feat(ggml): vectorize row conversion functions

Vectorized the following functions in ggml.c for improved performance on x86 architectures:
- ggml_fp16_to_fp32_row: using F16C intrinsics.
- ggml_fp32_to_fp16_row: using F16C intrinsics.
- ggml_bf16_to_fp32_row: using AVX2 and AVX512F intrinsics.

This change follows the existing pattern of using direct SIMD intrinsic checks in this file.

Author: Aaron

ggml/src/ggml.c

@@ -428,20 +428,46 @@ ggml_bf16_t ggml_fp32_to_bf16(float x) {
 }
 
 void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int64_t n) {
-    for (int64_t i = 0; i < n; i++) {
+    int i = 0;
+#if defined(__F16C__)
+    for (; i + 7 < n; i += 8) {
+        __m128i x_i = _mm_loadu_si128((__m128i *)(x + i));
+        __m256 y_v = _mm256_cvtph_ps(x_i);
+        _mm256_storeu_ps(y + i, y_v);
+    }
+#endif
+    for (; i < n; i++) {
         y[i] = GGML_FP16_TO_FP32(x[i]);
     }
 }
 
 void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int64_t n) {
     int i = 0;
+#if defined(__F16C__)
+    for (; i + 7 < n; i += 8) {
+        __m256 x_v = _mm256_loadu_ps(x + i);
+        __m128i y_v = _mm256_cvtps_ph(x_v, _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC);
+        _mm_storeu_si128((__m128i *)(y + i), y_v);
+    }
+#endif
     for (; i < n; ++i) {
         y[i] = GGML_FP32_TO_FP16(x[i]);
     }
 }
 
 void ggml_bf16_to_fp32_row(const ggml_bf16_t * x, float * y, int64_t n) {
     int i = 0;
+#if defined(__AVX512F__)
+    for (; i + 15 < n; i += 16) {
+        __m512 y_v = _mm512_castsi512_ps(_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((__m256i *)(x + i))), 16));
+        _mm512_storeu_ps(y + i, y_v);
+    }
+#elif defined(__AVX2__)
+    for (; i + 7 < n; i += 8) {
+        __m256 y_v = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((__m128i *)(x + i))), 16));
+        _mm256_storeu_ps(y + i, y_v);
+    }
+#endif
     for (; i < n; ++i) {
         y[i] = GGML_BF16_TO_FP32(x[i]);
     }