int main(int, char**)
{
std::vector<std::chrono::duration<double, std::milli>> duration_vector;
Halide::Buffer<uint8_t> input = Halide::Tools::load_image("../rgb.png");
Halide::Buffer<float> kernel(3, 3);
kernel(0,0) = 0; kernel(0,1) = 1.0f/5; kernel(0,2) = 0;
kernel(1,0) = 1.0f/5; kernel(1,1) = 1.0f/5; kernel(1,2) = 1.0f/5;
kernel(2,0) = 0; kernel(2,1) = 1; kernel(2,2) = 0;
// Small size discrepancy with Halide benchmark:
Halide::Buffer<uint8_t> output(input.width(), input.height(), input.channels());
std::cout << "Dimensions : " << std::endl;
std::cout << "input.extent(0): " << input.extent(0) << std::endl; // Rows
std::cout << "input.extent(1): " << input.extent(1) << std::endl; // Cols
std::cout << "input.extent(2): " << input.extent(2) << std::endl; // Colors
#ifdef __PROFILE_CUDA__
cudaProfilerStop();
#endif
// Warm up
pencil_convolution(input.extent(0), input.extent(1), input.extent(1),
(uint8_t *) input.raw_buffer()->host,
(float *) kernel.raw_buffer()->host,
(uint8_t *) output.raw_buffer()->host);
#ifdef __PROFILE_CUDA__
cudaProfilerStart();
#endif
// Tiramisu
for (int i = 0; i < 100; i++) {
auto start = std::chrono::high_resolution_clock::now();
pencil_convolution(input.extent(0), input.extent(1), input.extent(1),
(uint8_t *) input.raw_buffer()->host,
(float *) kernel.raw_buffer()->host,
(uint8_t *) output.raw_buffer()->host);
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> duration = end - start;
duration_vector.push_back(duration);
}
std::cout << "time: " << median(duration_vector) << std::endl;
return 0;
}
void profileEnd() {
cudaDeviceSynchronize();
cudaProfilerStop();
}
void profileStop() {
cudaProfilerStop();
}
int main(int argc, char **argv){
int i, j;
char unused_stop = 0;
int iters = 10;
hash_args args;
char msg[BUFFER_LENGTH];
unsigned char hash[SHA_DIGEST_LENGTH];
char hex_hash[SHA_DIGEST_LENGTH*2];
char hex_difficulty[SHA_DIGEST_LENGTH*2] = "00000008ffffffffffffffffffffffffffffffff";
unsigned char difficulty;
struct timeval start, end, diff;
unsigned long total = 0, curr;
// Fill in some deterministic data
for(i = 0; i < BUFFER_LENGTH; i++){
msg[i] = i % 128;
}
pad_message(msg, COMMIT_LENGTH, BUFFER_LENGTH);
args.stop = &unused_stop;
args.msg = (char*)msg;
if(argc > 1){
iters = atoi(argv[1]);
}
if(argc > 2){
memcpy(hex_difficulty, argv[2], SHA_DIGEST_LENGTH*2);
}
difficulty = parse_difficulty(hex_difficulty);
printf("Starting benchmark with difficulty %02x\n", difficulty);
init_hasher(difficulty);
for(i = 0; i < iters; i++){
memset(msg, 0, COMMIT_LENGTH);
*((int*)(&(msg[0]))) = i;
args.found = 0;
cudaProfilerStart();
gettimeofday(&start, NULL);
force_hash(&args);
gettimeofday(&end, NULL);
cudaProfilerStop();
timersub(&end, &start, &diff);
curr = diff.tv_sec * 1000 + diff.tv_usec / 1000;
total += curr;
SHA1(msg, COMMIT_LENGTH, hash);
for(j=0; j < 20; j++){
sprintf(&hex_hash[j*2], "%02x", hash[j] & 0xff);
}
if(memcmp(hex_hash, hex_difficulty, SHA_DIGEST_LENGTH*2) > 0){
printf("Msg:");
for(j = 0; j < BUFFER_LENGTH; j++){
printf("%02x", msg[j] & 0xff);
}
printf("\nBad hash: %.40s\n", hex_hash);
exit(1);
} else {
printf("Successful run in %ld ms: %.40s\n", curr, hex_hash);
}
if(!args.found){
puts("Failed to find a hash!");
exit(1);
}
printf("\n");
}
printf("\n%ld ms per iteration (%d iters, %.40s difficulty)\n",
total / iters,
iters, hex_difficulty);
free_hasher();
exit(0);
}
int main(int argc, char *argv[]) {
int i,j,k,n;
int nx = NX;
int ny = NY;
int nz = NZ;
int nsteps = NSTEPS;
if( argc >= 4 ) {
nx = atoi( argv[1] );
ny = atoi( argv[2] );
nz = atoi( argv[3] );
}
if( argc >=5 )
nsteps = atoi( argv[4] );
StartTimer();
size_t nbytes = nx * ny * nz * sizeof(float);
float *restrict x = (float*)malloc( nbytes );
float *restrict y = (float*)malloc( nbytes );
float *restrict z = (float*)malloc( nbytes );
float *restrict f = (float*)malloc( nbytes );
float *restrict g = (float*)malloc( nbytes );
float *restrict fp = (float*)malloc( nbytes );
float *restrict gp = (float*)malloc( nbytes );
if( 0==x || 0==y || 0==z || 0==f || 0==g || 0==fp || 0==gp ) {
printf( "couldn't allocate fields on the host\n" );
return (-1);
}
float dx = 2.0f/(nx-1);
float dy = 2.0f/(ny-1);
float dz = 2.0f/(nz-1);
float dt = 0.00000005f; // in order for the system to be numerically dt < dx!!!
