, determines number of columns 2^num (default: 2^10 = 1024)\n");
printf(" -Size (-S) <int>: exponent num, determines total matrix size 2^num (default: 2^22 = 4096*1024 )\n");
printf(" -nrepeat <int>: number of repetitions (default: 100)\n");
printf(" -help (-h): print this message\n\n");
exit(1); }
}
//Check Sizes
checkSizes( N, M, S, nrepeat );
Kokkos::initialize(argc,argv);
// Allocate y, x vectors and Matrix A:
// Device
typedef Kokkos::View<double*> ViewVectorType;
typedef Kokkos::View<double**> ViewMatrixType;
ViewVectorType y("y", N);
ViewVectorType x("x", M);
ViewMatrixType A("A", N, M);
ViewVectorType::HostMirror h_y = Kokkos::create_mirror_view(y);
ViewVectorType::HostMirror h_x = Kokkos::create_mirror_view(x);
ViewMatrixType::HostMirror h_A = Kokkos::create_mirror_view(A);
// Initialize y vector on host
for (int i = 0; i < N; ++i) {
h_y( i ) = 1;
}
// Initialize x vector on host
for (int i = 0; i < M; ++i) {
h_x( i ) = 1;
}
// Initialize A matrix, note 2D indexing computation on host
for (int j = 0; j < N; ++j) {
for ( int i = 0 ; i < M ; ++i ) {
h_A( j , i ) = 1;
}
}
Kokkos::deep_copy(y,h_y);
Kokkos::deep_copy(x,h_x);
Kokkos::deep_copy(A,h_A);
// Timer products
struct timeval begin,end;
gettimeofday(&begin,NULL);
for ( int repeat = 0; repeat < nrepeat; repeat++) {
//Application: <y,Ax> = y^T*A*x
double result = 0;
Kokkos::parallel_reduce( N, KOKKOS_LAMBDA ( int j, double &update ) {
double temp2 = 0;
for ( int i = 0 ; i < M ; ++i ) {
temp2 += A( j , i ) * x( i );
}
update += y( j ) * temp2;
}, result );
int main( int argc, char* argv[] )
{
int N = -1; // number of rows 2^12
int M = -1; // number of columns 2^10
int S = -1; // total size 2^22
int E = -1; // number of Elements
int nrepeat = 100; // number of repeats of the test
// Read command line arguments.
for ( int i = 0; i < argc; i++ ) {
if ( ( strcmp( argv[ i ], "-N" ) == 0 ) || ( strcmp( argv[ i ], "-Rows" ) == 0 ) ) {
N = pow( 2, atoi( argv[ ++i ] ) );
printf( " User N is %d\n", N );
}
else if ( ( strcmp( argv[ i ], "-M" ) == 0 ) || ( strcmp( argv[ i ], "-Columns" ) == 0 ) ) {
M = pow( 2, atof( argv[ ++i ] ) );
printf( " User M is %d\n", M );
}
else if ( ( strcmp( argv[ i ], "-S" ) == 0 ) || ( strcmp( argv[ i ], "-Size" ) == 0 ) ) {
S = pow( 2, atof( argv[ ++i ] ) );
printf( " User S is %d\n", S );
}
else if ( ( strcmp( argv[ i ], "-E" ) == 0 ) || ( strcmp( argv[ i ], "-Elements" ) == 0 ) ) {
E = pow( 2, atof( argv[ ++i ] ) );
printf( " User E is %d\n", E );
}
else if ( strcmp( argv[ i ], "-nrepeat" ) == 0 ) {
nrepeat = atoi( argv[ ++i ] );
}
else if ( ( strcmp( argv[ i ], "-h" ) == 0 ) || ( strcmp( argv[ i ], "-help" ) == 0 ) ) {
printf( " y^T*A*x Options:\n" );
printf( " -Rows (-N) <int>: exponent num, determines number of rows 2^num (default: 2^8 = 256)\n" );
printf( " -Columns (-M) <int>: exponent num, determines number of columns 2^num (default: 2^10 = 1024)\n" );
printf( " -Size (-S) <int>: exponent num, determines total matrix size 2^num (default: 2^18 = 256*1024 )\n" );
printf( " -Elements (-E) <int>: exponent num, determines number of elements 2^num (default: 2^10 = 1024 )\n" );
printf( " -nrepeat <int>: number of repetitions (default: 100)\n" );
printf( " -help (-h): print this message\n\n" );
exit( 1 );
}
}
// Check sizes.
