void mk_alternating(tl_Node *p) /* generates an alternating automaton for p */
{
if (tl_stats)
{
getrusage(RUSAGE_SELF, &tr_debut);
}
node_size = calculate_node_size(p) + 1; /* number of states in the automaton */
label = (tl_Node **) tl_emalloc(node_size * sizeof(tl_Node *));
transition = (ATrans **) tl_emalloc(node_size * sizeof(ATrans *));
node_size = node_size / (8 * sizeof(int)) + 1;
sym_size = calculate_sym_size(p); /* number of predicates */
if (sym_size)
{
sym_table = (char **) tl_emalloc(sym_size * sizeof(char *));
}
sym_size = sym_size / (8 * sizeof(int)) + 1;
final_set = make_set(-1, 0);
transition[0] = boolean(p); /* generates the alternating automaton */
if (tl_verbose)
{
fprintf(tl_out, "\nAlternating automaton before simplification\n");
print_alternating();
}
if (tl_simp_diff)
{
simplify_astates(); /* keeps only accessible states */
if (tl_verbose)
{
fprintf(tl_out, "\nAlternating automaton after simplification\n");
print_alternating();
}
}
if (tl_stats)
{
getrusage(RUSAGE_SELF, &tr_fin);
fprintf(tl_out, "\n%i states, %i transitions\n", astate_count, atrans_count);
}
releasenode(1, p);
tfree(label);
}
/*! \brief Symmetric elimination tree
*
* <pre>
* p = spsymetree (A);
*
* Find the elimination tree for symmetric matrix A.
* This uses Liu's algorithm, and runs in time O(nz*log n).
*
* Input:
* Square sparse matrix A. No check is made for symmetry;
* elements below and on the diagonal are ignored.
* Numeric values are ignored, so any explicit zeros are
* treated as nonzero.
* Output:
* Integer array of parents representing the etree, with n
* meaning a root of the elimination forest.
* Note:
* This routine uses only the upper triangle, while sparse
* Cholesky (as in spchol.c) uses only the lower. Matlab's
* dense Cholesky uses only the upper. This routine could
* be modified to use the lower triangle either by transposing
* the matrix or by traversing it by rows with auxiliary
* pointer and link arrays.
*
* John R. Gilbert, Xerox, 10 Dec 1990
* Based on code by JRG dated 1987, 1988, and 1990.
* Modified by X.S. Li, November 1999.
* </pre>
*/
int
sp_symetree_dist(
int_t *acolst, int_t *acolend, /* column starts and ends past 1 */
int_t *arow, /* row indices of A */
int_t n, /* dimension of A */
int_t *parent /* parent in elim tree */
)
{
int_t *root; /* root of subtee of etree */
int_t rset, cset;
int_t row, col;
int_t rroot;
int_t p;
int_t *pp;
#if ( DEBUGlevel>=1 )
CHECK_MALLOC(0, "Enter sp_symetree()");
#endif
root = mxCallocInt (n);
initialize_disjoint_sets (n, &pp);
for (col = 0; col < n; col++) {
cset = make_set (col, pp);
root[cset] = col;
parent[col] = n; /* Matlab */
for (p = acolst[col]; p < acolend[col]; p++) {
row = arow[p];
if (row >= col) continue;
rset = find (row, pp);
rroot = root[rset];
if (rroot != col) {
parent[rroot] = col;
cset = link (cset, rset, pp);
root[cset] = col;
}
}
}
SUPERLU_FREE (root);
finalize_disjoint_sets (pp);
#if ( DEBUGlevel>=1 )
CHECK_MALLOC(0, "Exit sp_symetree()");
#endif
return 0;
} /* SP_SYMETREE_DIST */
9 return A
// CPP CODE:
void kruskal() {
int i, u, v, cnt;
for (i = 0; i < cntNode; i++) make_set(i);
// sort the edge in increasing order.