// initialize the grid to run from -1 to 1 in each direction
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
for (k=0; k<nz; k++) {
int offset = OFFSET(i, j, k, ny, nz);
x[offset] = -1.0f + (i)*dx;
y[offset] = -1.0f + (j)*dy;
z[offset] = -1.0f + (k)*dz;
}
}
}
// initialize the field to be a gaussian
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
for (k=0; k<nz; k++) {
int offset = OFFSET(i, j, k, ny, nz);
f[offset] = 0.2f*exp( - ( x[offset]*x[offset] +
y[offset]*y[offset] +
z[offset]*z[offset] ) / 0.05f);
g[offset] = 0.0f;
}
}
}
// output the initial data when there are an even number of points,
// pick a line closest to a coordinate axis
FILE *fPtr = fopen("wave3d.xline", "w");
for (i=0; i<nx; i++) {
int offset = OFFSET(i, ny/2, nz/2, ny, nz);
fprintf(fPtr,"%5.3f %10.6e\n",x[offset],f[offset]);
}
fprintf(fPtr,"\n");
float step = 0.0f;
int printevery = 20;
printf("step = %9.6f \n",step);
cudaProfilerStart();
#pragma acc enter data copyin(x[0:nx*ny*nz], y[0:nx*ny*nz], z[0:nx*ny*nz], f[0:nx*ny*nz], g[0:nx*ny*nz])
#pragma acc enter data create(fp[0:nx*ny*nz], gp[0:nx*ny*nz])
{
for (n=0; n<nsteps; n++) {
step = step + dt;
if (((n+1)%printevery)==0)
printf("step = %9.6f \n",step);
#pragma acc kernels
{
// predictor
#pragma acc loop independent collapse(2) gang
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
#pragma acc loop independent vector
for (k=0; k<nz; k++) {
int offset = OFFSET(i, j, k, ny, nz);
fp[offset] = f[offset] + dt * g[offset];
}
}
}
// static boundaries
#pragma acc loop independent collapse(2)
for (j=0; j<ny; j++) {
for (k=0; k<nz; k++) {
int xbeg = OFFSET(0, j, k, ny, nz);
int xend = OFFSET(nx-1, j, k, ny, nz);
gp[xbeg] = g[xbeg];
gp[xend] = g[xend];
}
}
#pragma acc loop independent collapse(2)
for (i=0; i<nx; i++) {
for (k=0; k<nz; k++) {
int ybeg = OFFSET(i, 0, k, ny, nz);
int yend = OFFSET(i, ny-1, k, ny, nz);
gp[ybeg] = g[ybeg];
gp[yend] = g[yend];
}
}
#pragma acc loop independent collapse(2)
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
int zbeg = OFFSET(i, j, 0, ny, nz);
int zend = OFFSET(i, j, nz-1, ny, nz);
gp[zbeg] = g[zbeg];
gp[zend] = g[zend];
}
}
// use the predictor to update gp
#pragma acc loop independent collapse(2) gang
for (i=1; i<nx-1; i++) {
for (j=1; j<ny-1; j++) {
#pragma acc loop independent vector
for (k=1; k<nz-1; k++) {
int current = OFFSET(i, j, k, ny, nz);
int next_x = OFFSET(i+1, j, k, ny, nz);
int next_y = OFFSET(i, j+1, k, ny, nz);
int next_z = OFFSET(i, j, k+1, ny, nz);
int prev_x = OFFSET(i-1, j, k, ny, nz);
int prev_y = OFFSET(i, j-1, k, ny, nz);
int prev_z = OFFSET(i, j, k-1, ny, nz);
gp[current] = g[current] + dt * (
(fp[next_x] - 2.0f * fp[current] + fp[prev_x]) / dx / dx +
(fp[next_y] - 2.0f * fp[current] + fp[prev_y]) / dy / dy +
(fp[next_z] - 2.0f * fp[current] + fp[prev_z]) / dz / dz );
}
}
}
// use the average g's to update f
#pragma acc loop independent collapse(2) gang
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
