diff options
author | Joshua Bakita <jbakita@cs.unc.edu> | 2020-10-16 16:55:14 -0400 |
---|---|---|
committer | Joshua Bakita <jbakita@cs.unc.edu> | 2020-10-16 16:55:14 -0400 |
commit | 6ea9939e0610a809f6f47d13ec68df00d1ca0afc (patch) | |
tree | fe4a2eee3ddcf77e2367309dcd75a232b76dcd62 /dis/Matrix/ver2 | |
parent | e9285d0cdea756a2830f0ace378e4197b36869aa (diff) |
Move the DIS benchmarks up a directory and update hardcoded paths
Note that this repo does not attempt to keep a copy of the original
DIS benchmark distributions. UNC real-time has another repo for that.
Diffstat (limited to 'dis/Matrix/ver2')
-rwxr-xr-x | dis/Matrix/ver2/DISstressmarkRNG.h | 190 | ||||
-rwxr-xr-x | dis/Matrix/ver2/matrix.c | 594 |
2 files changed, 784 insertions, 0 deletions
diff --git a/dis/Matrix/ver2/DISstressmarkRNG.h b/dis/Matrix/ver2/DISstressmarkRNG.h new file mode 100755 index 0000000..4aa2620 --- /dev/null +++ b/dis/Matrix/ver2/DISstressmarkRNG.h | |||
@@ -0,0 +1,190 @@ | |||
1 | #include <math.h> | ||
2 | |||
3 | #define IA 16807 | ||
4 | #define IM 2147483647 | ||
5 | #define AM (1.0/IM) | ||
6 | #define IQ 127773 | ||
7 | #define IR 2836 | ||
8 | #define NTAB 32 | ||
9 | #define NDIV (1+(IM-1)/NTAB) | ||
10 | #define EPS 1.2e-7 | ||
11 | #define RNMX (1.0-EPS) | ||
12 | |||
13 | static long iy=0; | ||
14 | static long iv[NTAB]; | ||
15 | static long iseed; | ||
16 | |||
17 | int ABS(int x){ | ||
18 | if (x>= 0) return x; | ||
19 | else | ||
20 | return (-x); | ||
21 | } | ||
22 | |||
23 | int sign(int x){ | ||
24 | if (x >= 0) return 1; | ||
25 | else | ||
26 | return (-1); | ||
27 | } | ||
28 | |||
29 | int MAX(int x, int y){ | ||
30 | if (x>= y) return x; | ||
31 | else | ||
32 | return y; | ||
33 | } | ||
34 | |||
35 | int MIN(int x, int y){ | ||
36 | if (x<= y) return x; | ||
37 | else | ||
38 | return y; | ||
39 | } | ||
40 | |||
41 | void randInit(long idum) | ||
42 | { | ||
43 | long j; | ||
44 | long k; | ||
45 | |||
46 | assert (idum <= 0); | ||
47 | assert (iy == 0); | ||
48 | |||
49 | iseed = idum; | ||
50 | if (-(iseed)<1){ | ||
51 | iseed = 1; | ||
52 | } | ||
53 | else { | ||
54 | iseed = -(iseed); | ||
55 | } | ||
56 | for (j=NTAB+7; j>=0; j--){ | ||
57 | k = (iseed)/IQ; | ||
58 | iseed = IA*(iseed-k*IQ)-IR*k; | ||
59 | if (iseed < 0){ | ||
60 | iseed += IM; | ||
61 | } | ||
62 | if (j < NTAB){ | ||
63 | iv[j] = iseed; | ||
64 | } | ||
65 | } | ||
66 | iy = iv[0]; | ||
67 | } | ||
68 | |||
69 | float randNum() | ||
70 | { | ||
71 | long j; | ||
72 | long k; | ||
73 | float temp; | ||
74 | |||
75 | assert (iy != 0); | ||
76 | |||
77 | k = (iseed)/IQ; | ||
78 | iseed = IA*(iseed-k*IQ)-IR*k; | ||
79 | |||
80 | if (iseed < 0){ | ||
81 | iseed += IM; | ||
82 | } | ||
83 | j = iy/NDIV; | ||
84 | iy = iv[j]; | ||
85 | iv[j] = iseed; | ||
86 | |||
87 | temp = AM * iy; | ||
88 | |||
89 | if (temp > RNMX){ | ||
90 | return RNMX; | ||
91 | } | ||
92 | else { | ||
93 | return temp; | ||
94 | } | ||
95 | } | ||
96 | |||
97 | |||
98 | float randomFloat(float lowest_float, float highest_float) | ||
99 | { | ||
100 | float value; | ||
101 | float range; | ||
102 | |||
103 | assert (lowest_float < highest_float); | ||
104 | |||
105 | range = highest_float - lowest_float; | ||