qsort(edge, cntEdge, sizeof(Edge), cmp);
for (i = 0; i < cntEdge ; i++) {
int u = edge[i].u;
int v = edge[i].v;
if (find_set(u) != find_set(v)) {
union_set(u, v);
}
}
}
void lca(int u)
{
int i, j;
make_set(u);
ancestor[find_set(u)] = u;
for(i = 1;i <= n; i++)
{
if(tree[u][i] == 1)
{
lca(i);
union_set(u, i);
ancestor[find_set(u)] = u;
}
}
color[u] = 1;
for(i = 1;i <= n; i++)
if(q[u][i] && color[i] == 1) num[ancestor[find_set(i)]]++;
}
int main()
{
int m, i, j, s = 1;
while(1)
{
scanf("%d %d", &n, &m);
if(n == 0 && m == 0) break;
make_set(n);
while(m--)
{
scanf("%d %d", &i, &j);
union_set(i, j);
}
m = 0;
for(i = 1;i <= n; i++) if(find_set(i) == i) m++;
printf("Case %d: %d\n", s++, m);
}
return 0;
}
int numIslands(vector<vector<char>>& grid) {
int m = grid.size();
if (m == 0) return 0;
int n = grid[0].size();
if (n == 0) return 0;
make_set(id, m , n);
num_components = (grid[0][0] == '1');
// i == 0
for (int j = 1; j < n; j++) {
if (grid[0][j] == '0') continue;
num_components++;
if (grid[0][j - 1] == '1')
unions(to1d(0, j, n), to1d(0, j - 1, n));
}
// j == 0
for (int i = 1; i < m; i++) {
if (grid[i][0] == '0') continue;
num_components++;
if (grid[i - 1][0] == '1')
unions(to1d(i, 0, n), to1d(i - 1, 0, n));
}
//i != 0 && j != 0
for (int i = 1; i < m; i++) {
for (int j = 1; j < n; j++) {
if (grid[i][j] == '0') continue;
num_components++;
if (grid[i - 1][j] =='1') {
unions(to1d(i, j, n), to1d(i - 1, j, n));
}
if (grid[i][j - 1] == '1') {
unions(to1d(i, j, n), to1d(i, j - 1, n));
}
}
}
return num_components;
}
void connected_comp(){
int i=0;
for(;i<vertex_size;i++){
nodes[i] = make_set(&vertex[i]);
}
i=0;
/**jj for(;i<edge_size;i++){
char a=edge[i][0];
int ia = a-'a';
char b=edge[i][1];
int ib=b -'a';
struct set_node* nodea=nodes[ia];
struct set_node* nodeb=nodes[ib];
if(find_set(nodea)!=find_set(nodeb)){
unite_set(nodea,nodeb);
}
}*/
return ;
}
void mk_alternating(Node *p) /* generates an alternating automaton for p */
{
if(tl_stats) getrusage(RUSAGE_SELF, &tr_debut);
node_size = calculate_node_size(p) + 1; /* number of states in the automaton */
label = (Node **) tl_emalloc(node_size * sizeof(Node *));
transition = (ATrans **) tl_emalloc(node_size * sizeof(ATrans *));
node_size = node_size / (8 * sizeof(int)) + 1;
sym_size = calculate_sym_size(p); /* number of predicates */
if(sym_size) sym_table = (char **) tl_emalloc(sym_size * sizeof(char *));
sym_size = sym_size / (8 * sizeof(int)) + 1;
final_set = make_set(-1, 0);
transition[0] = boolean(p); /* generates the alternating automaton */
if(tl_verbose) {
fprintf(tl_out, "\nAlternating automaton before simplification\n");
print_alternating();
}
if(tl_simp_diff) {
simplify_astates(); /* keeps only accessible states */
if(tl_verbose) {
fprintf(tl_out, "\nAlternating automaton after simplification\n");
print_alternating();
}
}
#ifndef __MINGW__
if(tl_stats) {
getrusage(RUSAGE_SELF, &tr_fin);
timeval_subtract (&t_diff, &tr_fin.ru_utime, &tr_debut.ru_utime);
fprintf(tl_out, "\nBuilding and simplification of the alternating automaton: %i.%06is",
t_diff.tv_sec, t_diff.tv_usec);
fprintf(tl_out, "\n%i states, %i transitions\n", astate_count, atrans_count);
}
#endif
releasenode(1, p);
tfree(label);
}
Grafo* leArq(char *fileName) {
FILE *file = fopen( fileName, "r" );
if ( file == NULL ) {
printf( "Nao foi possivel ler o arquivo %s\n", fileName);
} else {
Grafo *grafo = (Grafo*) malloc(sizeof(Grafo));
int tamvert, tamarest;