checkSizes( N, M, S, E, nrepeat );
Kokkos::initialize( argc, argv );
typedef Kokkos::LayoutRight Layout;
typedef Kokkos::RangePolicy<> range_policy;
// Allocate y, x vectors and Matrix A on device.
typedef Kokkos::View<double**, Layout> ViewVectorType;
typedef Kokkos::View<double***, Layout> ViewMatrixType;
ViewVectorType y( "y", E, N );
ViewVectorType x( "x", E, M );
ViewMatrixType A( "A", E, N, M );
// Create host mirrors of device views.
ViewVectorType::HostMirror h_y = Kokkos::create_mirror_view( y );
ViewVectorType::HostMirror h_x = Kokkos::create_mirror_view( x );
ViewMatrixType::HostMirror h_A = Kokkos::create_mirror_view( A );
for ( int e = 0; e < E; e++ ) {
// Initialize y vector on host.
for ( int i = 0; i < N; ++i ) {
h_y( e, i ) = 1;
}
// Initialize x vector on host.
for ( int i = 0; i < M; ++i ) {
h_x( e, i ) = 1;
}
// Initialize A matrix on host.
for ( int j = 0; j < N; ++j ) {
for ( int i = 0; i < M; ++i ) {
h_A( e, j, i ) = 1;
}
}
}
// Deep copy host views to device views.
Kokkos::deep_copy( y, h_y );
Kokkos::deep_copy( x, h_x );
Kokkos::deep_copy( A, h_A );
typedef Kokkos::TeamPolicy<> team_policy;
typedef Kokkos::TeamPolicy<>::member_type member_type;
// Timer products.
struct timeval begin, end;
gettimeofday( &begin, NULL );
for ( int repeat = 0; repeat < nrepeat; repeat++ ) {
// Application: <y,Ax> = y^T*A*x
double result = 0;
Kokkos::parallel_reduce( team_policy( E, Kokkos::AUTO, 32 ), KOKKOS_LAMBDA ( const member_type &teamMember, double &update ) {
const int e = teamMember.league_rank();
double tempN = 0;
Kokkos::parallel_reduce( Kokkos::TeamThreadRange( teamMember, N ), [&] ( const int j, double &innerUpdateN ) {
double tempM = 0;
Kokkos::parallel_reduce( Kokkos::ThreadVectorRange( teamMember, M ), [&] ( const int i, double &innerUpdateM ) {
innerUpdateM += A( e, j, i ) * x( e, i );
}, tempM );
innerUpdateN += y( e, j ) * tempM;
}, tempN );
Kokkos::single( Kokkos::PerTeam( teamMember ), [&] () {
update += tempN;
});
}, result );
// Output result.
if ( repeat == ( nrepeat - 1 ) ) {
printf( " Computed result for %d x %d x %d is %lf\n", N, M, E, result );
}
const double solution = (double) N *(double) M *(double) E;
if ( result != solution ) {
printf( " Error: result( %lf ) != solution( %lf )\n", result, solution );
}
}
int main( int argc, char* argv[] )
{
int N = -1; // number of rows 2^12
int M = -1; // number of columns 2^10
int S = -1; // total size 2^22
int nrepeat = 100; // number of repeats of the test
// Read command line arguments.