#pragma acc loop independent vector
for (k=0; k<nz; k++) {
int offset = OFFSET(i, j, k, ny, nz);
fp[offset] = f[offset] + dt * (0.5f * (g[offset] + gp[offset]));
}
}
}
// now update all the variables
#pragma acc loop independent collapse(2) gang
for (i=0; i<nx; i++) {
for (j=0; j<ny; j++) {
#pragma acc loop independent vector
for (int k=0; k<nz; k++) {
int offset = OFFSET(i, j, k, ny, nz);
f[offset] = fp[offset];
g[offset] = gp[offset];
}
}
}
} // pragma acc kernels
if (((n+1)%printevery)==0) {
#pragma acc update host(x[0:nx*(ny*nz)], f[0:nx*(ny*nz)])
for (i=0; i<nx; i++) {
int offset = OFFSET(i, ny/2, nz/2, ny, nz);
fprintf(fPtr,"%5.3f %10.6e\n",x[offset],f[offset]);
}
fprintf(fPtr,"\n");
}
} // for nsteps
} // pragma acc data
cudaProfilerStop();
cudaDeviceSynchronize();
free(x);
free(y);
free(z);
free(f);
free(g);
free(fp);
free(gp);
float totalTime = GetTimer();
printf("Total time: %f seconds\n", totalTime / 1000.0f);
exit(0);
}
extern "C" magma_int_t
magma_sidr_strms(
magma_s_matrix A, magma_s_matrix b, magma_s_matrix *x,
magma_s_solver_par *solver_par,
magma_queue_t queue )
{
magma_int_t info = MAGMA_NOTCONVERGED;
// prepare solver feedback
solver_par->solver = Magma_IDRMERGE;
solver_par->numiter = 0;
solver_par->spmv_count = 0;
solver_par->init_res = 0.0;
solver_par->final_res = 0.0;
solver_par->iter_res = 0.0;
solver_par->runtime = 0.0;
// constants
const float c_zero = MAGMA_S_ZERO;
const float c_one = MAGMA_S_ONE;
const float c_n_one = MAGMA_S_NEG_ONE;
// internal user options
const magma_int_t smoothing = 1; // 0 = disable, 1 = enable
const float angle = 0.7; // [0-1]
// local variables
magma_int_t iseed[4] = {0, 0, 0, 1};
magma_int_t dof;
magma_int_t s;
magma_int_t distr;
magma_int_t k, i, sk;
magma_int_t innerflag;
magma_int_t ldd;
magma_int_t q;
float residual;
float nrm;
float nrmb;
float nrmr;
float nrmt;
float rho;
float om;
float gamma;
// matrices and vectors
magma_s_matrix dxs = {Magma_CSR};
magma_s_matrix dr = {Magma_CSR}, drs = {Magma_CSR};
magma_s_matrix dP = {Magma_CSR}, dP1 = {Magma_CSR};
magma_s_matrix dG = {Magma_CSR}, dGcol = {Magma_CSR};
magma_s_matrix dU = {Magma_CSR};
magma_s_matrix dM = {Magma_CSR};
magma_s_matrix df = {Magma_CSR};
magma_s_matrix dt = {Magma_CSR}, dtt = {Magma_CSR};
magma_s_matrix dc = {Magma_CSR};
magma_s_matrix dv = {Magma_CSR};
magma_s_matrix dskp = {Magma_CSR};
magma_s_matrix dalpha = {Magma_CSR};
magma_s_matrix dbeta = {Magma_CSR};
float *hMdiag = NULL;
float *hskp = NULL;
float *halpha = NULL;
float *hbeta = NULL;
float *d1 = NULL, *d2 = NULL;
// queue variables
const magma_int_t nqueues = 3; // number of queues
magma_queue_t queues[nqueues];
// chronometry
real_Double_t tempo1, tempo2;
// create additional queues
queues[0] = queue;
for ( q = 1; q < nqueues; q++ ) {
magma_queue_create( queue->device(), &(queues[q]) );
}
// initial s space
// TODO: add option for 's' (shadow space number)
// Hack: uses '--restart' option as the shadow space number.