106 | value = randNum()*(highest_float - lowest_float) + lowest_float; | ||
107 | assert(value >= lowest_float); | ||
108 | assert(value <= highest_float); | ||
109 | |||
110 | return value; | ||
111 | |||
112 | } | ||
113 | |||
114 | float randomNonZeroFloat(float lowest_float, float highest_float, float epsilon) | ||
115 | { | ||
116 | |||
117 | double range; | ||
118 | float value; | ||
119 | |||
120 | |||
121 | assert (lowest_float < 0); | ||
122 | assert (highest_float > 0); | ||
123 | assert (epsilon > 0); | ||
124 | assert ((epsilon < -lowest_float) && (epsilon < highest_float)); | ||
125 | |||
126 | range = highest_float - lowest_float; | ||
127 | value = (randNum() * range)+lowest_float; | ||
128 | |||
129 | if (ABS(value) < epsilon) | ||
130 | { | ||
131 | if (value > 0) value = value + epsilon; | ||
132 | else if (value < 0) value = value - epsilon; | ||
133 | |||
134 | } | ||
135 | |||
136 | assert (value >= lowest_float); | ||
137 | assert (value <= highest_float); | ||
138 | |||
139 | return value; | ||
140 | } | ||
141 | |||
142 | unsigned int randomUInt(int lowest_uint, int highest_uint) | ||
143 | { | ||
144 | float range; | ||
145 | unsigned int value; | ||
146 | float temp; | ||
147 | |||
148 | range =(float)(highest_uint - lowest_uint + 1); | ||
149 | temp = randNum(); | ||
150 | value =(unsigned int)( floor(temp * range) + lowest_uint); | ||
151 | |||
152 | assert (value >= lowest_uint); | ||
153 | assert (value <= highest_uint); | ||
154 | |||
155 | return value; | ||
156 | } | ||
157 | |||
158 | unsigned int randomNonZeroUInt(int lowest_uint, int highest_uint) | ||
159 | { | ||
160 | float range; | ||
161 | unsigned int value; | ||
162 | float temp; | ||
163 | |||
164 | range =(float)(highest_uint - lowest_uint + 1); | ||
165 | value = 0; | ||
166 | while(value == 0){ | ||
167 | temp = randNum(); | ||
168 | |||
169 | value =(unsigned int)( floor(temp * range) + lowest_uint); | ||
170 | } | ||
171 | |||
172 | assert (value >= lowest_uint); | ||
173 | assert (value <= highest_uint); | ||
174 | |||
175 | return value; | ||
176 | } | ||
177 | |||
178 | int randInt(int lowest_uint, int highest_uint) | ||
179 | { | ||
180 | float range; | ||
181 | int value; | ||
182 | |||
183 | range = highest_uint - lowest_uint + 1; | ||
184 | value = (int)(floor(randNum() * range) + lowest_uint); | ||
185 | |||
186 | assert (value >= lowest_uint); | ||
187 | assert (value <= highest_uint); | ||
188 | |||
189 | return value; | ||
190 | } | ||
diff --git a/dis/Matrix/ver2/matrix.c b/dis/Matrix/ver2/matrix.c new file mode 100755 index 0000000..957d7c5 --- /dev/null +++ b/dis/Matrix/ver2/matrix.c | |||
@@ -0,0 +1,594 @@ | |||
1 | /* Please note: | ||
2 | * This code is the optimized version of the first version of Matrix | ||
3 | * Stressmark. It uses less temporary vectors and vsariables, thus reduce | ||
4 | * memory allocation/deallocation overhead. the simulation is faster | ||
5 | */ | ||
6 | /* | ||
7 | * Sample code for the DIS Matrix Stressmark | ||
8 | * | ||
9 | * This source code is the completely correct source code based on | ||
10 | * the example codes provided by Atlantic Aerospace Division, Titan | ||
11 | * Systems Corporation, 2000. | ||
12 | * | ||
