Dear Jason, all,
I am trying to find the accuracy problem with RISCV-FS and I observe
that the problem is created (at least in my dummy example) because the
variables (double) are set to zero in random simulated time (for this
reason I get different results among executions of the same code).
Specifically for the following dummy code:
#include <cmath>
#include <stdio.h>
int main(){
int dim = 10;
float result;
for (int iter = 0; iter < 2; iter++){
result = 0;
for (int i = 0; i < dim; i++){
for (int j = 0; j < dim; j++){
float sq_i = sqrt(i);
float sq_j = sqrt(j);
result += sq_i * sq_j;
printf("ITER: %d | i: %d | j: %d Result(i: %f | j: %f
| i*j: %f): %f\n", iter, i , j, sq_i, sq_j, sq_i * sq_j, result);
}
}
printf("Final Result: %lf\n", result);
}
}
The correct Final Result in both iterations is 372.721656. However, I
get the following results in FS:
ITER: 0 | i: 0 | j: 0 Result(i: 0.000000 | j: 0.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 1 Result(i: 0.000000 | j: 1.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 2 Result(i: 0.000000 | j: 1.414214 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 3 Result(i: 0.000000 | j: 1.732051 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 4 Result(i: 0.000000 | j: 2.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 5 Result(i: 0.000000 | j: 2.236068 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 6 Result(i: 0.000000 | j: 2.449490 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 7 Result(i: 0.000000 | j: 2.645751 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 8 Result(i: 0.000000 | j: 2.828427 | i*j:
0.000000): 0.000000
ITER: 0 | i: 0 | j: 9 Result(i: 0.000000 | j: 3.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 0 Result(i: 1.000000 | j: 0.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 1 Result(i: 1.000000 | j: 1.000000 | i*j:
1.000000): 1.000000
ITER: 0 | i: 1 | j: 2 Result(i: 1.000000 | j: 1.414214 | i*j:
1.414214): 2.414214
ITER: 0 | i: 1 | j: 3 Result(i: 1.000000 | j: 1.732051 | i*j:
1.732051): 4.146264
ITER: 0 | i: 1 | j: 4 Result(i: 0.000000 | j: 2.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 5 Result(i: 0.000000 | j: 2.236068 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 6 Result(i: 0.000000 | j: 2.449490 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 7 Result(i: 0.000000 | j: 2.645751 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 8 Result(i: 0.000000 | j: 2.828427 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 9 Result(i: 0.000000 | j: 3.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 2 | j: 0 Result(i: 1.414214 | j: 0.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 2 | j: 1 Result(i: 1.414214 | j: 1.000000 | i*j:
1.414214): 1.414214
ITER: 0 | i: 2 | j: 2 Result(i: 1.414214 | j: 1.414214 | i*j:
2.000000): 3.414214
ITER: 0 | i: 2 | j: 3 Result(i: 1.414214 | j: 1.732051 | i*j:
2.449490): 5.863703
ITER: 0 | i: 2 | j: 4 Result(i: 1.414214 | j: 2.000000 | i*j:
2.828427): 8.692130
ITER: 0 | i: 2 | j: 5 Result(i: 1.414214 | j: 2.236068 | i*j:
3.162278): 11.854408
ITER: 0 | i: 2 | j: 6 Result(i: 1.414214 | j: 2.449490 | i*j:
3.464102): 15.318510
ITER: 0 | i: 2 | j: 7 Result(i: 1.414214 | j: 2.645751 | i*j:
3.741657): 19.060167
ITER: 0 | i: 2 | j: 8 Result(i: 1.414214 | j: 2.828427 | i*j:
4.000000): 23.060167
ITER: 0 | i: 2 | j: 9 Result(i: 1.414214 | j: 3.000000 | i*j:
4.242641): 27.302808