fscanf(file, "%d %d", &tamvert, &tamarest);
grafo -> verticesQtd = tamvert;
grafo -> arestasQtd = tamarest;
grafo -> arestas = (Aresta **)malloc((sizeof(Aresta*) * tamarest)+1);
grafo->arestas[tamarest] = 0;
grafo->vertices = (Vertice **)malloc((sizeof(Vertice*) * tamvert)+1);
grafo->vertices[tamvert] = 0;
for(int i = 0; i < tamvert; i++)
{
Vertice *v = (Vertice*)malloc(sizeof(Vertice));
v->id = i;
make_set(v);
grafo->vertices[i] = v;
}
for(int i = 0; i< tamarest; i++)
{
int origem, destino, custo;
fscanf(file, "%d %d %d", &origem, &destino, &custo);
Aresta *aresta = (Aresta*) malloc(sizeof(Aresta));
aresta -> origem = grafo->vertices[origem];
aresta -> destino = grafo->vertices[destino];
aresta -> custo = custo;
grafo->arestas[i] = aresta;
}
fclose( file );
return grafo;
}
return NULL;
}
int main()
{
long i,j,sum,a,b,c,M;
char s1[1000],s2[1000],str[1000];
while(scanf("%ld %ld",&N,&M)==2&&(N||M))
{
getchar();
make_set();
for(i=0;i<N;i++)
gets(name[i]);
qsort(name,N,sizeof(name[0]),cmp);
for(i=0;i<M;i++)
{
gets(str);
sscanf(str,"%s %s %ld",s1,s2,&c);
a=binser(s1);
b=binser(s2);
P[i].u=a;P[i].v=b;P[i].cost=c;
}
gets(str);
qsort(P,M,sizeof(S),cmp1);
j=0;sum=0;
for(i=0;j<N-1&&i<M;i++)
{
a=find(P[i].u); b=find(P[i].v);
if(a!=b)
{
j++;
sum+=P[i].cost;
link(a,b);
}
}
if(j!=N-1)
printf("Impossible\n");
else
printf("%ld\n",sum);
}
return 0;
}
int main()
{
int graph[MAXSIZE][MAXSIZE];
struct node * hash_table[MAXSIZE] = {NULL};
int i;
int j;
int k;
int T;
int V;
int flag;
freopen("detect_cycle_graph_inp.txt", "r", stdin);
scanf("%d", &T);
for (i = 0; i < T; i++) {
scanf("%d", &V);
for (j = 1; j <= V; j++) {
make_set(hash_table, j);
for (k = 1; k <= V; k++) {
scanf("%d", &graph[j][k]);
}
}
flag = detect_cycle(graph, V, hash_table);
if (flag == 1) {
printf("Yes\n");
} else {
printf("No\n");
}
}
fclose(stdin);
return 0;
}
int Kruskal(Graph *g)
{
int steps = 0;
unsigned int Parent[VERTICES];
unsigned int Rank[VERTICES];
unsigned int r1,r2;
Knode edge;
//Step1: Heapsort make heap is already called
// in main loop.
steps=+Heapsort(&(g->node_list));
//do makeset
for(unsigned int v=0;v<VERTICES;v++)
{
make_set(Parent,Rank,v);
steps++;
}
//perform the main algo
for(unsigned int i=0;i<g->EDGES;i++)
{
//greedily pick the next edge
edge = g->node_list[i];
//find operation
r1 = Find(Parent,edge.u,&steps);
r2 = Find(Parent,edge.v,&steps);
// cout<<edge.u<<" e "<<edge.v<<" "<<edge.weight<<" "<<r1<<" "<<r2<<endl;
if(r1!=r2)
{
//Union those two edges
Union(Parent,Rank,r1,r2);
//Mark those edges in_tree status
IN_MST[edge.v][edge.u]=true;
IN_MST[edge.u][edge.v]=true;
}
//just discard it.
steps++;
}
return steps;
}
void MST_kruskal(int G[][20],int no_of_nodes,int mst[][20])
{
int i,j;
int u,v;
for(i=0;i<no_of_nodes;i++)
for(j=0;j<no_of_nodes;j++)
mst[i][j]=0;
for(i=0;i<no_of_nodes;i++)make_set(i);
get_sorted_edge_list(G,no_of_nodes);
for(i=0;i<edge_list_size;i++)
{
u=edge_list[i][0];
v=edge_list[i][1];
if(find_set(u)!=find_set(v))
{
mst[u][v]=mst[v][u]=edge_list[i][2];
unite(u,v);
}
}
}
int main()
{
long i,a,b,c,kase,kas=1;
scanf("%ld",&kase);
while(kase--)
{
scanf("%ld %ld %ld",&N,&M,&A);
make_set();
for(i=0;i<M;i++)
{
scanf("%ld %ld %ld",&a,&b,&c);
gr[i].x=a;gr[i].y=b;gr[i].w=c;
}
qsort(gr,M,sizeof(graph),cmp);
b=kruskal();
a=0;
for(i=1;i<=N;i++)
if(i==par[i])
a++;
printf("Case #%ld: %ld %ld\n",kas++,b+a*A,a);
}
return 0;
}
void simplify_astates() /* simplifies the alternating automaton */
{
ATrans *t;