13 | * If you just compile and generate the executables from this source | ||
14 | * code, this code would be enough. However, if you wish to get a complete | ||
15 | * understanding of this stressmark, it is strongly suggested that you | ||
16 | * read the Benchmark Analysis and Specifications Document Version 1.0 | ||
17 | * before going on since the detailed comments are given in this documents. | ||
18 | * the comments are not repeated here. | ||
19 | */ | ||
20 | |||
21 | /* | ||
22 | * The Sparse Matrix Storage is implemented by Compact Row Storage Scheme | ||
23 | * In the code, the data is first generated by randomNonzeroFloat() | ||
24 | * the data is first stored in a full-space matrix with size of dim*dim | ||
25 | * then the data is transfered to the Compact Row Matrix, | ||
26 | * the data value is kept in *value, | ||
27 | * the columns corresponding to the value are stored in *col_ind, | ||
28 | * the start element of each row is stored in *row_start. | ||
29 | */ | ||
30 | |||
31 | /* | ||
32 | * Please note: | ||
33 | * the total number of data is numberNonzero +dim | ||
34 | * among which, NumberNonzero because this is symmetric matrix | ||
35 | * dim because the diagonal elements | ||
36 | */ | ||
37 | |||
38 | #include <stdio.h> | ||
39 | #include <math.h> | ||
40 | #include <stdlib.h> | ||
41 | #include <time.h> | ||
42 | #include <assert.h> | ||
43 | #include "DISstressmarkRNG.h" | ||
44 | #include "extra.h" | ||
45 | |||
46 | #define MIN_SEED -2147483647 | ||
47 | #define MAX_SEED -1 | ||
48 | #define MIN_DIM 1 | ||
49 | #define MAX_DIM 32768 | ||
50 | #define MAX_ITERATIONS 65536 | ||
51 | #define MIN_TOLERANCE 0.000007 | ||
52 | #define MAX_TOLERANCE 0.5 | ||
53 | #define MIN_NUMBER -3.4e10/dim | ||
54 | #define MAX_NUMBER 3.4e10/dim | ||
55 | #define EPSI 1.0e-10 | ||
56 | #define MIN_DIG_NUMBER 1.0e-10 | ||
57 | #define MAX_DIG_NUMBER 3.4e10 | ||
58 | |||
59 | /* | ||
60 | * External variable, dimension | ||
61 | */ | ||
62 | |||
63 | static int dim; | ||
64 | int argc; | ||
65 | char** argv; | ||
66 | |||
67 | /* | ||
68 | * matrix * vector | ||
69 | */ | ||
70 | |||
71 | void matrixMulvector(double *value, | ||
72 | int *col_ind, | ||
73 | int *row_start, | ||
74 | double *vector, | ||
75 | double *out) | ||
76 | { | ||
77 | int l, ll; | ||
78 | double sum; | ||
79 | int tmp_rs, tmp_re; | ||
80 | |||
81 | for (l=0; l<dim; l++){ | ||
82 | *(out + l) = 0; | ||
83 | tmp_rs = row_start[l]; | ||
84 | |||
85 | if (tmp_rs != -1){ | ||
86 | tmp_re = row_start[l+1]; /* | ||
87 | *get the start and ending elements of | ||
88 | * each row | ||
89 | */ | ||
90 | for (ll=tmp_rs; ll<tmp_re; ll++){ | ||
91 | *(out + l) += value[ll]*vector[col_ind[ll]]; | ||
92 | } | ||
93 | } | ||
94 | } | ||
95 | return; | ||
96 | } | ||
97 | |||
98 | |||
99 | /* | ||
100 | * vector1 - vector2 | ||
101 | */ | ||
102 | |||
103 | void vectorSub(double *vector1, double *vector2, double *vector){ | ||
104 | |||
105 | int l; | ||
106 | |||
107 | for (l=0; l<dim; l++){ | ||
108 | *(vector + l) = *(vector1 + l) - *(vector2 + l); | ||
109 | } | ||
110 | return; | ||
111 | } | ||
112 | |||
113 | |||
114 | /* | ||
115 | * vector1 + vector2 | ||
116 | */ | ||
117 | |||
118 | void vectorAdd(double *vector1, double *vector2, double *vector){ | ||