ITER: 0 | i: 3 | j: 0 Result(i: 1.732051 | j: 0.000000 | i*j:
0.000000): 27.302808
ITER: 0 | i: 3 | j: 1 Result(i: 1.732051 | j: 1.000000 | i*j:
1.732051): 29.034859
ITER: 0 | i: 3 | j: 2 Result(i: 1.732051 | j: 1.414214 | i*j:
2.449490): 31.484348
ITER: 0 | i: 3 | j: 3 Result(i: 1.732051 | j: 1.732051 | i*j:
3.000000): 34.484348
ITER: 0 | i: 3 | j: 4 Result(i: 1.732051 | j: 2.000000 | i*j:
3.464102): 37.948450
ITER: 0 | i: 3 | j: 5 Result(i: 1.732051 | j: 2.236068 | i*j:
3.872983): 41.821433
ITER: 0 | i: 3 | j: 6 Result(i: 1.732051 | j: 2.449490 | i*j:
4.242641): 46.064074
ITER: 0 | i: 3 | j: 7 Result(i: 1.732051 | j: 2.645751 | i*j:
4.582576): 50.646650
ITER: 0 | i: 3 | j: 8 Result(i: 1.732051 | j: 2.828427 | i*j:
4.898979): 55.545629
ITER: 0 | i: 3 | j: 9 Result(i: 1.732051 | j: 3.000000 | i*j:
5.196152): 60.741782
ITER: 0 | i: 4 | j: 0 Result(i: 2.000000 | j: 0.000000 | i*j:
0.000000): 60.741782
ITER: 0 | i: 4 | j: 1 Result(i: 2.000000 | j: 1.000000 | i*j:
2.000000): 62.741782
ITER: 0 | i: 4 | j: 2 Result(i: 2.000000 | j: 1.414214 | i*j:
2.828427): 65.570209
ITER: 0 | i: 4 | j: 3 Result(i: 2.000000 | j: 1.732051 | i*j:
3.464102): 69.034310
ITER: 0 | i: 4 | j: 4 Result(i: 2.000000 | j: 2.000000 | i*j:
4.000000): 73.034310
ITER: 0 | i: 4 | j: 5 Result(i: 2.000000 | j: 2.236068 | i*j:
4.472136): 77.506446
ITER: 0 | i: 4 | j: 6 Result(i: 2.000000 | j: 2.449490 | i*j:
4.898979): 82.405426
ITER: 0 | i: 4 | j: 7 Result(i: 2.000000 | j: 2.645751 | i*j:
5.291503): 87.696928
ITER: 0 | i: 4 | j: 8 Result(i: 2.000000 | j: 2.828427 | i*j:
5.656854): 93.353783
ITER: 0 | i: 4 | j: 9 Result(i: 2.000000 | j: 3.000000 | i*j:
6.000000): 99.353783
ITER: 0 | i: 5 | j: 0 Result(i: 2.236068 | j: 0.000000 | i*j:
0.000000): 99.353783
ITER: 0 | i: 5 | j: 1 Result(i: 2.236068 | j: 1.000000 | i*j:
2.236068): 101.589851
ITER: 0 | i: 5 | j: 2 Result(i: 2.236068 | j: 1.414214 | i*j:
3.162278): 104.752128
ITER: 0 | i: 5 | j: 3 Result(i: 2.236068 | j: 1.732051 | i*j:
3.872983): 108.625112
ITER: 0 | i: 5 | j: 4 Result(i: 2.236068 | j: 2.000000 | i*j:
4.472136): 113.097248
ITER: 0 | i: 5 | j: 5 Result(i: 2.236068 | j: 2.236068 | i*j:
5.000000): 118.097248
ITER: 0 | i: 5 | j: 6 Result(i: 2.236068 | j: 2.449490 | i*j:
5.477226): 123.574473
ITER: 0 | i: 5 | j: 7 Result(i: 2.236068 | j: 2.645751 | i*j:
5.916080): 129.490553
ITER: 0 | i: 5 | j: 8 Result(i: 2.236068 | j: 2.828427 | i*j:
6.324555): 135.815108
ITER: 0 | i: 5 | j: 9 Result(i: 2.236068 | j: 3.000000 | i*j:
6.708204): 142.523312
ITER: 0 | i: 6 | j: 0 Result(i: 2.449490 | j: 0.000000 | i*j:
0.000000): 142.523312
ITER: 0 | i: 6 | j: 1 Result(i: 2.449490 | j: 1.000000 | i*j:
2.449490): 144.972802
ITER: 0 | i: 6 | j: 2 Result(i: 2.449490 | j: 1.414214 | i*j:
3.464102): 148.436904
ITER: 0 | i: 6 | j: 3 Result(i: 2.449490 | j: 1.732051 | i*j:
4.242641): 152.679544
ITER: 0 | i: 6 | j: 4 Result(i: 2.449490 | j: 2.000000 | i*j:
4.898979): 157.578524
ITER: 0 | i: 6 | j: 5 Result(i: 2.449490 | j: 2.236068 | i*j:
5.477226): 163.055749
ITER: 0 | i: 6 | j: 6 Result(i: 2.449490 | j: 2.449490 | i*j:
6.000000): 169.055749
ITER: 0 | i: 6 | j: 7 Result(i: 2.449490 | j: 2.645751 | i*j:
6.480741): 175.536490
ITER: 0 | i: 6 | j: 8 Result(i: 2.449490 | j: 2.828427 | i*j:
6.928203): 182.464693
ITER: 0 | i: 6 | j: 9 Result(i: 2.449490 | j: 3.000000 | i*j:
7.348469): 189.813162
ITER: 0 | i: 7 | j: 0 Result(i: 2.645751 | j: 0.000000 | i*j:
0.000000): 189.813162
