void MAT_Multiply(int *A,
int *B, long *C,
unsigned int mA, unsigned int nA, unsigned int mB,
unsigned int nB, unsigned int mC, unsigned int nC)
{
#pragma HLS INTERFACE ap_fifo depth=100 port=A
#pragma HLS INTERFACE ap_fifo depth=100 port =B
#pragma HLS INTERFACE ap_fifo depth=100 port =C
int arrayA[1000][1000];
#pragma HLS ARRAY_RESHAPE variable=arrayA complete dim=2
#24 "partB/matrixmath.c"
int arrayB[1000][1000];
#pragma HLS ARRAY_RESHAPE variable=arrayB complete dim=1
#25 "partB/matrixmath.c"
long arrayC[1000][1000];
long temp;
unsigned int i, j, k;
if ((nA == mB)&(mA == mC)&(nB==nC))//Multiplication only when the dimensions are suitable
{
load_mat(A,arrayA,mA,nA);
load_mat(B,arrayB,mB,nB);
Row: for (i=0; i<1000; i++)
Col: for (j=0; j<1000; j++)
{
arrayC[i][j] = 0;
Product: for (k=0; k<1000; k++)
{
#pragma HLS PIPELINE
#41 "partB/matrixmath.c"
if ((i<mC)&(j<nC))
{
if (k<nA)
arrayC[i][j] += arrayA[i][k] * arrayB[k][j];
}
}
}
//Assignment
Row_Assign: for (i=0; i<1000; i++)
Col_Assign: for (j=0; j<1000; j++)
{
#pragma HLS PIPELINE
#54 "partB/matrixmath.c"
if ((i<mC)&(j<nC))
{
C[i*1000 +j] = arrayC[i][j];
}
}
}
}
void MAT_Multiply(int *A,
int *B, long *C,
unsigned int mA, unsigned int nA, unsigned int mB,
unsigned int nB, unsigned int mC, unsigned int nC)
{
#pragma HLS INTERFACE ap_fifo depth=3 port=A
#pragma HLS INTERFACE ap_fifo depth=3 port =B
#pragma HLS INTERFACE ap_fifo depth=3 port =C
#pragma empty_line
int arrayA[50][50];
int arrayB[50][50];
long arrayC[50][50];
long temp;
#pragma empty_line
unsigned int i, j, k;
if ((nA == mB)&(mA == mC)&(nB==nC))
{
load_mat(A,arrayA,mA,nA);
load_mat(B,arrayB,mB,nB);
#pragma empty_line
#pragma empty_line
Row: for (i=0; i<50; i++)
Col: for (j=0; j<50; j++)
{
arrayC[i][j] = 0;
Product: for (k=0; k<50; k++)
{
if ((i<mC)&(j<nC))
{
if (k<nA)
arrayC[i][j] += arrayA[i][k] * arrayB[k][j];
}
}
}
#pragma empty_line
#pragma empty_line
#pragma empty_line
Row_Assign: for (i=0; i<50; i++)
Col_Assign: for (j=0; j<50; j++)
{
if ((i<mC)&(j<nC))
{
C[i*50 +j] = arrayC[i][j];
}
}
#pragma empty_line
}
}
void MAT_Multiply(int *A,
int *B, long *C,
unsigned int mA, unsigned int nA, unsigned int mB,
unsigned int nB, unsigned int mC, unsigned int nC)
{
#pragma HLS INTERFACE ap_fifo port =A
#pragma HLS INTERFACE ap_fifo port =B
#pragma HLS INTERFACE ap_fifo port =C
int arrayA[100][100];
int arrayB[100][100];
long arrayC[100][100];
long temp;
unsigned int i, j, k;
if ((nA == mB)&(mA == mC)&(nB==nC))
{
load_mat(A,arrayA,mA,nA);
load_mat(B,arrayB,mB,nB);
Row: for (i=0; i<100; i++)
Col: for (j=0; j<100; j++)
{
arrayC[i][j] = 0;
Product: for (k=0; k<100; k++)
{
if ((i<mC)&(j<nC))
{
if (k<nA)
arrayC[i][j] += arrayA[i][k] * arrayB[k][j];
}
}
}
Row_Assign: for (i=0; i<100; i++)
Col_Assign: for (j=0; j<100; j++)
{
if ((i<mC)&(j<nC))
{
C[i*100 +j] = arrayC[i][j];
}
}
}
}
int load_scene_open(t_prog *prog, char *str)
{
char **file;
t_coord dir;
if (((file = str_to_wordtab(str, "\n")) == NULL)
|| (load_scene_open_beg(prog, file)))
return (-1);
prog->cam_fov.y = prog->cam_fov.x * ((prog->win_size.x