int i, *acc = make_set(-1, 0); /* no state is accessible initially */
for(t = transition[0]; t; t = t->nxt, i = 0)
merge_sets(acc, t->to, 0); /* all initial states are accessible */
for(i = node_id - 1; i > 0; i--) {
if (!in_set(acc, i)) { /* frees unaccessible states */
label[i] = ZN;
free_atrans(transition[i], 1);
transition[i] = (ATrans *)0;
continue;
}
astate_count++;
simplify_atrans(&transition[i]);
for(t = transition[i]; t; t = t->nxt)
merge_sets(acc, t->to, 0);
}
tfree(acc);
}
void
init()
{
int i, j, tmp;
m = 0;
for(i=1; i<=n; i++)
for(j=1; j<=n; j++) {
scanf("%d", &tmp);
if(i<j && tmp) {
edges[m].from = i;
edges[m].to = j;
edges[m++].len = tmp;
}
}
qsort(edges, m, sizeof(struct Edge), compare);
make_set();
int q, f, t;
scanf("%d", &q);
for(i=0; i<q; i++) {
scanf("%d %d", &f, &t);
Union(f, t);
}
}
int main()
{
subset* sub = (subset*)malloc(10*sizeof(subset));
int i;
printf("I am here\n");
for(i=1;i<=10;i++){
make_set(sub,i);
}
for(i=1;i<=10;i++){
printf("%d %d\n",sub[i].parent,sub[i].rank);
}
make_union(sub,1,2);
make_union(sub,2,3);
make_union(sub,3,4);
for(i=1;i<=10;i++){
printf("%d %d\n",sub[i].parent,sub[i].rank);
}
for(i=1;i<=10;i++){
printf("Parent of %d is %d\n",i,find_set(sub,i));
}
return 0;
}
/*
* Symmetric elimination tree
*/
int
sp_symetree(
int *acolst, int *acolend, /* column starts and ends past 1 */
int *arow, /* row indices of A */
int n, /* dimension of A */
int *parent /* parent in elim tree */
)
{
int *root; /* root of subtree of etree */
int rset, cset;
int row, col;
int rroot;
int p;
root = mxCallocInt (n);
initialize_disjoint_sets (n);
for (col = 0; col < n; col++) {
cset = make_set (col);
root[cset] = col;
parent[col] = n; /* Matlab */
for (p = acolst[col]; p < acolend[col]; p++) {
row = arow[p];
if (row >= col) continue;
rset = find (row);
rroot = root[rset];
if (rroot != col) {
parent[rroot] = col;
cset = link (cset, rset);
root[cset] = col;
}
}
}
SUPERLU_FREE (root);
finalize_disjoint_sets ();
return 0;
} /* SP_SYMETREE */
int smo(bow_wv **docs, int *yvect, double *weights, double *a_b, double **W,
int ndocs, double *error, float *cvect, int *nsv) {
int changed;
int inspect_all;
struct svm_smo_model model;
int nchanged;
int num_words;
double *original_weights;
int i,j,k,n;
num_words = bow_num_words();
m1 = m2 = m3 = m4 = 0;
model.n_pair_suc = model.n_pair_tot = model.n_single_suc =
model.n_single_tot = model.n_outer = 0;
model.nsv = *nsv;
model.docs = docs;
model.error = error;
model.ndocs = ndocs;
model.cvect = cvect;
original_weights = NULL;
if (svm_kernel_type == 0 && !(*W)) {
*W = model.W = (double *) malloc(sizeof(double)*num_words);
} else {
model.W = NULL;
}
model.weights = weights;
model.yvect = yvect;
/* figure out the # of positives */
for (i=j=k=n=0; i<ndocs; i++) {
if (yvect[i] == 1) {
k = i;
j++;
} else {
n = i;
}
}
/* k is set to the last positive example found, n is the last negative */
make_set(ndocs,ndocs,&(model.I0));
make_set(ndocs,j,&(model.I1));
make_set(ndocs,ndocs-j,&(model.I2));
make_set(ndocs,j,&(model.I3));
make_set(ndocs,ndocs-j,&(model.I4));
/* this is the code which initializes the sets according to the weights values */
for (i=0; i<ndocs; i++) {
struct set *s;
if (weights[i] > svm_epsilon_a && weights[i] < cvect[i] - svm_epsilon_a) {
s = &(model.I0);
} else if (yvect[i] == 1) {
if (weights[i] < svm_epsilon_a) s = &(model.I1);
else s = &(model.I3);
} else {
if (weights[i] < svm_epsilon_a) s = &(model.I4);
else s = &(model.I2);
}