for ( int i = 0; i < argc; i++ ) {
if ( ( strcmp( argv[ i ], "-N" ) == 0 ) || ( strcmp( argv[ i ], "-Rows" ) == 0 ) ) {
N = pow( 2, atoi( argv[ ++i ] ) );
printf( " User N is %d\n", N );
}
else if ( ( strcmp( argv[ i ], "-M" ) == 0 ) || ( strcmp( argv[ i ], "-Columns" ) == 0 ) ) {
M = pow( 2, atof( argv[ ++i ] ) );
printf( " User M is %d\n", M );
}
else if ( ( strcmp( argv[ i ], "-S" ) == 0 ) || ( strcmp( argv[ i ], "-Size" ) == 0 ) ) {
S = pow( 2, atof( argv[ ++i ] ) );
printf( " User S is %d\n", S );
}
else if ( strcmp( argv[ i ], "-nrepeat" ) == 0 ) {
nrepeat = atoi( argv[ ++i ] );
}
else if ( ( strcmp( argv[ i ], "-h" ) == 0 ) || ( strcmp( argv[ i ], "-help" ) == 0 ) ) {
printf( " y^T*A*x Options:\n" );
printf( " -Rows (-N) <int>: exponent num, determines number of rows 2^num (default: 2^12 = 4096)\n" );
printf( " -Columns (-M) <int>: exponent num, determines number of columns 2^num (default: 2^10 = 1024)\n" );
printf( " -Size (-S) <int>: exponent num, determines total matrix size 2^num (default: 2^22 = 4096*1024 )\n" );
printf( " -nrepeat <int>: number of repetitions (default: 100)\n" );
printf( " -help (-h): print this message\n\n" );
exit( 1 );
}
}
// Check sizes.
checkSizes( N, M, S, nrepeat );
Kokkos::initialize( argc, argv );
typedef Kokkos::DefaultExecutionSpace::array_layout Layout;
// typedef Kokkos::LayoutLeft Layout;
// typedef Kokkos::LayoutRight Layout;
typedef Kokkos::RangePolicy<> range_policy;
// Allocate y, x vectors and Matrix A on device.
typedef Kokkos::View<double*, Layout> ViewVectorType;
typedef Kokkos::View<double**, Layout> ViewMatrixType;
ViewVectorType y( "y", N );
ViewVectorType x( "x", M );
ViewMatrixType A( "A", N, M );
// Create host mirrors of device views.
ViewVectorType::HostMirror h_y = Kokkos::create_mirror_view( y );
ViewVectorType::HostMirror h_x = Kokkos::create_mirror_view( x );
ViewMatrixType::HostMirror h_A = Kokkos::create_mirror_view( A );
// Initialize y vector on host.
for ( int i = 0; i < N; ++i ) {
h_y( i ) = 1;
}
// Initialize x vector on host.
for ( int i = 0; i < M; ++i ) {
h_x( i ) = 1;
}
// Initialize A matrix on host.
for ( int j = 0; j < N; ++j ) {
for ( int i = 0; i < M; ++i ) {
h_A( j, i ) = 1;
}
}
// Deep copy host views to device views.
Kokkos::deep_copy( y, h_y );
Kokkos::deep_copy( x, h_x );
Kokkos::deep_copy( A, h_A );
// EXERCISE: Use hierarchical parallel execution policy for calculation.
// EXERCISE hints:
// typedef Kokkos::TeamPolicy<> team_policy;
// typedef Kokkos::TeamPolicy<>::member_type member_type;
// Timer products.
struct timeval begin, end;
gettimeofday( &begin, NULL );
for ( int repeat = 0; repeat < nrepeat; repeat++ ) {
// Application: <y,Ax> = y^T*A*x
double result = 0;
// EXERCISE: Convert from range_policy to team_policy.
Kokkos::parallel_reduce( range_policy( 0, N ), KOKKOS_LAMBDA ( int j, double &update ) {
// EXERCISE: Convert to nested Kokkos::parallel_reduce.
