feat: use avx2 to speedup matmulF32 (#56)

src/funcs.cpp

@@ -152,25 +152,37 @@ struct MatmulThreadInfo {
 void matmulF32(MatmulThreadInfo* a) {
     const float* input = (float*)a->input;
     float* w = (float*)a->weights;
-    int d;
+    unsigned int d, j;
 
 #if defined(__ARM_NEON)
     float32x4_t q;
     float32x4_t p;
     float32x4_t z;
     for (d = a->ds; d < a->de; d++) {
         z = vmovq_n_f32(0);
-        for (int j = 0; j < a->n; j += 4) {
+        for (j = 0; j < a->n; j += 4) {
             q = vld1q_f32(&input[j]);
             p = vld1q_f32(&w[d * a->n + j]);
             z = vfmaq_f32(z, q, p);
         }
         a->output[d] = vaddvq_f32(z);
     }
+#elif defined(__AVX2__)
+    assert(a->n % 8 == 0);
+    __m256 a0, b0, u;
+    for (d = a->ds; d < a->de; d++) {
+        u = _mm256_set1_ps(0.0f);
+        for (j = 0; j < a->n; j += 8) {
+            a0 = _mm256_loadu_ps(&input[j]);
+            b0 = _mm256_loadu_ps(&w[d * a->n + j]);
+            u = _mm256_fmadd_ps(a0, b0, u);
+        }
+        a->output[d] = hsum_float_8(u);
+    }
 #else
     for (d = a->ds; d < a->de; d++) {
         float val = 0.0f;
-        for (int j = 0; j < a->n; j++) {
+        for (j = 0; j < a->n; j++) {
             val += w[d * a->n + j] * input[j];
         }
         a->output[d] = val;