// This is not a good idea because the default value of restart option is used to detect
// if the user provided a custom restart. This means that if the default restart value
// is changed then the code will think it was the user (unless the default value is
// also updated in the 'if' statement below.
s = 1;
if ( solver_par->restart != 50 ) {
if ( solver_par->restart > A.num_cols ) {
s = A.num_cols;
} else {
s = solver_par->restart;
}
}
solver_par->restart = s;
// set max iterations
solver_par->maxiter = min( 2 * A.num_cols, solver_par->maxiter );
// check if matrix A is square
if ( A.num_rows != A.num_cols ) {
//printf("Matrix A is not square.\n");
info = MAGMA_ERR_NOT_SUPPORTED;
goto cleanup;
}
// |b|
nrmb = magma_snrm2( b.num_rows, b.dval, 1, queue );
if ( nrmb == 0.0 ) {
magma_sscal( x->num_rows, MAGMA_S_ZERO, x->dval, 1, queue );
info = MAGMA_SUCCESS;
goto cleanup;
}
// t = 0
// make t twice as large to contain both, dt and dr
ldd = magma_roundup( b.num_rows, 32 );
CHECK( magma_svinit( &dt, Magma_DEV, ldd, 2, c_zero, queue ));
dt.num_rows = b.num_rows;
dt.num_cols = 1;
dt.nnz = dt.num_rows;
// redirect the dr.dval to the second part of dt
CHECK( magma_svinit( &dr, Magma_DEV, b.num_rows, 1, c_zero, queue ));
magma_free( dr.dval );
dr.dval = dt.dval + ldd;
// r = b - A x
CHECK( magma_sresidualvec( A, b, *x, &dr, &nrmr, queue ));
// |r|
solver_par->init_res = nrmr;
solver_par->final_res = solver_par->init_res;
solver_par->iter_res = solver_par->init_res;
if ( solver_par->verbose > 0 ) {
solver_par->res_vec[0] = (real_Double_t)nrmr;
}
// check if initial is guess good enough
if ( nrmr <= solver_par->atol ||
nrmr/nrmb <= solver_par->rtol ) {
info = MAGMA_SUCCESS;
goto cleanup;
}
// P = randn(n, s)
// P = ortho(P)
//---------------------------------------
// P = 0.0
CHECK( magma_svinit( &dP, Magma_CPU, A.num_cols, s, c_zero, queue ));
// P = randn(n, s)
distr = 3; // 1 = unif (0,1), 2 = unif (-1,1), 3 = normal (0,1)
dof = dP.num_rows * dP.num_cols;
lapackf77_slarnv( &distr, iseed, &dof, dP.val );
// transfer P to device
CHECK( magma_smtransfer( dP, &dP1, Magma_CPU, Magma_DEV, queue ));
magma_smfree( &dP, queue );
// P = ortho(P1)
if ( dP1.num_cols > 1 ) {
// P = magma_sqr(P1), QR factorization
CHECK( magma_sqr( dP1.num_rows, dP1.num_cols, dP1, dP1.ld, &dP, NULL, queue ));
} else {
// P = P1 / |P1|
nrm = magma_snrm2( dof, dP1.dval, 1, queue );
nrm = 1.0 / nrm;
magma_sscal( dof, nrm, dP1.dval, 1, queue );
CHECK( magma_smtransfer( dP1, &dP, Magma_DEV, Magma_DEV, queue ));
}
magma_smfree( &dP1, queue );
//---------------------------------------
// allocate memory for the scalar products
CHECK( magma_smalloc_pinned( &hskp, 5 ));
CHECK( magma_svinit( &dskp, Magma_DEV, 4, 1, c_zero, queue ));
CHECK( magma_smalloc_pinned( &halpha, s ));
CHECK( magma_svinit( &dalpha, Magma_DEV, s, 1, c_zero, queue ));
CHECK( magma_smalloc_pinned( &hbeta, s ));
CHECK( magma_svinit( &dbeta, Magma_DEV, s, 1, c_zero, queue ));
// workspace for merged dot product
CHECK( magma_smalloc( &d1, max(2, s) * b.num_rows ));
CHECK( magma_smalloc( &d2, max(2, s) * b.num_rows ));
// smoothing enabled
if ( smoothing > 0 ) {
// set smoothing solution vector
CHECK( magma_smtransfer( *x, &dxs, Magma_DEV, Magma_DEV, queue ));
// tt = 0
// make tt twice as large to contain both, dtt and drs