set_insert(i, s);
}
if (model.W) {
for (i=0; i<num_words; i++) {
model.W[i] = 0.0;
}
}
if (model.I0.ilength == 0) {
model.blow = 1;
model.bup = -1;
model.iup = k;
model.ilow = n;
error[k] = -1;
error[n] = 1;
} else { /* compute bup & blow */
int efrom, nitems;
int *items;
double e;
nitems = model.I0.ilength;
items = model.I0.items;
for (i=0, e=-1*MAXDOUBLE; i<nitems; i++) {
if (e < error[items[i]]) {
e = error[items[i]];
efrom = items[i];
}
}
model.blow = e;
model.ilow = efrom;
for (i=0, e=MAXDOUBLE; i<nitems; i++) {
if (e > error[items[i]]) {
e = error[items[i]];
efrom = items[i];
}
}
model.bup = e;
model.iup = efrom;
if (model.W) {
for (i=0; i<nitems; i++) {
for (j=0; j<docs[items[i]]->num_entries; j++) {
model.W[docs[items[i]]->entry[j].wi] +=
yvect[items[i]] * weights[items[i]] * docs[items[i]]->entry[j].weight;
}
}
/* also need to include bound sv's (I2 & I3) */
for (k=0, nitems=model.I2.ilength, items=model.I2.items;
k<2;
k++, nitems=model.I3.ilength, items=model.I3.items) {
for (i=0; i<nitems; i++) {
for (j=0; j<docs[items[i]]->num_entries; j++) {
model.W[docs[items[i]]->entry[j].wi] +=
yvect[items[i]] * weights[items[i]] * docs[items[i]]->entry[j].weight;
}
}
}
}
}
if (!model.W) {
model.W = *W;
}
if (svm_weight_style == WEIGHTS_PER_MODEL) {
kcache_init(ndocs);
}
inspect_all = 1;
nchanged = 0;
changed = 0;
while (nchanged || inspect_all) {
nchanged = 0;
#ifdef DEBUG
check_inv(&model,ndocs);
#endif
model.n_outer ++;
PRINT_SMO_PROGRESS(stderr, &model);
fflush(stderr);
if (1 && inspect_all) {
int ub = ndocs;
i=j=random() % ndocs;
for (k=0; k<2; k++,ub=j,i=0) {
for (; i<ub; i++) {
nchanged += opt_single(i, &model);
#ifdef DEBUG
check_inv(&model,ndocs);
#endif
}
}
inspect_all = 0;
} else {
/* greg's modification to keerthi, et al's modification 2 */
/* loop of optimizing all pairwise in a row with all elements
* in I0 (just like above, but only those in I0) */
do {
nchanged = 0;
/* here's the continuous iup/ilow loop */
while (1) {
if (!set_lookup(model.iup, &(model.I0))) {
error[model.iup] = smo_evaluate_error(&model,model.iup);
}
if (!set_lookup(model.ilow, &(model.I0))) {
error[model.ilow] = smo_evaluate_error(&model,model.ilow);
}
if (opt_pair(model.iup, model.ilow, &model)) {
#ifdef DEBUG
check_inv(&model,ndocs);
#endif
nchanged ++;
} else {
break;
}
if (model.bup > model.blow - 2*svm_epsilon_crit)
break;
}
if (nchanged) {
changed = 1;
}
nchanged = 0;
/* now inspect all of the elements in I0 */
{
int ub = ndocs;
i=j=random() % ndocs;
for (k=0; k<2; k++,ub=j,i=0) {
for (; i<ub; i++) {
if (set_lookup(i, &(model.I0))) {
nchanged += opt_single(i, &model);
#ifdef DEBUG
check_inv(&model,ndocs);
#endif
}
}
}
}
} while (nchanged);
/* of of the loop */
if (nchanged) {
changed = 1;
}
inspect_all = 1;
}
/* note: both of the above blocks no when they are done so they flip inspect_all */
if (nchanged) {
changed = 1;
}
}
free_set(&model.I0);
free_set(&model.I1);
free_set(&model.I2);
free_set(&model.I3);
free_set(&model.I4);
if (svm_weight_style == WEIGHTS_PER_MODEL) {
kcache_clear();
}
if (svm_verbosity > 3)
fprintf(stderr,"\n");
//printf("bup=%f, blow=%f\n",model.bup,model.blow);
*a_b = (model.bup + model.blow) / 2;
if (svm_kernel_type == 0) {
for (i=j=0; i<num_words; i++) {
if (model.W[i] != 0.0)
j++;
}
}
//printf("m1: %d, m2: %d, m3: %d, m4: %d", m1,m2,m3,m4);
*nsv = model.nsv;
return (changed);
}
/*! \brief Nonsymmetric elimination tree
*
* <pre>
* Find the elimination tree for A'*A.
