/**
* Check that the results of all implemented multiplication algorithms
* match up.
*
* \param m Number of rows of A
* \param l Number of columns of A/number of rows of B
* \param n Number of columns of B
* \param k Parameter k of M4RM algorithm, may be 0 for automatic choice.
* \param cutoff Cut off parameter at which dimension to switch from
* Strassen to M4RM
*/
int mul_test_equality(rci_t m, rci_t l, rci_t n, int k, int cutoff) {
int ret = 0;
mzd_t *A, *B, *C, *D, *E;
printf(" mul: m: %4d, l: %4d, n: %4d, k: %2d, cutoff: %4d", m, l, n, k, cutoff);
/* we create two random matrices */
A = mzd_init(m, l);
B = mzd_init(l, n);
mzd_randomize(A);
mzd_randomize(B);
/* C = A*B via Strassen */
C = mzd_mul(NULL, A, B, cutoff);
/* D = A*B via M4RM, temporary buffers are managed internally */
D = mzd_mul_m4rm( NULL, A, B, k);
/* E = A*B via naive cubic multiplication */
E = mzd_mul_naive( NULL, A, B);
mzd_free(A);
mzd_free(B);
if (mzd_equal(C, D) != TRUE) {
printf(" Strassen != M4RM");
ret -=1;
}
if (mzd_equal(D, E) != TRUE) {
printf(" M4RM != Naiv");
ret -= 1;
}
if (mzd_equal(C, E) != TRUE) {
printf(" Strassen != Naiv");
ret -= 1;
}
mzd_free(C);
mzd_free(D);
mzd_free(E);
if(ret==0) {
printf(" ... passed\n");
} else {
printf(" ... FAILED\n");
}
return ret;
}
/*
* Class: m4rjni_Mzd
* Method: mzd_mul_naive
* Signature: (JJ)J
*/
JNIEXPORT jlong JNICALL Java_m4rjni_Mzd_mzd_1mul_1naive(JNIEnv *env, jclass obj, jlong Aptr, jlong Bptr) {
mzd_t *A = (mzd_t*)Aptr;
mzd_t *B = (mzd_t*)Bptr;
if (A==NULL || B==NULL) return 0;
return (jlong)mzd_mul_naive(NULL,A,B);
}