ldd = magma_roundup( b.num_rows, 32 );
CHECK( magma_svinit( &dtt, Magma_DEV, ldd, 2, c_zero, queue ));
dtt.num_rows = dr.num_rows;
dtt.num_cols = 1;
dtt.nnz = dtt.num_rows;
// redirect the drs.dval to the second part of dtt
CHECK( magma_svinit( &drs, Magma_DEV, dr.num_rows, 1, c_zero, queue ));
magma_free( drs.dval );
drs.dval = dtt.dval + ldd;
// set smoothing residual vector
magma_scopyvector( dr.num_rows, dr.dval, 1, drs.dval, 1, queue );
}
// G(n,s) = 0
if ( s > 1 ) {
ldd = magma_roundup( A.num_rows, 32 );
CHECK( magma_svinit( &dG, Magma_DEV, ldd, s, c_zero, queue ));
dG.num_rows = A.num_rows;
} else {
CHECK( magma_svinit( &dG, Magma_DEV, A.num_rows, s, c_zero, queue ));
}
// dGcol represents a single column of dG, array pointer is set inside loop
CHECK( magma_svinit( &dGcol, Magma_DEV, dG.num_rows, 1, c_zero, queue ));
magma_free( dGcol.dval );
// U(n,s) = 0
if ( s > 1 ) {
ldd = magma_roundup( A.num_cols, 32 );
CHECK( magma_svinit( &dU, Magma_DEV, ldd, s, c_zero, queue ));
dU.num_rows = A.num_cols;
} else {
CHECK( magma_svinit( &dU, Magma_DEV, A.num_cols, s, c_zero, queue ));
}
// M(s,s) = I
CHECK( magma_svinit( &dM, Magma_DEV, s, s, c_zero, queue ));
CHECK( magma_smalloc_pinned( &hMdiag, s ));
magmablas_slaset( MagmaFull, dM.num_rows, dM.num_cols, c_zero, c_one, dM.dval, dM.ld, queue );
// f = 0
CHECK( magma_svinit( &df, Magma_DEV, dP.num_cols, 1, c_zero, queue ));
// c = 0
CHECK( magma_svinit( &dc, Magma_DEV, dM.num_cols, 1, c_zero, queue ));
// v = r
CHECK( magma_smtransfer( dr, &dv, Magma_DEV, Magma_DEV, queue ));
//--------------START TIME---------------
// chronometry
tempo1 = magma_sync_wtime( queue );
if ( solver_par->verbose > 0 ) {
solver_par->timing[0] = 0.0;
}
cudaProfilerStart();
om = MAGMA_S_ONE;
gamma = MAGMA_S_ZERO;
innerflag = 0;
// new RHS for small systems
// f = P' r
// Q1
magma_sgemvmdot_shfl( dP.num_rows, dP.num_cols, dP.dval, dr.dval, d1, d2, df.dval, queues[1] );
// skp[4] = f(k)
// Q1
magma_sgetvector_async( 1, df.dval, 1, &hskp[4], 1, queues[1] );
// c(k:s) = f(k:s)
// Q1
magma_scopyvector_async( s, df.dval, 1, dc.dval, 1, queues[1] );
// c(k:s) = M(k:s,k:s) \ f(k:s)
// Q1
magma_strsv( MagmaLower, MagmaNoTrans, MagmaNonUnit, s, dM.dval, dM.ld, dc.dval, 1, queues[1] );
// start iteration
do
{
solver_par->numiter++;
// shadow space loop
for ( k = 0; k < s; ++k ) {
sk = s - k;
dGcol.dval = dG.dval + k * dG.ld;
// v = r - G(:,k:s) c(k:s)
// Q1
magmablas_sgemv( MagmaNoTrans, dG.num_rows, sk, c_n_one, dGcol.dval, dG.ld, &dc.dval[k], 1, c_one, dv.dval, 1, queues[1] );
// U(:,k) = om * v + U(:,k:s) c(k:s)
// Q1
magmablas_sgemv( MagmaNoTrans, dU.num_rows, sk, c_one, &dU.dval[k*dU.ld], dU.ld, &dc.dval[k], 1, om, dv.dval, 1, queues[1] );
// G(:,k) = A U(:,k)
// Q1
CHECK( magma_s_spmv( c_one, A, dv, c_zero, dGcol, queues[1] ));
solver_par->spmv_count++;
// bi-orthogonalize the new basis vectors
for ( i = 0; i < k; ++i ) {
// alpha = P(:,i)' G(:,k)
// Q1
halpha[i] = magma_sdot( dP.num_rows, &dP.dval[i*dP.ld], 1, dGcol.dval, 1, queues[1] );
// implicit sync Q1 --> alpha = P(:,i)' G(:,k)
// alpha = alpha / M(i,i)
halpha[i] = halpha[i] / hMdiag[i];
// G(:,k) = G(:,k) - alpha * G(:,i)
// Q1
magma_saxpy( dG.num_rows, -halpha[i], &dG.dval[i*dG.ld], 1, dGcol.dval, 1, queues[1] );
}