119 | |||
120 | int l; | ||
121 | |||
122 | for (l=0; l<dim; l++){ | ||
123 | *(vector + l) = *(vector1 + l) + *(vector2 + l); | ||
124 | } | ||
125 | return; | ||
126 | } | ||
127 | |||
128 | /* | ||
129 | * vector1 * vector2 | ||
130 | */ | ||
131 | |||
132 | double vectorMul(double *vector1, double *vector2){ | ||
133 | |||
134 | int l; | ||
135 | double product; | ||
136 | |||
137 | product = 0; | ||
138 | |||
139 | for (l=0; l<dim; l++){ | ||
140 | product += (*(vector1 + l))*(*(vector2 + l)); | ||
141 | |||
142 | } | ||
143 | return product; | ||
144 | } | ||
145 | |||
146 | /* | ||
147 | * /vector/ | ||
148 | */ | ||
149 | |||
150 | double vectorValue(double *vector){ | ||
151 | |||
152 | double value; | ||
153 | int l; | ||
154 | |||
155 | value = 0; | ||
156 | |||
157 | for (l=0; l<dim; l++){ | ||
158 | value += (*(vector + l)) * (*(vector + l)); | ||
159 | } | ||
160 | |||
161 | return (sqrt(value)); | ||
162 | } | ||
163 | |||
164 | /* | ||
165 | * transpose(vector) | ||
166 | * In fact, we return the original vector here | ||
167 | */ | ||
168 | |||
169 | void transpose(double *vector, double *vect){ | ||
170 | |||
171 | int l; | ||
172 | |||
173 | for (l=0; l<dim; l++){ | ||
174 | *(vect+l) = *(vector+l); | ||
175 | } | ||
176 | return; | ||
177 | } | ||
178 | |||
179 | /* | ||
180 | * value * <vector> | ||
181 | */ | ||
182 | void valueMulvector(double value, double *vector, double *vect){ | ||
183 | |||
184 | int l; | ||
185 | int lll, i; | ||
186 | double tmp; | ||
187 | |||
188 | for (l=0; l<dim; l++){ | ||
189 | *(vect + l) = *(vector + l) * value; | ||
190 | } | ||
191 | return; | ||
192 | } | ||
193 | |||
194 | /* | ||
195 | * generate the data distributed sparsely in matrix | ||
196 | */ | ||
197 | |||
198 | void initMatrix(double *matrix, int dim, int numberNonzero){ | ||
199 | |||
200 | int k, l, ll; | ||
201 | int i, j; | ||
202 | |||
203 | int lll; | ||
204 | double sum; | ||
205 | |||
206 | for (k=0; k< dim*dim; k++){ | ||
207 | *(matrix + k) = 0; | ||
208 | } | ||
209 | |||
210 | for (l=0; l<numberNonzero/2; l++){ | ||
211 | |||
212 | i = randomUInt(1, dim-1); | ||
213 | j = randomUInt(0, i-1); | ||
214 | |||
215 | while (*(matrix + i*dim + j) != 0){ | ||
216 | |||
217 | i++; | ||
218 | if (i == dim){ | ||
219 | j++; | ||
220 | if (j == dim-1){ | ||
221 | j = 0; | ||
222 | i = 1; | ||
223 | } | ||
224 | else{ | ||
225 | i = j+1; | ||
226 | } | ||
227 | } | ||
228 | } | ||
229 | |||
230 | if (*(matrix + i*dim + j) == 0){ | ||
231 | *(matrix + i*dim + j) = (double )randomNonZeroFloat(MIN_NUMBER, | ||
232 | MAX_NUMBER, | ||
233 | EPSI); | ||
234 | *(matrix + j*dim + i) = *(matrix + i*dim + j); | ||
235 | } | ||
236 | } | ||
237 | |||
238 | for (ll=0; ll<dim; ll++){ | ||
239 | |||
240 | |||
241 | |||
242 | *(matrix + ll*dim + ll) = (double )randomNonZeroFloat(-MAX_DIG_NUMBER, | ||
243 | MAX_DIG_NUMBER, | ||
244 | MIN_DIG_NUMBER); | ||
245 | |||
246 | sum = 0; | ||
247 | |||
248 | for (lll=0; lll<dim; lll++){ | ||
249 | if (lll != ll){ | ||
250 | sum += *(matrix + lll*dim + ll); | ||
251 | } | ||
252 | } | ||
253 | |||
254 | if (*(matrix + ll*dim + ll) < sum ){ | ||
255 | *(matrix + ll*dim + ll) += sum; | ||
256 | } | ||
