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Math: Optimize 16-bit matrix multiplication function
Performed multiple optimization in the 16-bit matrix multiplication function. - This check-in changed accumulator data type from int64_t to int32_t , reducing the instruction cycle count by ~8.18% gain for matrix multiplication. - Enhanced pointer arithmetic within for loops - Eliminated unnecessary conditionals by directly handling Q0 data within algorithm core logic These optimization yied a ~36.31% reduction in memory usage for matrix multplication function Signed-off-by: Shriram Shastry <malladi.sastry@intel.com>
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src/math/matrix.c

Lines changed: 41 additions & 31 deletions
Original file line numberDiff line numberDiff line change
@@ -25,56 +25,66 @@
2525
* -EINVAL if input dimensions do not allow for multiplication.
2626
* -ERANGE if the shift operation might cause integer overflow.
2727
*/
28-
int mat_multiply(struct mat_matrix_16b *a, struct mat_matrix_16b *b, struct mat_matrix_16b *c)
28+
int mat_multiply(struct mat_matrix_16b *a, struct mat_matrix_16b *b,
29+
struct mat_matrix_16b *c)
2930
{
3031
/* Validate matrix dimensions are compatible for multiplication */
3132
if (a->columns != b->rows || a->rows != c->rows || b->columns != c->columns)
3233
return -EINVAL;
3334

34-
int64_t s;
35-
int16_t *x;
36-
int16_t *y;
37-
int16_t *z = c->data;
38-
int i, j, k;
39-
int y_inc = b->columns;
40-
const int shift_minus_one = a->fractions + b->fractions - c->fractions - 1;
35+
int32_t acc; /* Accumulator for dot product calculation */
36+
int16_t *x, *y, *z = c->data; /* Pointers for matrices a, b, and c */
37+
int i, j, k; /* Loop counters */
38+
int y_inc = b->columns; /* Column increment for matrix b elements */
39+
/* Calculate shift amount for adjusting fractional bits in the result */
40+
const int shift = a->fractions + b->fractions - c->fractions - 1;
4141

4242
/* Check shift to ensure no integer overflow occurs during shifting */
43-
if (shift_minus_one < -1 || shift_minus_one > 31)
43+
if (shift < -1 || shift > 31)
4444
return -ERANGE;
4545

46-
/* If all data is Q0 */
47-
if (shift_minus_one == -1) {
46+
/* Matrix multiplication loop */
47+
if (shift == -1) {
48+
/* Special case when shift is -1 (Q0 data) */
4849
for (i = 0; i < a->rows; i++) {
4950
for (j = 0; j < b->columns; j++) {
50-
s = 0;
51+
/* Initialize accumulator for each element */
52+
acc = 0;
53+
/* Set x at the start of ith row of a */
5154
x = a->data + a->columns * i;
55+
/* Set y at the top of jth column of b */
5256
y = b->data + j;
57+
/* Dot product loop */
5358
for (k = 0; k < b->rows; k++) {
54-
s += (int32_t)(*x) * (*y);
55-
x++;
59+
/* Multiply & accumulate */
60+
acc += (int32_t)(*x++) * (*y);
61+
/* Move to next row in the current column of b */
5662
y += y_inc;
5763
}
58-
*z = (int16_t)s; /* For Q16.0 */
59-
z++;
64+
*z = (int16_t)acc;
65+
z++; /* Move to the next element in the output matrix */
6066
}
6167
}
62-
63-
return 0;
64-
}
65-
66-
for (i = 0; i < a->rows; i++) {
67-
for (j = 0; j < b->columns; j++) {
68-
s = 0;
69-
x = a->data + a->columns * i;
70-
y = b->data + j;
71-
for (k = 0; k < b->rows; k++) {
72-
s += (int32_t)(*x) * (*y);
73-
x++;
74-
y += y_inc;
68+
} else {
69+
/* General case for other shift values */
70+
for (i = 0; i < a->rows; i++) {
71+
for (j = 0; j < b->columns; j++) {
72+
/* Initialize accumulator for each element */
73+
acc = 0;
74+
/* Set x at the start of ith row of a */
75+
x = a->data + a->columns * i;
76+
/* Set y at the top of jth column of b */
77+
y = b->data + j;
78+
/* Dot product loop */
79+
for (k = 0; k < b->rows; k++) {
80+
/* Multiply & accumulate */
81+
acc += (int32_t)(*x++) * (*y);
82+
/* Move to next row in the current column of b */
83+
y += y_inc;
84+
}
85+
*z = (int16_t)(((acc >> shift) + 1) >> 1);
86+
z++; /* Move to the next element in the output matrix */
7587
}
76-
*z = (int16_t)(((s >> shift_minus_one) + 1) >> 1); /*Shift to Qx.y */
77-
z++;
7888
}
7989
}
8090
return 0;

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