ITER: 0 | i: 7 | j: 1 Result(i: 2.645751 | j: 1.000000 | i*j:
2.645751): 192.458914
ITER: 0 | i: 7 | j: 2 Result(i: 2.645751 | j: 1.414214 | i*j:
3.741657): 196.200571
ITER: 0 | i: 7 | j: 3 Result(i: 2.645751 | j: 1.732051 | i*j:
4.582576): 200.783147
ITER: 0 | i: 7 | j: 4 Result(i: 2.645751 | j: 2.000000 | i*j:
5.291503): 206.074649
ITER: 0 | i: 7 | j: 5 Result(i: 2.645751 | j: 2.236068 | i*j:
5.916080): 211.990729
ITER: 0 | i: 7 | j: 6 Result(i: 2.645751 | j: 2.449490 | i*j:
6.480741): 218.471470
ITER: 0 | i: 7 | j: 7 Result(i: 2.645751 | j: 2.645751 | i*j:
7.000000): 225.471470
ITER: 0 | i: 7 | j: 8 Result(i: 2.645751 | j: 2.828427 | i*j:
7.483315): 232.954785
ITER: 0 | i: 7 | j: 9 Result(i: 2.645751 | j: 3.000000 | i*j:
7.937254): 240.892039
ITER: 0 | i: 8 | j: 0 Result(i: 2.828427 | j: 0.000000 | i*j:
0.000000): 240.892039
ITER: 0 | i: 8 | j: 1 Result(i: 2.828427 | j: 1.000000 | i*j:
2.828427): 243.720466
ITER: 0 | i: 8 | j: 2 Result(i: 2.828427 | j: 1.414214 | i*j:
4.000000): 247.720466
ITER: 0 | i: 8 | j: 3 Result(i: 2.828427 | j: 1.732051 | i*j:
4.898979): 252.619445
ITER: 0 | i: 8 | j: 4 Result(i: 2.828427 | j: 2.000000 | i*j:
5.656854): 258.276300
ITER: 0 | i: 8 | j: 5 Result(i: 2.828427 | j: 2.236068 | i*j:
6.324555): 264.600855
ITER: 0 | i: 8 | j: 6 Result(i: 2.828427 | j: 2.449490 | i*j:
6.928203): 271.529058
ITER: 0 | i: 8 | j: 7 Result(i: 2.828427 | j: 2.645751 | i*j:
7.483315): 279.012373
ITER: 0 | i: 8 | j: 8 Result(i: 2.828427 | j: 2.828427 | i*j:
8.000000): 287.012373
ITER: 0 | i: 8 | j: 9 Result(i: 2.828427 | j: 3.000000 | i*j:
8.485281): 295.497654
ITER: 0 | i: 9 | j: 0 Result(i: 3.000000 | j: 0.000000 | i*j:
0.000000): 295.497654
ITER: 0 | i: 9 | j: 1 Result(i: 3.000000 | j: 1.000000 | i*j:
3.000000): 298.497654
ITER: 0 | i: 9 | j: 2 Result(i: 3.000000 | j: 1.414214 | i*j:
4.242641): 302.740295
ITER: 0 | i: 9 | j: 3 Result(i: 3.000000 | j: 1.732051 | i*j:
5.196152): 307.936447
ITER: 0 | i: 9 | j: 4 Result(i: 3.000000 | j: 2.000000 | i*j:
6.000000): 313.936447
ITER: 0 | i: 9 | j: 5 Result(i: 3.000000 | j: 2.236068 | i*j:
6.708204): 320.644651
ITER: 0 | i: 9 | j: 6 Result(i: 3.000000 | j: 2.449490 | i*j:
7.348469): 327.993120
ITER: 0 | i: 9 | j: 7 Result(i: 3.000000 | j: 2.645751 | i*j:
7.937254): 335.930374
ITER: 0 | i: 9 | j: 8 Result(i: 3.000000 | j: 2.828427 | i*j:
8.485281): 344.415656
ITER: 0 | i: 9 | j: 9 Result(i: 3.000000 | j: 3.000000 | i*j:
9.000000): 353.415656
Final Result: 353.415656
ITER: 1 | i: 0 | j: 0 Result(i: 0.000000 | j: 0.000000 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 1 Result(i: 0.000000 | j: 1.000000 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 2 Result(i: 0.000000 | j: 1.414214 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 3 Result(i: 0.000000 | j: 1.732051 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 4 Result(i: 0.000000 | j: 2.000000 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 5 Result(i: 0.000000 | j: 2.236068 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 6 Result(i: 0.000000 | j: 2.449490 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 7 Result(i: 0.000000 | j: 2.645751 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 8 Result(i: 0.000000 | j: 2.828427 | i*j:
0.000000): 0.000000
ITER: 1 | i: 0 | j: 9 Result(i: 0.000000 | j: 3.000000 | i*j:
0.000000): 0.000000
ITER: 1 | i: 1 | j: 0 Result(i: 1.000000 | j: 0.000000 | i*j:
0.000000): 0.000000
ITER: 1 | i: 1 | j: 1 Result(i: 1.000000 | j: 1.000000 | i*j:
1.000000): 1.000000
ITER: 1 | i: 1 | j: 2 Result(i: 1.000000 | j: 1.414214 | i*j:
1.414214): 2.414214
ITER: 1 | i: 1 | j: 3 Result(i: 1.000000 | j: 1.732051 | i*j:
1.732051): 4.146264
ITER: 1 | i: 1 | j: 4 Result(i: 1.000000 | j: 2.000000 | i*j:
2.000000): 6.146264
ITER: 1 | i: 1 | j: 5 Result(i: 1.000000 | j: 2.236068 | i*j:
2.236068): 8.382332
ITER: 1 | i: 1 | j: 6 Result(i: 1.000000 | j: 2.449490 | i*j:
2.449490): 10.831822
ITER: 1 | i: 1 | j: 7 Result(i: 1.000000 | j: 2.645751 | i*j:
2.645751): 13.477573
ITER: 1 | i: 1 | j: 8 Result(i: 1.000000 | j: 2.828427 | i*j:
2.828427): 16.306001
ITER: 1 | i: 1 | j: 9 Result(i: 1.000000 | j: 3.000000 | i*j:
3.000000): 19.306001
ITER: 1 | i: 2 | j: 0 Result(i: 1.414214 | j: 0.000000 | i*j:
0.000000): 19.306001
ITER: 1 | i: 2 | j: 1 Result(i: 1.414214 | j: 1.000000 | i*j:
1.414214): 20.720214
ITER: 1 | i: 2 | j: 2 Result(i: 1.414214 | j: 1.414214 | i*j:
2.000000): 22.720214
ITER: 1 | i: 2 | j: 3 Result(i: 1.414214 | j: 1.732051 | i*j:
2.449490): 25.169704
ITER: 1 | i: 2 | j: 4 Result(i: 1.414214 | j: 2.000000 | i*j:
2.828427): 27.998131
ITER: 1 | i: 2 | j: 5 Result(i: 1.414214 | j: 2.236068 | i*j:
3.162278): 31.160409
ITER: 1 | i: 2 | j: 6 Result(i: 1.414214 | j: 2.449490 | i*j:
3.464102): 34.624510
ITER: 1 | i: 2 | j: 7 Result(i: 1.414214 | j: 2.645751 | i*j:
3.741657): 38.366168
ITER: 1 | i: 2 | j: 8 Result(i: 1.414214 | j: 2.828427 | i*j:
4.000000): 42.366168
ITER: 1 | i: 2 | j: 9 Result(i: 1.414214 | j: 3.000000 | i*j:
4.242641): 46.608808
ITER: 1 | i: 3 | j: 0 Result(i: 1.732051 | j: 0.000000 | i*j:
0.000000): 46.608808
ITER: 1 | i: 3 | j: 1 Result(i: 1.732051 | j: 1.000000 | i*j:
1.732051): 48.340859
ITER: 1 | i: 3 | j: 2 Result(i: 1.732051 | j: 1.414214 | i*j:
2.449490): 50.790349
ITER: 1 | i: 3 | j: 3 Result(i: 1.732051 | j: 1.732051 | i*j:
3.000000): 53.790349
ITER: 1 | i: 3 | j: 4 Result(i: 1.732051 | j: 2.000000 | i*j:
3.464102): 57.254450
ITER: 1 | i: 3 | j: 5 Result(i: 1.732051 | j: 2.236068 | i*j:
3.872983): 61.127434
ITER: 1 | i: 3 | j: 6 Result(i: 1.732051 | j: 2.449490 | i*j:
4.242641): 65.370075
ITER: 1 | i: 3 | j: 7 Result(i: 1.732051 | j: 2.645751 | i*j:
4.582576): 69.952650
ITER: 1 | i: 3 | j: 8 Result(i: 1.732051 | j: 2.828427 | i*j:
4.898979): 74.851630
ITER: 1 | i: 3 | j: 9 Result(i: 1.732051 | j: 3.000000 | i*j:
5.196152): 80.047782
ITER: 1 | i: 4 | j: 0 Result(i: 2.000000 | j: 0.000000 | i*j:
0.000000): 80.047782
ITER: 1 | i: 4 | j: 1 Result(i: 2.000000 | j: 1.000000 | i*j:
2.000000): 82.047782
ITER: 1 | i: 4 | j: 2 Result(i: 2.000000 | j: 1.414214 | i*j:
2.828427): 84.876209
ITER: 1 | i: 4 | j: 3 Result(i: 2.000000 | j: 1.732051 | i*j:
3.464102): 88.340311
ITER: 1 | i: 4 | j: 4 Result(i: 2.000000 | j: 2.000000 | i*j:
4.000000): 92.340311
ITER: 1 | i: 4 | j: 5 Result(i: 2.000000 | j: 2.236068 | i*j:
4.472136): 96.812447
ITER: 1 | i: 4 | j: 6 Result(i: 2.000000 | j: 2.449490 | i*j:
4.898979): 101.711426
ITER: 1 | i: 4 | j: 7 Result(i: 2.000000 | j: 2.645751 | i*j:
5.291503): 107.002929
ITER: 1 | i: 4 | j: 8 Result(i: 2.000000 | j: 2.828427 | i*j:
5.656854): 112.659783
ITER: 1 | i: 4 | j: 9 Result(i: 2.000000 | j: 3.000000 | i*j:
6.000000): 118.659783
ITER: 1 | i: 5 | j: 0 Result(i: 2.236068 | j: 0.000000 | i*j:
0.000000): 118.659783
ITER: 1 | i: 5 | j: 1 Result(i: 2.236068 | j: 1.000000 | i*j:
2.236068): 120.895851
ITER: 1 | i: 5 | j: 2 Result(i: 2.236068 | j: 1.414214 | i*j:
3.162278): 124.058129
ITER: 1 | i: 5 | j: 3 Result(i: 2.236068 | j: 1.732051 | i*j:
3.872983): 127.931112
ITER: 1 | i: 5 | j: 4 Result(i: 2.236068 | j: 2.000000 | i*j:
4.472136): 132.403248
ITER: 1 | i: 5 | j: 5 Result(i: 2.236068 | j: 2.236068 | i*j:
5.000000): 137.403248
ITER: 1 | i: 5 | j: 6 Result(i: 2.236068 | j: 2.449490 | i*j:
5.477226): 142.880474
ITER: 1 | i: 5 | j: 7 Result(i: 2.236068 | j: 2.645751 | i*j:
5.916080): 148.796553
ITER: 1 | i: 5 | j: 8 Result(i: 2.236068 | j: 2.828427 | i*j:
6.324555): 155.121109
ITER: 1 | i: 5 | j: 9 Result(i: 2.236068 | j: 3.000000 | i*j:
6.708204): 161.829313
ITER: 1 | i: 6 | j: 0 Result(i: 2.449490 | j: 0.000000 | i*j:
0.000000): 161.829313
ITER: 1 | i: 6 | j: 1 Result(i: 2.449490 | j: 1.000000 | i*j:
2.449490): 164.278802
ITER: 1 | i: 6 | j: 2 Result(i: 2.449490 | j: 1.414214 | i*j:
3.464102): 167.742904
ITER: 1 | i: 6 | j: 3 Result(i: 2.449490 | j: 1.732051 | i*j:
4.242641): 171.985545
ITER: 1 | i: 6 | j: 4 Result(i: 2.449490 | j: 2.000000 | i*j:
4.898979): 176.884524
ITER: 1 | i: 6 | j: 5 Result(i: 2.449490 | j: 2.236068 | i*j:
5.477226): 182.361750
ITER: 1 | i: 6 | j: 6 Result(i: 2.449490 | j: 2.449490 | i*j:
6.000000): 188.361750
ITER: 1 | i: 6 | j: 7 Result(i: 2.449490 | j: 2.645751 | i*j:
6.480741): 194.842491
ITER: 1 | i: 6 | j: 8 Result(i: 2.449490 | j: 2.828427 | i*j:
6.928203): 201.770694
ITER: 1 | i: 6 | j: 9 Result(i: 2.449490 | j: 3.000000 | i*j:
7.348469): 209.119163
ITER: 1 | i: 7 | j: 0 Result(i: 2.645751 | j: 0.000000 | i*j:
0.000000): 209.119163
ITER: 1 | i: 7 | j: 1 Result(i: 2.645751 | j: 1.000000 | i*j:
2.645751): 211.764914
ITER: 1 | i: 7 | j: 2 Result(i: 2.645751 | j: 1.414214 | i*j:
3.741657): 215.506572
ITER: 1 | i: 7 | j: 3 Result(i: 2.645751 | j: 1.732051 | i*j:
4.582576): 220.089147
ITER: 1 | i: 7 | j: 4 Result(i: 2.645751 | j: 2.000000 | i*j:
5.291503): 225.380650
ITER: 1 | i: 7 | j: 5 Result(i: 2.645751 | j: 2.236068 | i*j:
5.916080): 231.296730
ITER: 1 | i: 7 | j: 6 Result(i: 2.645751 | j: 2.449490 | i*j:
6.480741): 237.777470
ITER: 1 | i: 7 | j: 7 Result(i: 2.645751 | j: 2.645751 | i*j:
7.000000): 244.777470
ITER: 1 | i: 7 | j: 8 Result(i: 2.645751 | j: 2.828427 | i*j:
7.483315): 252.260785
ITER: 1 | i: 7 | j: 9 Result(i: 2.645751 | j: 3.000000 | i*j:
7.937254): 260.198039
ITER: 1 | i: 8 | j: 0 Result(i: 2.828427 | j: 0.000000 | i*j:
0.000000): 260.198039
ITER: 1 | i: 8 | j: 1 Result(i: 2.828427 | j: 1.000000 | i*j:
2.828427): 263.026466
ITER: 1 | i: 8 | j: 2 Result(i: 2.828427 | j: 1.414214 | i*j:
4.000000): 267.026466
ITER: 1 | i: 8 | j: 3 Result(i: 2.828427 | j: 1.732051 | i*j:
4.898979): 271.925446
ITER: 1 | i: 8 | j: 4 Result(i: 2.828427 | j: 2.000000 | i*j:
5.656854): 277.582300
ITER: 1 | i: 8 | j: 5 Result(i: 2.828427 | j: 2.236068 | i*j:
6.324555): 283.906855
ITER: 1 | i: 8 | j: 6 Result(i: 2.828427 | j: 2.449490 | i*j:
6.928203): 290.835059
ITER: 1 | i: 8 | j: 7 Result(i: 2.828427 | j: 2.645751 | i*j:
7.483315): 298.318373
ITER: 1 | i: 8 | j: 8 Result(i: 2.828427 | j: 2.828427 | i*j:
8.000000): 306.318373
ITER: 1 | i: 8 | j: 9 Result(i: 2.828427 | j: 3.000000 | i*j:
8.485281): 314.803655
ITER: 1 | i: 9 | j: 0 Result(i: 3.000000 | j: 0.000000 | i*j:
0.000000): 314.803655
ITER: 1 | i: 9 | j: 1 Result(i: 3.000000 | j: 1.000000 | i*j:
3.000000): 317.803655
ITER: 1 | i: 9 | j: 2 Result(i: 3.000000 | j: 1.414214 | i*j:
4.242641): 322.046295
ITER: 1 | i: 9 | j: 3 Result(i: 3.000000 | j: 1.732051 | i*j:
5.196152): 327.242448
ITER: 1 | i: 9 | j: 4 Result(i: 3.000000 | j: 2.000000 | i*j:
6.000000): 333.242448
ITER: 1 | i: 9 | j: 5 Result(i: 3.000000 | j: 2.236068 | i*j:
6.708204): 339.950652
ITER: 1 | i: 9 | j: 6 Result(i: 3.000000 | j: 2.449490 | i*j:
7.348469): 347.299121
ITER: 1 | i: 9 | j: 7 Result(i: 3.000000 | j: 2.645751 | i*j:
7.937254): 355.236375
ITER: 1 | i: 9 | j: 8 Result(i: 3.000000 | j: 2.828427 | i*j:
8.485281): 363.721656
ITER: 1 | i: 9 | j: 9 Result(i: 3.000000 | j: 3.000000 | i*j:
9.000000): 372.721656
Final Result: 372.721656
As we can see in the following iterations the sqrt(1) as well as the
result is set to zero for some reason.
ITER: 0 | i: 1 | j: 4 Result(i: 0.000000 | j: 2.000000 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 5 Result(i: 0.000000 | j: 2.236068 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 6 Result(i: 0.000000 | j: 2.449490 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 7 Result(i: 0.000000 | j: 2.645751 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 8 Result(i: 0.000000 | j: 2.828427 | i*j:
0.000000): 0.000000
ITER: 0 | i: 1 | j: 9 Result(i: 0.000000 | j: 3.000000 | i*j:
0.000000): 0.000000
Please help me to resolve the accuracy issue! I think that it will be
very useful for gem5 community.
To be noticed, I find the correct simulated tick in which the
application started in FS (using m5 dumpstats), and I start the
--debug-start, but the trace file which is generated is 10x larger
than SE mode for the same application. How can I compare them?
Thank you in advance!
Best regards,
Nikos
Quoting Νικόλαος Ταμπουρατζής <ntampourat...@ece.auth.gr>:
> Dear Jason,
>
> I am trying to use --debug-start but in FS mode it is very difficult
> to find the tick on which the application is started!
>
> However, I am writing the following very simple c++ program:
>
> #include <cmath>
> #include <stdio.h>
>
> int main(){
>
> int dim = 4096;
>
> double result;
>
> for (int iter = 0; iter < 2; iter++){
> result = 0;
> for (int i = 0; i < dim; i++){
> for (int j = 0; j < dim; j++){
> result += sqrt(i) * sqrt(j);
> }
> }
> printf("Result: %lf\n", result); //Result: 30530733453.127449
> }
> }
>
> I cross-compile it using: riscv64-linux-gnu-g++ -static -O3 -o
> test_riscv test_riscv.cpp
>
>
> While in X86 (without cross-compilation of course), QEMU-RISCV,
> GEM5-SE the result is the same (30530733453.127449), in GEM5-FS the
> result is different! In addition, the result is also different
> between the 2 iterations.
>
> Please reproduce the error if you want in order to verify my result.
> Ηow can the issue be resolved?
>
> Thank you in advance!
>
> Best regards,
> Nikos
>
>
> Quoting Jason Lowe-Power <ja...@lowepower.com>:
>
>> Hi Nikos,
>>
>> You can use --debug-start to start the debugging after some number of
>> ticks. Also, I would expect that the difference should come up quickly,
so
>> no need to run the program to the end.
>>
>> For the FS mode one, you will want to just start the trace as the
>> application starts. This could be a bit of a pain.
>>
>> I'm not really sure what fundamentally could be different. FS and SE
mode
>> use the exact same code for executing instructions, so I don't think
that's
>> the problem. Have you tried running for smaller inputs or just one
>> iteration?