/ prog->win_size.y) / 1.5);
if (get_cam_pos(file, prog) == 1 ||
get_cam_look_at(file, prog) == 1 ||
load_mat(prog, file) == -1 ||
load_light(prog, file) == -1 ||
load_obj(prog, file) == -1)
return (-1);
if (prog->look_at.x == prog->cam_pos.x &&
prog->look_at.y == prog->cam_pos.y &&
prog->look_at.z == prog->cam_pos.z)
return (my_printf(2, "Wrong camera placement\n") - 1);
dir = normalize(minus_point(prog->look_at, prog->cam_pos));
prog->cam_rot.x = RTD(acos(-(dir.z / sqrt(pow(dir.x, 2)
+ pow(dir.z, 2))))) - 90;
prog->cam_rot.y = RTD((M_PI / 2 - acos(dir.y)));
prog->cam_dir = normalize(minus_point(prog->look_at, prog->cam_pos));
free_tab(file);
return (0);
}
/*
* Loads the first dataset into a matrix structure
*/
static int load_real_ball_data(int dataset, int numSet) {
int numCols;
static char fileName[100];
static char dirName[100];
if (dataset == 1) {
sprintf(dirName, "../../Desktop/okanKinestheticTeachin_20141210");
numCols = 25;
dist_to_table = -0.80;
}
else if (dataset == 2) {
sprintf(dirName, "../../Desktop/okanKinestheticTeachin_20151124");
numCols = 25 + 6; // cartesian robot pos and vel also saved for this dataset
dist_to_table = -1.15;
}
else {
printf("Dataset not found!\n");
return FALSE;
}
static char savefile[] = "unifyData";
sprintf(fileName,"%s//%s%d.txt",dirName, savefile, numSet);
int numRows = read_row_size(fileName);
realBallData = my_matrix(1,numRows,1,numCols);
if (load_mat(realBallData,numRows,numCols,fileName))
//print_mat_size("ballData", realBallData, numRows, 5);
return TRUE;
return FALSE;
}
// load params
void load_params(FILE* ifile, int max_examples) {
if ((max_examples < 0) || (max_examples > (int) n_examples))
max_examples = n_examples;
for(auto w : param_matrices) {
// we only load the whole matrics here
LOG(trace) << "load params " << "max_examples=" << max_examples
<< " cols(w)=" << w->n_cols;
assert(max_examples == (int) w->n_cols);
LOG(trace) << "load one param matrix";
load_mat(ifile, *w);
}
}
int main(int argc, char ** argv)
{
int t, j, k, n, sum;
int * mat;
int * best;
int run_number, runs_max;
srand(time(NULL));
if(argc < 3)
n = 15;
else
n = atoi(argv[2]);
if(argc < 2)
mat = load_mat("euler345_matrix.txt", n);
else
mat = load_mat(argv[1], n);
best = (int *) malloc(n * sizeof(best[0]));
for(j = 0; j < n; j++)
best[j] = j;
runs_max = INT_MIN;
for(run_number = 0; run_number < n * n; run_number++)
{
for(t = 0; t < n; t++)
{
int temp;
j = rand() % (n - 1);
k = j + 1 + rand() % (n - j - 1);
temp = best[j];
best[j] = best[k];
best[k] = temp;
}
for(t = 0; t < n; t++)
{
for(j = 0; j < n; j++)
{
for(k = j + 1; k < n; k++)
{
if(mat[k * n + best[j]] + mat[j * n + best[k]] >
mat[j * n + best[j]] + mat[k * n + best[k]])
{
int temp = best[j];
best[j] = best[k];
best[k] = temp;
}
}
}
}
sum = 0;
for(j = 0; j < n; j++)
{
//printf("%d\n", mat[j * n + best[j]]);
sum += mat[j * n + best[j]];
}
if(sum > runs_max)
runs_max = sum;
}
printf("Matrix sum: %d\n", runs_max);
return 0;
}
void SpinAdapted::Load(Matrix& a, std::ifstream &ifs)
{
boost::archive::binary_iarchive load_mat(ifs);
load_mat >> a;
}