* This uses something similar to Liu's algorithm.
* It runs in time O(nz(A)*log n) and does not form A'*A.
*
* Input:
* Sparse matrix A. Numeric values are ignored, so any
* explicit zeros are treated as nonzero.
* Output:
* Integer array of parents representing the elimination
* tree of the symbolic product A'*A. Each vertex is a
* column of A, and nc means a root of the elimination forest.
*
* John R. Gilbert, Xerox, 10 Dec 1990
* Based on code by JRG dated 1987, 1988, and 1990.
* </pre>
*/
int
sp_coletree_dist(
int_t *acolst, int_t *acolend, /* column start and end past 1 */
int_t *arow, /* row indices of A */
int_t nr, int_t nc, /* dimension of A */
int_t *parent /* parent in elim tree */
)
{
int_t *root; /* root of subtee of etree */
int_t *firstcol; /* first nonzero col in each row*/
int_t rset, cset;
int_t row, col;
int_t rroot;
int_t p;
int_t *pp;
#if ( DEBUGlevel>=1 )
int_t iam = 0;
CHECK_MALLOC(iam, "Enter sp_coletree()");
#endif
root = mxCallocInt (nc);
initialize_disjoint_sets (nc, &pp);
/* Compute firstcol[row] = first nonzero column in row */
firstcol = mxCallocInt (nr);
for (row = 0; row < nr; firstcol[row++] = nc);
for (col = 0; col < nc; col++)
for (p = acolst[col]; p < acolend[col]; p++) {
row = arow[p];
firstcol[row] = SUPERLU_MIN(firstcol[row], col);
}
/* Compute etree by Liu's algorithm for symmetric matrices,
except use (firstcol[r],c) in place of an edge (r,c) of A.
Thus each row clique in A'*A is replaced by a star
centered at its first vertex, which has the same fill. */
for (col = 0; col < nc; col++) {
cset = make_set (col, pp);
root[cset] = col;
parent[col] = nc; /* Matlab */
for (p = acolst[col]; p < acolend[col]; p++) {
row = firstcol[arow[p]];
if (row >= col) continue;
rset = find (row, pp);
rroot = root[rset];
if (rroot != col) {
parent[rroot] = col;
cset = link (cset, rset, pp);
root[cset] = col;
}
}
}
SUPERLU_FREE (root);
SUPERLU_FREE (firstcol);
finalize_disjoint_sets (pp);
#if ( DEBUGlevel>=1 )
CHECK_MALLOC(iam, "Exit sp_coletree()");
#endif
return 0;
} /* SP_COLETREE_DIST */
int main(int argc, char* argv[])
{
int a, b, max = -1, p1, p2, flag = 1, k = 0, i;
make_set();
while(scanf("%d%d", &a, &b), a != -1 || b != -1)
{
point[a] = true;
point[b] = true;
if(a > max)
{
max = a;
}
if(b > max)
{
max = b;
}
if(max == 0)
{
puts("Yes\n");
continue;
}
p1 = find(a);
p2 = find(b);
if(p1 != p2)
{
father[p1] = p2;
}
else
{
flag = 0;
}
while(scanf("%d%d", &a, &b), a != 0 || b != 0)
{
if(flag == 0)
{
puts("No\n");
break;
}
if(a > max)
{
max = a;
}
if(b > max)
{
max = b;
}
point[a] = true;
point[b] = true;
p1 = find(a);
p2 = find(b);
if(p1 != p2)
father[p1] = p2;
else
{
flag = 0;
continue;
}
}
for(i = 0; i < max; i++)
{
if(point[i])
{
if(father[i] == i)
k++;
}
}
if(k != 1)
flag = 0;
if(flag != 0)
{
puts("Yes\n");
}
else
{
puts("No\n");
}
make_set();
k = 0; flag = 1;
max = -1;
}
}
int main(int argc, char **argv)
#endif
{
int i, niter, step;
double mflops, t, tmax;
logical verified;
char class;
double tsum[t_last+2], t1[t_last+2],
tming[t_last+2], tmaxg[t_last+2];
char *t_recs[t_last+2] = {
"total", "rhs", "xsolve", "ysolve", "zsolve",
"bpack", "exch", "xcomm", "ycomm", "zcomm",
" totcomp", " totcomm" };
//---------------------------------------------------------------------
// Root node reads input file (if it exists) else takes
// defaults from parameters
//---------------------------------------------------------------------
printf("\n\n NAS Parallel Benchmarks (NPB3.3-OCL-MD) - SP Benchmark\n\n");
FILE *fp;
fp = fopen("timer.flag", "r");
timeron = false;
if (fp != NULL) {
timeron = true;
fclose(fp);
}
if ((fp = fopen("inputsp.data", "r")) != NULL) {
int result;
printf(" Reading from input file inputsp.data\n");
result = fscanf(fp, "%d", &niter);
while (fgetc(fp) != '\n');
result = fscanf(fp, "%*f");
while (fgetc(fp) != '\n');