>>
>> Jason
>>
>>
>>
>> On Wed, Sep 21, 2022 at 9:04 AM Νικόλαος Ταμπουρατζής <
>> ntampourat...@ece.auth.gr> wrote:
>>
>>> Dear Bobby,
>>>
>>> Iam trying to add --debug-flags=Exec (building the gem5 for gem5.opt
>>> not for gem5.fast which I had) but the debug traces exceed the 20GB
>>> (and it is not finished yet) for less than 1 simulated second. How can
>>> I reduce the size of the debug-flags (or set something more specific)?
>>>
>>> In contrast I build the HPCG benchmark with DHPCG_DEBUG flag. If you
>>> want, you can compare these two output files
>>> (hpcg20010909T014640_SE_Mode & HPCG-Benchmark_3.1_FS_Mode). As you can
>>> see, something goes wrong with the accuracy of calculations in FS mode
>>> (benchmark uses double precission). You can find the files here:
>>> http://kition.mhl.tuc.gr:8000/d/68d82f3533/
>>>
>>> Best regards,
>>> Nikos
>>>
>>> Quoting Jason Lowe-Power <ja...@lowepower.com>:
>>>
>>>> That's quite odd that it works in SE mode but not FS mode!
>>>>
>>>> I would suggest running with --debug-flags=Exec for both and then
>>> perform a
>>>> diff to see how they differ.
>>>>
>>>> Cheers,
>>>> Jason
>>>>
>>>> On Tue, Sep 20, 2022 at 2:45 PM Νικόλαος Ταμπουρατζής <
>>>> ntampourat...@ece.auth.gr> wrote:
>>>>
>>>>> Dear Bobby,
>>>>>
>>>>> In QEMU I get the same (correct) results that I get in SE mode
>>>>> simulation. I get invalid results in FS simulation (in both
>>>>> riscv-fs.py and riscv-ubuntu-run.py). I cannot access real RISCV
>>>>> hardware at this moment, however, if you want you may execute my
xhpcg
>>>>> binary (http://kition.mhl.tuc.gr:8000/f/4ca25fdd3c/) with the
>>>>> following configuration:
>>>>>
>>>>> ./xhpcg --nx=16 --ny=16 --nz=16 --npx=1 --npy=1 --npz=1 --rt=0.1
>>>>>
>>>>> Please let me know if you have any updates!
>>>>>
>>>>> Best regards,
>>>>> Nikos
>>>>>
>>>>>
>>>>> Quoting Jason Lowe-Power <ja...@lowepower.com>:
>>>>>
>>>>> > Hi Nikos,
>>>>> >
>>>>> > I notice you said the following in your original email:
>>>>> >
>>>>> > In addition, I used the RISCV Ubuntu image
>>>>> >> (
https://github.com/gem5/gem5-resources/tree/stable/src/riscv-ubuntu
>>> ),
>>>>> >> I installed the gcc compiler, compile it (through qemu) and I get
>>>>> >> wrong results too.
>>>>> >
>>>>> >
>>>>> > Is this saying you get the wrong results is QEMU? If so, the bug
is in
>>>>> GCC
>>>>> > or the HPCG workload, not in gem5. If not, I would test in QEMU to
>>> make
>>>>> > sure the binary works there. Another way you could test to see if
the
>>>>> > problem is your binary or gem5 would be to run it on real
hardware. We
>>>>> have
>>>>> > access to some RISC-V hardware here at UC Davis, if you don't have
>>> access
>>>>> > to it.
>>>>> >
>>>>> > Cheers,
>>>>> > Jason
>>>>> >
>>>>> > On Tue, Sep 20, 2022 at 12:58 AM Νικόλαος Ταμπουρατζής <
>>>>> > ntampourat...@ece.auth.gr> wrote:
>>>>> >
>>>>> >> Dear Bobby,
>>>>> >>
>>>>> >> 1) I use the original riscv-fs.py which is provided in the latest
>>> gem5
>>>>> >> release.
>>>>> >> I run the gem5 once (./build/RISCV/gem5.fast -d ./HPCG_FS_results
>>>>> >> ./configs/example/gem5_library/riscv-fs.py) in order to download
the
>>>>> >> riscv-bootloader-vmlinux-5.10 and riscv-disk-img.
>>>>> >> After this I mount the riscv-disk-img (sudo mount -o loop
>>>>> >> riscv-disk-img /mnt), put the xhpcg executable and I do the
following
>>>>> >> changes in riscv-fs.py to boot the riscv-disk-img with executable:
>>>>> >>
>>>>> >> image = CustomDiskImageResource(
>>>>> >> local_path = "/home/cossim/.cache/gem5/riscv-disk-img",
>>>>> >> )
>>>>> >>
>>>>> >> # Set the Full System workload.
>>>>> >> board.set_kernel_disk_workload(
>>>>> >>
kernel=Resource("riscv-bootloader-vmlinux-5.10"),
>>>>> >> disk_image=image,
>>>>> >> )
>>>>> >>
>>>>> >> Finally, in the
gem5/src/python/gem5/components/boards/riscv_board.py
>>>>> >> I change the last line to "return ["console=ttyS0",
>>>>> >> "root={root_value}", "rw"]" in order to allow the write
permissions
>>> in
>>>>> >> the image.