// EXERCISE hint: Kokkos::TeamThreadRange( ??? ) and [&].
double temp2 = 0;
for ( int i = 0; i < M; ++i ) {
temp2 += A( j, i ) * x( i );
}
// EXERCISE: Only one team member update the result.
update += y( j ) * temp2;
}, result );
int test_crs_matrix_test_singlevec(int numRows, int numCols, int nnz, int test, const char* filename, const bool binaryfile) {
typedef Kokkos::CrsMatrix<Scalar,int,execution_space,void,int> matrix_type ;
typedef typename Kokkos::View<Scalar*,Kokkos::LayoutLeft,execution_space> mv_type;
typedef typename Kokkos::View<Scalar*,Kokkos::LayoutLeft,execution_space,Kokkos::MemoryRandomAccess > mv_random_read_type;
typedef typename mv_type::HostMirror h_mv_type;
Scalar* val = NULL;
int* row = NULL;
int* col = NULL;
srand(17312837);
if(filename==NULL)
nnz = SparseMatrix_generate<Scalar,int>(numRows,numCols,nnz,nnz/numRows*0.2,numRows*0.01,val,row,col);
else
if(!binaryfile)
nnz = SparseMatrix_MatrixMarket_read<Scalar,int>(filename,numRows,numCols,nnz,val,row,col);
else
nnz = SparseMatrix_ReadBinaryGraph<Scalar,int>(filename,numRows,numCols,nnz,val,row,col);
matrix_type A("CRS::A",numRows,numCols,nnz,val,row,col,false);
mv_type x("X",numCols);
mv_random_read_type t_x(x);
mv_type y("Y",numRows);
h_mv_type h_x = Kokkos::create_mirror_view(x);
h_mv_type h_y = Kokkos::create_mirror_view(y);
h_mv_type h_y_compare = Kokkos::create_mirror(y);
typename matrix_type::StaticCrsGraphType::HostMirror h_graph = Kokkos::create_mirror(A.graph);
typename matrix_type::values_type::HostMirror h_values = Kokkos::create_mirror_view(A.values);
//Kokkos::deep_copy(h_graph.row_map,A.graph.row_map);
//h_a(k) = (Scalar) (1.0*(rand()%40)-20.);
for(int i=0; i<numCols;i++) {
h_x(i) = (Scalar) (1.0*(rand()%40)-20.);
h_y(i) = (Scalar) (1.0*(rand()%40)-20.);
}
for(int i=0;i<numRows;i++) {
int start = h_graph.row_map(i);
int end = h_graph.row_map(i+1);
for(int j=start;j<end;j++) {
h_values(j) = h_graph.entries(j) + i;
}
h_y_compare(i) = 0;
for(int j=start;j<end;j++) {
Scalar val = h_graph.entries(j) + i;
int idx = h_graph.entries(j);
h_y_compare(i)+=val*h_x(idx);
}
}
Kokkos::deep_copy(x,h_x);
Kokkos::deep_copy(y,h_y);
Kokkos::deep_copy(A.graph.entries,h_graph.entries);
Kokkos::deep_copy(A.values,h_values);
/*for(int i=0;i<numRows;i++)
for(int k = 0; k<numVecs; k++) {
//error[k]+=(h_y_compare(i,k)-h_y(i,k))*(h_y_compare(i,k)-h_y(i,k));
printf("%i %i %lf %lf %lf\n",i,k,h_y_compare(i,k),h_y(i,k),h_x(i,k));
}*/
typename Kokkos::CrsMatrix<Scalar,int,execution_space,void,int>::values_type x1("X1",numCols);
typename Kokkos::CrsMatrix<Scalar,int,execution_space,void,int>::values_type y1("Y1",numRows);
#ifdef NEWKERNEL
KokkosSparse::spmv("N",1.0,A,x1,0.0,y1);
#else
Kokkos::MV_Multiply(y1,A,x1);
#endif
#ifdef NEWKERNEL
KokkosSparse::spmv("N",1.0,A,x,0.0,y);
#else