result = fscanf(fp, "%d%d%d", &grid_points[0], &grid_points[1],
&grid_points[2]);
fclose(fp);
} else {
printf(" No input file inputsp.data. Using compiled defaults\n");
niter = NITER_DEFAULT;
grid_points[0] = PROBLEM_SIZE;
grid_points[1] = PROBLEM_SIZE;
grid_points[2] = PROBLEM_SIZE;
}
setup_opencl(argc, argv);
printf(" Size: %4dx%4dx%4d\n",
grid_points[0], grid_points[1], grid_points[2]);
printf(" Iterations: %4d", niter);
if (num_devices != MAXCELLS*MAXCELLS)
printf(" WARNING: compiled for %5d devices \n", MAXCELLS*MAXCELLS);
printf(" Number of active devices: %5d\n\n", num_devices);
make_set();
for (i = 0; i < t_last; i++) {
timer_clear(i);
}
set_constants();
initialize();
lhsinit();
exact_rhs();
compute_buffer_size(5);
set_kernel_args();
//---------------------------------------------------------------------
// do one time step to touch all code, and reinitialize
//---------------------------------------------------------------------
#ifdef MINIMD_SNUCL_OPTIMIZATIONS
// set cmd queue property
for(i = 0; i < num_devices; i++) {
clSetCommandQueueProperty(cmd_queue[i],
CL_QUEUE_AUTO_DEVICE_SELECTION |
//CL_QUEUE_ITERATIVE |
CL_QUEUE_COMPUTE_INTENSIVE,
true,
NULL);
}
#endif
adi();
#ifdef MINIMD_SNUCL_OPTIMIZATIONS
for(i = 0; i < num_devices; i++) {
clSetCommandQueueProperty(cmd_queue[i],
0,
true,
NULL);
}
#endif
initialize();
//---------------------------------------------------------------------
// Synchronize before placing time stamp
//---------------------------------------------------------------------
for (i = 0; i < t_last; i++) {
timer_clear(i);
}
timer_clear(0);
timer_start(0);
for (step = 1; step <= niter; step++) {
if ((step % 20) == 0 || step == 1) {
printf(" Time step %4d\n", step);
}
adi();
}
timer_stop(0);
t = timer_read(0);
verify(niter, &class, &verified);
tmax = t;
if( tmax != 0.0 ) {
mflops = (881.174*(double)( PROBLEM_SIZE*PROBLEM_SIZE*PROBLEM_SIZE )
-4683.91*(double)( PROBLEM_SIZE*PROBLEM_SIZE )
+11484.5*(double)( PROBLEM_SIZE )
-19272.4) * (double)( niter ) / (tmax*1000000.0);
} else {
mflops = 0.0;
}
c_print_results("SP", class, grid_points[0],
grid_points[1], grid_points[2], niter,
tmax, mflops, " floating point",
verified, NPBVERSION,COMPILETIME, CS1, CS2, CS3, CS4, CS5,
CS6, CS7, clu_GetDeviceTypeName(device_type), device_name, num_devices);
if (timeron) {
/*
for (i = 0; i < t_last; i++) {
t1[i] = timer_read(i);
}
t1[t_xsolve] = t1[t_xsolve] - t1[t_xcomm];
t1[t_ysolve] = t1[t_ysolve] - t1[t_ycomm];
t1[t_zsolve] = t1[t_zsolve] - t1[t_zcomm];
t1[t_last+2] = t1[t_xcomm]+t1[t_ycomm]+t1[t_zcomm]+t1[t_exch];
t1[t_last+1] = t1[t_total] - t1[t_last+2];
MPI_Reduce(&t1, tsum, t_last+2, dp_type, MPI_SUM, 0, comm_setup);
MPI_Reduce(&t1, tming, t_last+2, dp_type, MPI_MIN, 0, comm_setup);
MPI_Reduce(&t1, tmaxg, t_last+2, dp_type, MPI_MAX, 0, comm_setup);
if (node == 0) {
printf(" nprocs =%6d minimum maximum average\n",
total_nodes);
for (i = 0; i < t_last+2; i++) {
tsum[i] = tsum[i] / total_nodes;
printf(" timer %2d(%8s) : %10.4f %10.4f %10.4f\n",
i+1, t_recs[i], tming[i], tmaxg[i], tsum[i]);
}
}
*/
}
release_opencl();
return 0;
}
// resolves collisions between bodies, returning new body count
int collide(int n, body bodies[]) {
// initialize disjoint set and bodies to include
set* bsets[n];
int include[n];
for (int i = 0; i < n; i++) {
bsets[i] = make_set(i);
include[i] = 1;
}
// find largest object
double maxrad = RADIUS(bodies[0].m);
for (int i = 0; i < n; i++) {
double rad = RADIUS(bodies[i].m);
if (rad > maxrad)
maxrad = rad;
}
// form mesh for collision detection
mesh* m = mesh_new(maxrad * 2);
for (int i = 0; i < n; i++)
mesh_put(m, bodies[i].pos, i);
// find collisions
for (int i = 0; i < n; i++) {
vector ipos = bodies[i].pos;
double irad = RADIUS(bodies[i].m);
// which bodies are in contact with this one?