>>>>> >>
>>>>> >>
>>>>> >> 2) The HPCG benchmark after some iterations calculates if the
results
>>>>> >> are valid or not valid. In the case of FS it gives invalid
results.
>>> As
>>>>> >> I see from the results, one (at least) problem is that produces
>>>>> >> different results in each HPCG execution (with the same
>>> configuration).
>>>>> >>
>>>>> >> Here is the HPCG output and riscv-fs.py
>>>>> >> (http://kition.mhl.tuc.gr:8000/d/68d82f3533/). You may reproduce
the
>>>>> >> results in the video if you use the xhpcg executable
>>>>> >> (http://kition.mhl.tuc.gr:8000/f/4ca25fdd3c/)
>>>>> >>
>>>>> >> Please help me in order to solve it!
>>>>> >>
>>>>> >> Finally, I get invalid results in the HPL benchmark in FS mode
too.
>>>>> >>
>>>>> >> Best regards,
>>>>> >> Nikos
>>>>> >>
>>>>> >>
>>>>> >> Quoting Bobby Bruce <bbr...@ucdavis.edu>:
>>>>> >>
>>>>> >> > I'm going to need a bit more information to help:
>>>>> >> >
>>>>> >> > 1. In what way have you modified
>>>>> >> > ./configs/example/gem5_library/riscv-fs.py? Can you attach the
>>> script
>>>>> >> here?
>>>>> >> > 2. What error are you getting or in what way are the results
>>> invalid?
>>>>> >> >
>>>>> >> > -
>>>>> >> > Dr. Bobby R. Bruce
>>>>> >> > Room 3050,
>>>>> >> > Kemper Hall, UC Davis
>>>>> >> > Davis,
>>>>> >> > CA, 95616
>>>>> >> >
>>>>> >> > web: https://www.bobbybruce.net
>>>>> >> >
>>>>> >> >
>>>>> >> > On Mon, Sep 19, 2022 at 1:43 PM Νικόλαος Ταμπουρατζής <
>>>>> >> > ntampourat...@ece.auth.gr> wrote:
>>>>> >> >
>>>>> >> >>
>>>>> >> >> Dear gem5 community,
>>>>> >> >>
>>>>> >> >> I have successfully cross-compile the HPCG benchmark for RISCV
>>>>> (Serial
>>>>> >> >> version, without MPI and OpenMP). While it working properly in
>>> gem5
>>>>> SE
>>>>> >> >> mode (./build/RISCV/gem5.fast -d ./HPCG_SE_results
>>>>> >> >> ./configs/example/se.py -c xhpcg --options '--nx=16 --ny=16
>>> --nz=16
>>>>> >> >> --npx=1 --npy=1 --npz=1 --rt=0.1'), I get invalid results in FS
>>>>> >> >> simulation using "./build/RISCV/gem5.fast -d ./HPCG_FS_results
>>>>> >> >> ./configs/example/gem5_library/riscv-fs.py" (I mount the riscv
>>> image
>>>>> >> >> and put it).
>>>>> >> >>
>>>>> >> >> Can you help me please?
>>>>> >> >>
>>>>> >> >> In addition, I used the RISCV Ubuntu image
>>>>> >> >> (
>>> https://github.com/gem5/gem5-resources/tree/stable/src/riscv-ubuntu
>>>>> ),
>>>>> >> >> I installed the gcc compiler, compile it (through qemu) and I
get
>>>>> >> >> wrong results too.
>>>>> >> >>
>>>>> >> >> Here is the Makefile which I use, the hpcg executable for RISCV
>>>>> >> >> (xhpcg), and a video that shows the results
>>>>> >> >> (http://kition.mhl.tuc.gr:8000/f/4ca25fdd3c/).
>>>>> >> >>
>>>>> >> >> P.S. I use the latest gem5 version.
>>>>> >> >>
>>>>> >> >> Thank you in advance! :)
>>>>> >> >>
>>>>> >> >> Best regards,
>>>>> >> >> Nikos
>>>>> >> >> _______________________________________________
>>>>> >> >> gem5-users mailing list -- gem5-users@gem5.org
>>>>> >> >> To unsubscribe send an email to gem5-users-le...@gem5.org
>>>>> >> >>
>>>>> >>
>>>>> >>
>>>>> >> _______________________________________________
>>>>> >> gem5-users mailing list -- gem5-users@gem5.org
>>>>> >> To unsubscribe send an email to gem5-users-le...@gem5.org
>>>>> >>
>>>>>
>>>>>
>>>>> _______________________________________________
>>>>> gem5-users mailing list -- gem5-users@gem5.org
>>>>> To unsubscribe send an email to gem5-users-le...@gem5.org
>>>>>
>>>
>>>
>>> _______________________________________________
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>>> To unsubscribe send an email to gem5-users-le...@gem5.org
>>>
>
>
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