257 | } | ||
258 | |||
259 | return; | ||
260 | } | ||
261 | |||
262 | /* | ||
263 | * generate the data value in the vectors | ||
264 | */ | ||
265 | |||
266 | void initVector(double *vector, int dim){ | ||
267 | |||
268 | int l; | ||
269 | |||
270 | for (l=0; l<dim; l++){ | ||
271 | *(vector + l) = (double )randomFloat (MIN_NUMBER, MAX_NUMBER); | ||
272 | } | ||
273 | |||
274 | return; | ||
275 | } | ||
276 | |||
277 | /* | ||
278 | * make a vector contains value of zero | ||
279 | */ | ||
280 | |||
281 | void zeroVector(double *vector, int dim){ | ||
282 | int l; | ||
283 | |||
284 | for (l=0; l<dim; l++){ | ||
285 | *(vector + l) = 0; | ||
286 | } | ||
287 | return; | ||
288 | } | ||
289 | |||
290 | /* | ||
291 | * return a vector which is the copy of the vect | ||
292 | */ | ||
293 | |||
294 | void equalVector(double *vect, double *vect1){ | ||
295 | |||
296 | int l; | ||
297 | |||
298 | for (l=0; l<dim; l++){ | ||
299 | *(vect1+l) = *(vect+l); | ||
300 | } | ||
301 | return; | ||
302 | } | ||
303 | |||
304 | |||
305 | |||
306 | void biConjugateGradient(double *value, | ||
307 | int *col_ind, | ||
308 | int *row_start, | ||
309 | double *vectorB, | ||
310 | double *vectorX, | ||
311 | double errorTolerance, | ||
312 | int maxIterations, | ||
313 | double *actualError, | ||
314 | int *actualIteration, | ||
315 | int dim) | ||
316 | /* | ||
317 | * in the code, we use a lot of temparary vectors and variables | ||
318 | * this is just for simple and clear | ||
319 | * you can optimize these temporary variables and vectors | ||
320 | * based on your need | ||
321 | * | ||
322 | */ | ||
323 | { | ||
324 | double *vectorR; | ||
325 | double *vectorP, *matrixAvectorP, *nextVectorR; | ||
326 | double error; | ||
327 | int iteration; | ||
328 | double alpha, beta; | ||
329 | |||
330 | double *tmpVector1, *tmpVector2, *tmpVector3; | ||
331 | double tmpValue1, tmpValue2; | ||
332 | int i; | ||
333 | int l; | ||
334 | int ll; | ||
335 | SET_UP | ||
336 | |||
337 | alpha = 0; | ||
338 | beta = 0; | ||
339 | |||
340 | vectorP = (double *)malloc(dim*sizeof(double)); | ||
341 | vectorR = (double *)malloc(dim*sizeof(double)); | ||
342 | nextVectorR = (double *)malloc(dim*sizeof(double)); | ||
343 | vectorX = (double *)malloc(dim*sizeof(double)); | ||
344 | |||
345 | tmpVector1 = (double *)malloc(dim*sizeof(double)); | ||
346 | tmpVector2 = (double *)malloc(dim*sizeof(double)); | ||
347 | tmpVector3 = (double *)malloc(dim*sizeof(double)); | ||
348 | |||
349 | /* | ||
350 | * vectorR = vectorB - matrixA*vectorX | ||
351 | */ | ||
352 | matrixMulvector(value,col_ind, row_start, vectorX, tmpVector1); | ||
353 | |||
354 | vectorSub(vectorB, tmpVector1, vectorR); | ||
355 | |||
356 | /* | ||
357 | * vectorP = vectorR | ||
358 | */ | ||
359 | |||
360 | equalVector(vectorR, vectorP); | ||
361 | |||
362 | /* | ||
363 | * error = |matrixA * vectorX - vectorB| / |vectorB| | ||
364 | */ | ||
365 | vectorSub(tmpVector1, vectorB, tmpVector1); | ||
366 | |||
367 | error = vectorValue(tmpVector1)/vectorValue(vectorB); | ||
368 | |||
369 | iteration = 0; | ||
370 | |||
371 | while ((iteration < maxIterations) && (error > errorTolerance)){ | ||
372 | START_LOOP | ||
373 | |||
374 | /* | ||