// sync Q1 --> G(:,k) = G(:,k) - alpha * G(:,i), skp[4] = f(k)
magma_queue_sync( queues[1] );
// new column of M = P'G, first k-1 entries are zero
// M(k:s,k) = P(:,k:s)' G(:,k)
// Q2
magma_sgemvmdot_shfl( dP.num_rows, sk, &dP.dval[k*dP.ld], dGcol.dval, d1, d2, &dM.dval[k*dM.ld+k], queues[2] );
// non-first s iteration
if ( k > 0 ) {
// alpha = dalpha
// Q0
magma_ssetvector_async( k, halpha, 1, dalpha.dval, 1, queues[0] );
// U update outside of loop using GEMV
// U(:,k) = U(:,k) - U(:,1:k) * alpha(1:k)
// Q0
magmablas_sgemv( MagmaNoTrans, dU.num_rows, k, c_n_one, dU.dval, dU.ld, dalpha.dval, 1, c_one, dv.dval, 1, queues[0] );
}
// Mdiag(k) = M(k,k)
// Q2
magma_sgetvector( 1, &dM.dval[k*dM.ld+k], 1, &hMdiag[k], 1, queues[2] );
// implicit sync Q2 --> Mdiag(k) = M(k,k)
// U(:,k) = v
// Q0
magma_scopyvector_async( dU.num_rows, dv.dval, 1, &dU.dval[k*dU.ld], 1, queues[0] );
// check M(k,k) == 0
if ( MAGMA_S_EQUAL(hMdiag[k], MAGMA_S_ZERO) ) {
innerflag = 1;
info = MAGMA_DIVERGENCE;
break;
}
// beta = f(k) / M(k,k)
hbeta[k] = hskp[4] / hMdiag[k];
// check for nan
if ( magma_s_isnan( hbeta[k] ) || magma_s_isinf( hbeta[k] )) {
innerflag = 1;
info = MAGMA_DIVERGENCE;
break;
}
// r = r - beta * G(:,k)
// Q2
magma_saxpy( dr.num_rows, -hbeta[k], dGcol.dval, 1, dr.dval, 1, queues[2] );
// non-last s iteration
if ( (k + 1) < s ) {
// f(k+1:s) = f(k+1:s) - beta * M(k+1:s,k)
// Q1
magma_saxpy( sk-1, -hbeta[k], &dM.dval[k*dM.ld+(k+1)], 1, &df.dval[k+1], 1, queues[1] );
// c(k+1:s) = f(k+1:s)
// Q1
magma_scopyvector_async( sk-1, &df.dval[k+1], 1, &dc.dval[k+1], 1, queues[1] );
// c(k+1:s) = M(k+1:s,k+1:s) \ f(k+1:s)
// Q1
magma_strsv( MagmaLower, MagmaNoTrans, MagmaNonUnit, sk-1, &dM.dval[(k+1)*dM.ld+(k+1)], dM.ld, &dc.dval[k+1], 1, queues[1] );
// skp[4] = f(k+1)
// Q1
magma_sgetvector_async( 1, &df.dval[k+1], 1, &hskp[4], 1, queues[1] );
}
// smoothing disabled
if ( smoothing <= 0 ) {
// |r|
// Q2
nrmr = magma_snrm2( dr.num_rows, dr.dval, 1, queues[2] );
// implicit sync Q2 --> |r|
// smoothing enabled
} else {
// smoothing operation
//---------------------------------------
// t = rs - r
// Q2
magma_sidr_smoothing_1( drs.num_rows, drs.num_cols, drs.dval, dr.dval, dtt.dval, queues[2] );
// x = x + beta * U(:,k)
// Q0
magma_saxpy( x->num_rows, hbeta[k], &dU.dval[k*dU.ld], 1, x->dval, 1, queues[0] );
// t't
// t'rs
// Q2
CHECK( magma_sgemvmdot_shfl( dt.ld, 2, dtt.dval, dtt.dval, d1, d2, &dskp.dval[2], queues[2] ));
// skp[2-3] = dskp[2-3]
// Q2
magma_sgetvector( 2, &dskp.dval[2], 1, &hskp[2], 1, queues[2] );
// implicit sync Q2 --> skp = dskp
// gamma = (t' * rs) / (t' * t)
gamma = hskp[3] / hskp[2];
// rs = rs - gamma * t
// Q1
magma_saxpy( drs.num_rows, -gamma, dtt.dval, 1, drs.dval, 1, queues[1] );
// xs = xs - gamma * (xs - x)
// Q0
magma_sidr_smoothing_2( dxs.num_rows, dxs.num_cols, -gamma, x->dval, dxs.dval, queues[0] );
// |rs|
// Q1
nrmr = magma_snrm2( drs.num_rows, drs.dval, 1, queues[1] );
// implicit sync Q0 --> |r|
//---------------------------------------
}
// v = r
// Q1
magma_scopyvector_async( dr.num_rows, dr.dval, 1, dv.dval, 1, queues[1] );
// last s iteration
if ( (k + 1) == s ) {
// t = A r
// Q2
CHECK( magma_s_spmv( c_one, A, dr, c_zero, dt, queues[2] ));
solver_par->spmv_count++;
// t't
// t'r
// Q2