// look up position in mesh
body_list* next = mesh_get(m, ipos, 1);
for (body_list* cur = next; cur; cur = next) {
// get candidate collider
int j = cur->index;
vector jpos = bodies[j].pos;
double jrad = RADIUS(bodies[j].m);
// merge sets of colliding objects
if (dist(ipos, jpos) < (irad + jrad) * (irad + jrad))
merge(bsets[i], bsets[j]);
// traverse and free
next = cur->next;
free(cur);
}
}
// free the mesh
mesh_free(m);
// merge objects
for (int i = 0; i < n; i++) {
int rootidx = get_value(find(bsets[i]));
if (rootidx != i) {
include[i] = 0;
bodies[rootidx] = body_merge(bodies[rootidx], bodies[i]);
}
}
// free sets
for (int i = 0; i < n; i++)
free(bsets[i]);
// copy down
int j = 0;
for (int i = 0; i < n; i++) {
if (include[i])
bodies[j++] = bodies[i];
}
return j;
}
double kruskal(struct Graph *graph, int source_vertex, int target_vertex) {
PRINT_TEXT("_________________________________________________");
PRINT_TEXT("...STARTING KRUSKAL...");
clock_t start = clock();
double cpu_time;
int **adjacency_matrix = allocate_2D_matrix(MAX_VERTICES, MAX_VERTICES);
int i, count = 0;
struct Edge_Heap *heap = create_edge_heap();
struct Node *node, *node2;
for (i = 0; i < graph->totalVertices; i++) {
node = graph->list[i].next;
while (node) {
/*Used to avoid the duplicate addition of edges in the heap*/
if (adjacency_matrix[i][node->vertex] == 0) {
adjacency_matrix[i][node->vertex] = 1;
adjacency_matrix[node->vertex][i] = -1;
insert_edge_heap(heap, i, node->vertex, node->weight);
count++;
}
node = node->next;
}
}
int size = heap->curr_size;
heapsort(heap);
// PRINT_TEXT("HEAP INSERTIONS DONE");
// PRINT_TEXT_VALUE("TOTAL:", count);
struct Graph *new_graph = construct_graph();
struct Set_Arrays *set_data = make_set();
count = 0;
i = heap->curr_size - 1;
while (i >= 0) {
struct Edge *edge = &heap->A[i--];
// while (is_edge_heap_empty(heap) != TRUE) {
// struct Edge *edge = get_max(heap);
// printf("Considering: %d %d %d\n", edge->vertex1, edge->vertex2,
// edge->weight);
// PRINT_VALUES(set_data->dad[edge->vertex1], set_data->dad[edge->vertex2])
if (union_by_rank(set_data, edge->vertex1, edge->vertex2)) {
count++;
link_creation_with_weight(new_graph, edge->vertex1, edge->vertex2,
edge->weight);
link_creation_with_weight(new_graph, edge->vertex2, edge->vertex1,
edge->weight);
// PRINT_TEXT("ADDED");
}
// for (i = 0; i < MAX_VERTICES; i++) {
// PRINT_VALUE(set_data->dad[i])
// }
}
// PRINT_TEXT_VALUE("TOTAL EDGES ADDED:", count);
/*Not including max capacity finding using BFS in calculation*/
cpu_time = ((double) (clock() - start)) / CLOCKS_PER_SEC;
// printGraph(new_graph);
print_max_capacity_path_krukskal(new_graph, source_vertex, target_vertex);
printf("KRUSKAL DONE, TIME TAKEN: %f\n", cpu_time);
PRINT_TEXT("_________________________________________________");
for (i = 0; i < MAX_VERTICES; i++)
free(adjacency_matrix[i]);
free(adjacency_matrix);
return cpu_time;
}