375 | * alpha = (transpose(vectorR) * vectorR) / | ||
376 | * (transpose(vectorP) * (matrixA * vectorP) | ||
377 | */ | ||
378 | |||
379 | matrixMulvector(value, col_ind, row_start, vectorP, tmpVector1); | ||
380 | transpose(vectorR, tmpVector2); | ||
381 | transpose(vectorP, tmpVector3); | ||
382 | tmpValue1 = vectorMul(tmpVector3, tmpVector1); | ||
383 | tmpValue2 = vectorMul(tmpVector2, vectorR); | ||
384 | alpha = tmpValue2/tmpValue1; | ||
385 | |||
386 | /* | ||
387 | * nextVectorR = vectorR - alpha*(matrixA * vectorP) | ||
388 | */ | ||
389 | |||
390 | valueMulvector(alpha, tmpVector1, tmpVector2); | ||
391 | vectorSub(vectorR, tmpVector2, tmpVector1); | ||
392 | equalVector(tmpVector1, nextVectorR); | ||
393 | |||
394 | /* | ||
395 | * beta = (transpose(nextVectorR) * nextVectorR) / | ||
396 | * (transpose(vectorR) * vectorR) | ||
397 | */ | ||
398 | |||
399 | transpose(nextVectorR, tmpVector3); | ||
400 | tmpValue1 = vectorMul(tmpVector3, nextVectorR); | ||
401 | transpose(vectorR, tmpVector2); | ||
402 | tmpValue2 = vectorMul(tmpVector2, vectorR); | ||
403 | beta = tmpValue1/tmpValue2; | ||
404 | |||
405 | /* | ||
406 | * vectorX = vectorX + alpha * vectorP | ||
407 | */ | ||
408 | valueMulvector(alpha, vectorP, tmpVector1); | ||
409 | vectorAdd(vectorX,tmpVector1, vectorX); | ||
410 | |||
411 | /* | ||
412 | *vectorP = nextVectorR + beta*vectorP | ||
413 | */ | ||
414 | valueMulvector(beta, vectorP, tmpVector1); | ||
415 | vectorAdd(nextVectorR, tmpVector1, tmpVector1); | ||
416 | |||
417 | for (ll=0; ll<dim; ll++){ | ||
418 | *(vectorP + ll) = *(tmpVector1 + ll); | ||
419 | } | ||
420 | |||
421 | /* | ||
422 | * vectorR = nextVectorR | ||
423 | */ | ||
424 | |||
425 | for (l=0; l<dim; l++){ | ||
426 | *(vectorR+l) = *(nextVectorR+l); | ||
427 | } | ||
428 | |||
429 | /* | ||
430 | * error = |matrixA * vectorX - vectorB| / |vectorB| | ||
431 | */ | ||
432 | matrixMulvector(value, col_ind,row_start, vectorX, tmpVector1); | ||
433 | vectorSub(tmpVector1,vectorB,tmpVector1); | ||
434 | error = vectorValue(tmpVector1)/vectorValue(vectorB); | ||
435 | |||
436 | iteration++; | ||
437 | STOP_LOOP | ||
438 | } | ||
439 | |||
440 | *actualError = error; | ||
441 | *actualIteration = iteration; | ||
442 | |||
443 | free(tmpVector1); | ||
444 | free(tmpVector2); | ||
445 | free(tmpVector3); | ||
446 | |||
447 | free(vectorR); | ||
448 | free(vectorP); | ||
449 | WRITE_TO_FILE | ||
450 | |||
451 | return; | ||
452 | } | ||
453 | |||
454 | /* | ||
455 | * This is the function to transfer the data from the matrix of dense storage | ||
456 | * to Compact Row Storage | ||
457 | */ | ||
458 | void create_CRS(double *matrixA, | ||
459 | double *value, | ||
460 | int *col_ind, | ||
461 | int *row_start, | ||
462 | int dim, | ||
463 | int numberNonzero) | ||
464 | { | ||
465 | |||
466 | int i, j, k; | ||
467 | int cnt; | ||
468 | double tmp; | ||
469 | |||
470 | /* | ||
471 | *initialize the row_start | ||
472 | */ | ||
473 | |||
474 | for(k=0; k<dim; k++){ | ||
475 | row_start[k] = -1; | ||
476 | } | ||
477 | |||
478 | /* | ||
479 | * make the end of the last row to be numberNonzero + dim. | ||
480 | */ | ||
481 | |||
482 | row_start[dim] = numberNonzero+dim; | ||
483 | |||
484 | /* | ||