CHECK( magma_sgemvmdot_shfl( dt.ld, 2, dt.dval, dt.dval, d1, d2, dskp.dval, queues[2] ));
}
// store current timing and residual
if ( solver_par->verbose > 0 ) {
tempo2 = magma_sync_wtime( queue );
if ( (solver_par->numiter) % solver_par->verbose == 0 ) {
solver_par->res_vec[(solver_par->numiter) / solver_par->verbose]
= (real_Double_t)nrmr;
solver_par->timing[(solver_par->numiter) / solver_par->verbose]
= (real_Double_t)tempo2 - tempo1;
}
}
// check convergence or iteration limit
if ( nrmr <= solver_par->atol ||
nrmr/nrmb <= solver_par->rtol ) {
s = k + 1; // for the x-update outside the loop
innerflag = 2;
info = MAGMA_SUCCESS;
break;
}
}
// smoothing disabled
if ( smoothing <= 0 && innerflag != 1 ) {
// dbeta(1:s) = beta(1:s)
// Q0
magma_ssetvector_async( s, hbeta, 1, dbeta.dval, 1, queues[0] );
// x = x + U(:,1:s) * beta(1:s)
// Q0
magmablas_sgemv( MagmaNoTrans, dU.num_rows, s, c_one, dU.dval, dU.ld, dbeta.dval, 1, c_one, x->dval, 1, queues[0] );
}
// check convergence or iteration limit or invalid result of inner loop
if ( innerflag > 0 ) {
break;
}
// computation of a new omega
//---------------------------------------
// skp[0-2] = dskp[0-2]
// Q2
magma_sgetvector( 2, dskp.dval, 1, hskp, 1, queues[2] );
// implicit sync Q2 --> skp = dskp
// |t|
nrmt = magma_ssqrt( MAGMA_S_REAL(hskp[0]) );
// rho = abs((t' * r) / (|t| * |r|))
rho = MAGMA_D_ABS( MAGMA_S_REAL(hskp[1]) / (nrmt * nrmr) );
// om = (t' * r) / (|t| * |t|)
om = hskp[1] / hskp[0];
if ( rho < angle ) {
om = (om * angle) / rho;
}
//---------------------------------------
if ( MAGMA_S_EQUAL(om, MAGMA_S_ZERO) ) {
info = MAGMA_DIVERGENCE;
break;
}
// sync Q1 --> v = r
magma_queue_sync( queues[1] );
// r = r - om * t
// Q2
magma_saxpy( dr.num_rows, -om, dt.dval, 1, dr.dval, 1, queues[2] );
// x = x + om * v
// Q0
magma_saxpy( x->num_rows, om, dv.dval, 1, x->dval, 1, queues[0] );
// smoothing disabled
if ( smoothing <= 0 ) {
// |r|
// Q2
nrmr = magma_snrm2( dr.num_rows, dr.dval, 1, queues[2] );
// implicit sync Q2 --> |r|
// v = r
// Q0
magma_scopyvector_async( dr.num_rows, dr.dval, 1, dv.dval, 1, queues[0] );
// new RHS for small systems
// f = P' r
// Q1
magma_sgemvmdot_shfl( dP.num_rows, dP.num_cols, dP.dval, dr.dval, d1, d2, df.dval, queues[1] );
// skp[4] = f(k)
// Q1
magma_sgetvector_async( 1, df.dval, 1, &hskp[4], 1, queues[1] );
// c(k:s) = f(k:s)
// Q1
magma_scopyvector_async( s, df.dval, 1, dc.dval, 1, queues[1] );
// c(k:s) = M(k:s,k:s) \ f(k:s)
// Q1
magma_strsv( MagmaLower, MagmaNoTrans, MagmaNonUnit, s, dM.dval, dM.ld, dc.dval, 1, queues[1] );
// smoothing enabled
} else {
// smoothing operation
//---------------------------------------
// t = rs - r
// Q2
magma_sidr_smoothing_1( drs.num_rows, drs.num_cols, drs.dval, dr.dval, dtt.dval, queues[2] );
// t't
// t'rs
// Q2
CHECK( magma_sgemvmdot_shfl( dt.ld, 2, dtt.dval, dtt.dval, d1, d2, &dskp.dval[2], queues[2] ));
// skp[2-3] = dskp[2-3]
// Q2
magma_sgetvector( 2, &dskp.dval[2], 1, &hskp[2], 1, queues[2] );
// implicit sync Q2 --> skp = dskp
// gamma = (t' * rs) / (t' * t)
gamma = hskp[3] / hskp[2];
// rs = rs - gamma * (rs - r)
// Q2
magma_saxpy( drs.num_rows, -gamma, dtt.dval, 1, drs.dval, 1, queues[2] );
// xs = xs - gamma * (xs - x)
// Q0
magma_sidr_smoothing_2( dxs.num_rows, dxs.num_cols, -gamma, x->dval, dxs.dval, queues[0] );
// v = r
// Q0