Kokkos::MV_Multiply(y,A,x);
#endif
execution_space::fence();
Kokkos::deep_copy(h_y,y);
Scalar error = 0;
Scalar sum = 0;
for(int i=0;i<numRows;i++) {
error+=(h_y_compare(i)-h_y(i))*(h_y_compare(i)-h_y(i));
sum += h_y_compare(i)*h_y_compare(i);
// printf("%i %i %lf %lf %lf\n",i,k,h_y_compare(i,k),h_y(i,k),h_x(i,k));
}
//for(int i=0;i<A.nnz;i++) printf("%i %lf\n",h_graph.entries(i),h_values(i));
int num_errors = 0;
double total_error = 0;
double total_sum = 0;
num_errors += (error/(sum==0?1:sum))>1e-5?1:0;
total_error += error;
total_sum += sum;
int loop = 100;
Kokkos::Impl::Timer timer;
for(int i=0;i<loop;i++)
#ifdef NEWKERNEL
KokkosSparse::spmv("N",1.0,A,x,0.0,y);
#else
Kokkos::MV_Multiply(y,A,x);
#endif
execution_space::fence();
double time = timer.seconds();
double matrix_size = 1.0*((nnz*(sizeof(Scalar)+sizeof(int)) + numRows*sizeof(int)))/1024/1024;
double vector_size = 2.0*numRows*sizeof(Scalar)/1024/1024;
double vector_readwrite = (nnz+numCols)*sizeof(Scalar)/1024/1024;
double problem_size = matrix_size+vector_size;
printf("%i %i %i %i %6.2lf MB %6.2lf GB/s %6.2lf GFlop/s %6.3lf ms %i\n",nnz, numRows,numCols,1,problem_size,(matrix_size+vector_readwrite)/time*loop/1024, 2.0*nnz*loop/time/1e9, time/loop*1000, num_errors);
return (int)total_error;
}
int test_crs_matrix_test_singlevec(int numRows, int numCols, int nnz, int test, const char* filename, const bool binaryfile) {
typedef KokkosArray::CrsMatrix<Scalar,int,device_type> matrix_type ;
typedef typename KokkosArray::View<Scalar*,KokkosArray::LayoutLeft,device_type> mv_type;
typedef typename KokkosArray::View<Scalar*,KokkosArray::LayoutLeft,device_type,KokkosArray::MemoryRandomRead> mv_random_read_type;
typedef typename mv_type::HostMirror h_mv_type;
Scalar* val = NULL;
int* row = NULL;
int* col = NULL;
srand(17312837);
if(filename==NULL)
nnz = SparseMatrix_generate<Scalar,int>(numRows,numCols,nnz,nnz/numRows*0.2,numRows*0.01,val,row,col);
else
if(!binaryfile)
nnz = SparseMatrix_MatrixMarket_read<Scalar,int>(filename,numRows,numCols,nnz,val,row,col);
else
nnz = SparseMatrix_ReadBinaryGraph<Scalar,int>(filename,numRows,numCols,nnz,val,row,col);
matrix_type A("CRS::A",numRows,numCols,nnz,val,row,col,false);
mv_type x("X",numCols);
mv_random_read_type t_x(x);
mv_type y("Y",numRows);
h_mv_type h_x = KokkosArray::create_mirror_view(x);
h_mv_type h_y = KokkosArray::create_mirror_view(y);
h_mv_type h_y_compare = KokkosArray::create_mirror(y);
typename matrix_type::CrsArrayType::HostMirror h_graph = KokkosArray::create_mirror(A.graph);
typename matrix_type::values_type::HostMirror h_values = KokkosArray::create_mirror_view(A.values);
//KokkosArray::deep_copy(h_graph.row_map,A.graph.row_map);
//h_a(k) = (Scalar) (1.0*(rand()%40)-20.);
for(int i=0; i<numCols;i++) {
h_x(i) = (Scalar) (1.0*(rand()%40)-20.);