485 | * initialize the col_ind | ||
486 | */ | ||
487 | |||
488 | for (k=0; k<numberNonzero+dim; k++){ | ||
489 | col_ind[k] = -1; | ||
490 | } | ||
491 | |||
492 | |||
493 | cnt = 0; | ||
494 | |||
495 | for (i=0; (cnt<numberNonzero+dim)&&(i<dim); i++){ | ||
496 | for (j=0; (cnt<numberNonzero+dim)&&(j<dim); j++){ | ||
497 | |||
498 | tmp = *(matrixA + i*dim + j); | ||
499 | |||
500 | if (tmp!=0){ | ||
501 | |||
502 | value[cnt] = tmp; | ||
503 | col_ind[cnt] = j; | ||
504 | |||
505 | if (row_start[i] == -1) | ||
506 | row_start[i] = cnt; | ||
507 | |||
508 | cnt += 1; | ||
509 | } | ||
510 | } | ||
511 | } | ||
512 | row_start[i] = cnt; | ||
513 | |||
514 | return; | ||
515 | } | ||
516 | |||
517 | |||
518 | int main(int _argc, char** _argv) | ||
519 | { | ||
520 | argc = _argc; | ||
521 | argv = _argv; | ||
522 | int seed; | ||
523 | int numberNonzero; | ||
524 | int maxIterations; | ||
525 | float errorTolerance; | ||
526 | double actualError; | ||
527 | int actualIteration; | ||
528 | |||
529 | time_t beginTime; | ||
530 | time_t endTime; | ||
531 | |||
532 | double *matrixA; | ||
533 | double *vectorB; | ||
534 | double *vectorX; | ||
535 | |||
536 | double *value; | ||
537 | int *col_ind; | ||
538 | int *row_start; | ||
539 | int sum; | ||
540 | int k; | ||
541 | |||
542 | fscanf(stdin, "%d %d %d %d %f", | ||
543 | &seed, &dim, &numberNonzero,&maxIterations,&errorTolerance); | ||
544 | assert((seed > MIN_SEED) && (seed < MAX_SEED)); | ||
545 | assert((dim > MIN_DIM) && (dim < MAX_DIM)); | ||
546 | assert((numberNonzero > dim) && (numberNonzero < dim*dim)); | ||
547 | assert((maxIterations > 0) && (maxIterations < MAX_ITERATIONS)); | ||
548 | assert((errorTolerance > MIN_TOLERANCE) && (errorTolerance < MAX_TOLERANCE)); | ||
549 | |||
550 | matrixA = (double *)malloc(dim*dim*sizeof(double )); | ||
551 | vectorB = (double *)malloc(dim*sizeof(double)); | ||
552 | vectorX = (double *)malloc(dim*sizeof(double)); | ||
553 | |||
554 | value = (double *)malloc((numberNonzero+dim)*sizeof(double)); | ||
555 | col_ind = (int *)malloc((numberNonzero+dim)*sizeof(int)); | ||
556 | row_start = (int *)malloc((dim+1)*sizeof(int)); | ||
557 | |||
558 | randInit(seed); | ||
559 | |||
560 | initMatrix(matrixA, dim, numberNonzero); | ||
561 | |||
562 | create_CRS(matrixA, value, col_ind, row_start, dim, numberNonzero); | ||
563 | |||
564 | initVector(vectorB, dim); | ||
565 | zeroVector(vectorX, dim); | ||
566 | printf(" after init\n"); | ||
567 | |||
568 | beginTime = time(NULL); | ||
569 | |||
570 | actualError = 0; | ||
571 | actualIteration = 0; | ||
572 | |||
573 | biConjugateGradient(value, col_ind, row_start, vectorB, vectorX, errorTolerance, | ||
574 | maxIterations, | ||
575 | &actualError, &actualIteration, dim); | ||
576 | |||
577 | |||
578 | |||
579 | endTime = time(NULL) - beginTime; | ||
580 | |||
581 | |||
582 | |||
583 | sum = 0; | ||
584 | for (k=1; k<dim; k++){ | ||
585 | sum += sum + *(vectorX + k); | ||
586 | } | ||
587 | |||
588 | fprintf(stdout, "sum = %d, actualError = %e, actualIteration = %d\n", sum, actualError, actualIteration); | ||
589 | fprintf(stdout, "total time = %u sec. \n", (unsigned int)endTime); | ||
590 | |||
591 | return(0); | ||
592 | } | ||
593 | |||
594 | |||