magma_scopyvector_async( dr.num_rows, dr.dval, 1, dv.dval, 1, queues[0] );
// new RHS for small systems
// f = P' r
// Q1
magma_sgemvmdot_shfl( dP.num_rows, dP.num_cols, dP.dval, dr.dval, d1, d2, df.dval, queues[1] );
// skp[4] = f(k)
// Q1
magma_sgetvector_async( 1, df.dval, 1, &hskp[4], 1, queues[1] );
// c(k:s) = f(k:s)
// Q1
magma_scopyvector_async( s, df.dval, 1, dc.dval, 1, queues[1] );
// |rs|
// Q2
nrmr = magma_snrm2( drs.num_rows, drs.dval, 1, queues[2] );
// implicit sync Q2 --> |r|
// c(k:s) = M(k:s,k:s) \ f(k:s)
// Q1
magma_strsv( MagmaLower, MagmaNoTrans, MagmaNonUnit, s, dM.dval, dM.ld, dc.dval, 1, queues[1] );
//---------------------------------------
}
// store current timing and residual
if ( solver_par->verbose > 0 ) {
tempo2 = magma_sync_wtime( queue );
magma_queue_sync( queue );
if ( (solver_par->numiter) % solver_par->verbose == 0 ) {
solver_par->res_vec[(solver_par->numiter) / solver_par->verbose]
= (real_Double_t)nrmr;
solver_par->timing[(solver_par->numiter) / solver_par->verbose]
= (real_Double_t)tempo2 - tempo1;
}
}
// check convergence or iteration limit
if ( nrmr <= solver_par->atol ||
nrmr/nrmb <= solver_par->rtol ) {
info = MAGMA_SUCCESS;
break;
}
// sync Q0 --> v = r
magma_queue_sync( queues[0] );
}
while ( solver_par->numiter + 1 <= solver_par->maxiter );
// sync all queues
for ( q = 0; q < nqueues; q++ ) {
magma_queue_sync( queues[q] );
}
// smoothing enabled
if ( smoothing > 0 ) {
// x = xs
magma_scopyvector_async( x->num_rows, dxs.dval, 1, x->dval, 1, queue );
// r = rs
magma_scopyvector_async( dr.num_rows, drs.dval, 1, dr.dval, 1, queue );
}
cudaProfilerStop();
// get last iteration timing
tempo2 = magma_sync_wtime( queue );
magma_queue_sync( queue );
solver_par->runtime = (real_Double_t)tempo2 - tempo1;
//--------------STOP TIME----------------
// get final stats
solver_par->iter_res = nrmr;
CHECK( magma_sresidualvec( A, b, *x, &dr, &residual, queue ));
solver_par->final_res = residual;
// set solver conclusion
if ( info != MAGMA_SUCCESS && info != MAGMA_DIVERGENCE ) {
if ( solver_par->init_res > solver_par->final_res ) {
info = MAGMA_SLOW_CONVERGENCE;
}
}
cleanup:
// free resources
// sync all queues, destory additional queues
magma_queue_sync( queues[0] );
for ( q = 1; q < nqueues; q++ ) {
magma_queue_sync( queues[q] );
magma_queue_destroy( queues[q] );
}
// smoothing enabled
if ( smoothing > 0 ) {
drs.dval = NULL; // needed because its pointer is redirected to dtt
magma_smfree( &dxs, queue );
magma_smfree( &drs, queue );
magma_smfree( &dtt, queue );
}
dr.dval = NULL; // needed because its pointer is redirected to dt
dGcol.dval = NULL; // needed because its pointer is redirected to dG
magma_smfree( &dr, queue );
magma_smfree( &dP, queue );
magma_smfree( &dP1, queue );
magma_smfree( &dG, queue );
magma_smfree( &dGcol, queue );
magma_smfree( &dU, queue );
magma_smfree( &dM, queue );
magma_smfree( &df, queue );
magma_smfree( &dt, queue );
magma_smfree( &dc, queue );
magma_smfree( &dv, queue );
magma_smfree( &dskp, queue );
magma_smfree( &dalpha, queue );
magma_smfree( &dbeta, queue );
magma_free_pinned( hMdiag );
magma_free_pinned( hskp );
magma_free_pinned( halpha );
magma_free_pinned( hbeta );
magma_free( d1 );
magma_free( d2 );
solver_par->info = info;
return info;
/* magma_sidr_strms */
}