h_y(i) = (Scalar) (1.0*(rand()%40)-20.);
}
for(int i=0;i<numRows;i++) {
int start = h_graph.row_map(i);
int end = h_graph.row_map(i+1);
for(int j=start;j<end;j++) {
h_values(j) = h_graph.entries(j) + i;
}
h_y_compare(i) = 0;
for(int j=start;j<end;j++) {
Scalar val = h_graph.entries(j) + i;
int idx = h_graph.entries(j);
h_y_compare(i)+=val*h_x(idx);
}
}
KokkosArray::deep_copy(x,h_x);
KokkosArray::deep_copy(y,h_y);
KokkosArray::deep_copy(A.graph.entries,h_graph.entries);
KokkosArray::deep_copy(A.values,h_values);
/*for(int i=0;i<numRows;i++)
for(int k = 0; k<numVecs; k++) {
//error[k]+=(h_y_compare(i,k)-h_y(i,k))*(h_y_compare(i,k)-h_y(i,k));
printf("%i %i %lf %lf %lf\n",i,k,h_y_compare(i,k),h_y(i,k),h_x(i,k));
}*/
typename KokkosArray::CrsMatrix<Scalar,int,device_type>::values_type x1("X1",numCols);
typename KokkosArray::CrsMatrix<Scalar,int,device_type>::values_type y1("Y1",numRows);
KokkosArray::MV_Multiply(0.0,y1,1.0,A,x1);
KokkosArray::MV_Multiply(0.0,y,1.0,A,x);
device_type::fence();
KokkosArray::deep_copy(h_y,y);
Scalar error = 0;
Scalar sum = 0;
for(int i=0;i<numRows;i++) {
error+=(h_y_compare(i)-h_y(i))*(h_y_compare(i)-h_y(i));
sum += h_y_compare(i)*h_y_compare(i);
// printf("%i %i %lf %lf %lf\n",i,k,h_y_compare(i,k),h_y(i,k),h_x(i,k));
}
//for(int i=0;i<A.nnz;i++) printf("%i %lf\n",h_graph.entries(i),h_values(i));
int num_errors = 0;
double total_error = 0;
double total_sum = 0;
num_errors += (error/(sum==0?1:sum))>1e-5?1:0;
total_error += error;
total_sum += sum;
int loop = 10;
timespec starttime,endtime;
clock_gettime(CLOCK_REALTIME,&starttime);
for(int i=0;i<loop;i++)
KokkosArray::MV_Multiply(0.0,y,1.0,A,t_x);
device_type::fence();
clock_gettime(CLOCK_REALTIME,&endtime);
double time = endtime.tv_sec - starttime.tv_sec + 1.0 * (endtime.tv_nsec - starttime.tv_nsec) / 1000000000;
double matrix_size = 1.0*((nnz*(sizeof(Scalar)+sizeof(int)) + numRows*sizeof(int)))/1024/1024;
double vector_size = 2.0*numRows*sizeof(Scalar)/1024/1024;
double vector_readwrite = 2.0*nnz*sizeof(Scalar)/1024/1024;
double problem_size = matrix_size+vector_size;
printf("%i %i %i %i %6.2lf MB %6.2lf GB/s %6.2lf ms %i\n",nnz, numRows,numCols,1,problem_size,(matrix_size+vector_readwrite)/time*loop/1024, time/loop*1000, num_errors);
return (int)total_error;
}
int main(int argc, char* argv[])
{
int N = -1 ; // number of rows 2^12
int M = -1 ; // number of columns 2^10
int S = -1 ; // total size 2^22
int nrepeat = 100 ; // number of repeats of the test
// Read command line arguments
for(int i=0; i<argc; i++) {
if( (strcmp(argv[i], "-N") == 0) || (strcmp(argv[i], "-Rows") == 0) ) {
N = pow( 2, atoi(argv[++i]) );
printf(" User N is %d\n",N);
} else if( (strcmp(argv[i], "-M") == 0) || (strcmp(argv[i], "-Columns") == 0)) {
M = pow( 2, atof(argv[++i]) );
printf(" User M is %d\n",M);
} else if( (strcmp(argv[i], "-S") == 0) || (strcmp(argv[i], "-Size") == 0)) {
S = pow( 2, atof(argv[++i]) );
printf(" User S is %d\n",S);
} else if( strcmp(argv[i], "-nrepeat") == 0) {
nrepeat = atoi(argv[++i]);
} else if( (strcmp(argv[i], "-h") == 0) || (strcmp(argv[i], "-help") == 0) ) {
printf(" y^T*A*x Options:\n");
printf(" -Rows (-N) <int>: exponent num, determines number of rows 2^num (default: 2^12 = 4096)\n");
printf(" -Columns (-M) <int>: exponent num, determines number of columns 2^num (default: 2^10 = 1024)\n");
printf(" -Size (-S) <int>: exponent num, determines total matrix size 2^num (default: 2^22 = 4096*1024 )\n");
printf(" -nrepeat <int>: number of repetitions (default: 100)\n");
printf(" -help (-h): print this message\n\n");
exit(1); }
}
//Check Sizes
checkSizes( N, M, S, nrepeat );
Kokkos::initialize(argc,argv);
// typedef Kokkos::DefaultExecutionSpace::array_layout Layout;
// typedef Kokkos::LayoutLeft Layout ;
typedef Kokkos::LayoutRight Layout ;
// Allocate y, x vectors and Matrix A:
// Device
typedef Kokkos::View<double*, Layout> ViewVectorType;
typedef Kokkos::View<double**, Layout> ViewMatrixType;
ViewVectorType y("y", N);
ViewVectorType x("x", M);
ViewMatrixType A("A", N, M);
//Host mirror
ViewVectorType::HostMirror h_y = Kokkos::create_mirror_view(y);
ViewVectorType::HostMirror h_x = Kokkos::create_mirror_view(x);
ViewMatrixType::HostMirror h_A = Kokkos::create_mirror_view(A);
// Initialize y vector on host
for (int i = 0; i < N; ++i) {
h_y( i ) = 1;
}
// Initialize x vector on host
for (int i = 0; i < M; ++i) {
h_x( i ) = 1;
}
// Initialize A matrix, note 2D indexing computation on host
for (int j = 0; j < N; ++j) {
for ( int i = 0 ; i < M ; ++i ) {
h_A( j , i ) = 1;
}
}
//Deep copy host view to device views
Kokkos::deep_copy(y, h_y);
Kokkos::deep_copy(x, h_x);
Kokkos::deep_copy(A, h_A);
typedef Kokkos::TeamPolicy<> team_policy ;
typedef Kokkos::TeamPolicy<>::member_type member_type ;
// Timer products
struct timeval begin,end;
gettimeofday(&begin,NULL);
for ( int repeat = 0; repeat < nrepeat; repeat++) {
//Application: <y,Ax> = y^T*A*x
double result = 0;
Kokkos::parallel_reduce( team_policy( N , Kokkos::AUTO ), KOKKOS_LAMBDA ( const member_type& teamMember, double &update ) {
const int j = teamMember.league_rank();
double temp2 = 0;
Kokkos::parallel_reduce( Kokkos::TeamThreadRange( teamMember, M ), [&] (const int i, double &innerUpdate ) {
innerUpdate += A( j , i ) * x( i );
}, temp2);
if ( teamMember.team_rank() == 0 )
update += y( j ) * temp2;
}, result );
//Output result
if ( repeat == (nrepeat - 1) )
printf(" Computed result for %d x %d is %lf\n", N, M, result);
const double solution = (double)N *(double)M;
if ( result != solution ) {
printf(" Error: result( %lf ) != solution( %lf )\n",result,solution);
}
}
