cleanup

no functional change

src/nnue/nnue_feature_transformer.h

@@ -228,33 +228,74 @@ class FeatureTransformer {
         return FeatureSet::HashValue ^ (OutputDimensions * 2);
     }
 
-    static constexpr void order_packs([[maybe_unused]] uint64_t* v) {
-#if defined(USE_AVX512)  // _mm512_packs_epi16 ordering
-        uint64_t tmp0 = v[2], tmp1 = v[3];
-        v[2] = v[8], v[3] = v[9];
-        v[8] = v[4], v[9] = v[5];
-        v[4] = tmp0, v[5] = tmp1;
-        tmp0 = v[6], tmp1 = v[7];
-        v[6] = v[10], v[7] = v[11];
-        v[10] = v[12], v[11] = v[13];
-        v[12] = tmp0, v[13] = tmp1;
-#elif defined(USE_AVX2)  // _mm256_packs_epi16 ordering
+    static constexpr void order_packus([[maybe_unused]] uint64_t* v) {
+#if defined(USE_AVX512)  // _mm512_packus_epi16 ordering
+        std::swap(v[12], v[6]);
+        std::swap(v[13], v[7]);
+
+        std::swap(v[6], v[10]);
+        std::swap(v[7], v[11]);
+
+        std::swap(v[4], v[2]);
+        std::swap(v[5], v[3]);
+
+        std::swap(v[2], v[8]);
+        std::swap(v[3], v[9]);
+#elif defined(USE_AVX2)  // _mm256_packus_epi16 ordering
         std::swap(v[2], v[4]);
         std::swap(v[3], v[5]);
 #endif
     }
 
-    static constexpr void inverse_order_packs([[maybe_unused]] uint64_t* v) {
-#if defined(USE_AVX512)  // Inverse _mm512_packs_epi16 ordering
-        uint64_t tmp0 = v[2], tmp1 = v[3];
-        v[2] = v[4], v[3] = v[5];
-        v[4] = v[8], v[5] = v[9];
-        v[8] = tmp0, v[9] = tmp1;
-        tmp0 = v[6], tmp1 = v[7];
-        v[6] = v[12], v[7] = v[13];
-        v[12] = v[10], v[13] = v[11];
-        v[10] = tmp0, v[11] = tmp1;
-#elif defined(USE_AVX2)  // Inverse _mm256_packs_epi16 ordering
+    static constexpr void inverse_order_packus([[maybe_unused]] uint64_t* v) {
+#if defined(USE_AVX512)  // Inverse _mm512_packus_epi16 ordering
+
+        // Here, our goal is to concatenate two 512-bit
+        // vectors, without changing their order. To do
+        // this, we reorder the weights every 1024 bits
+        // by swapping the elements by 64-bit blocks.
+
+        // Current _mm512_packus_epi16 order:
+        // 01    23    45    67    // Vector 0
+        //    89    AB    CD    EF // Vector 1
+        // 01 89 23 AB 45 CD 67 EF // Packed Result
+
+        std::swap(v[2], v[8]);
+        std::swap(v[3], v[9]);
+
+        // Current _mm512_packus_epi16 order:
+        // 01    89    45    67    // Vector 0
+        //    23    AB    CD    EF // Vector 1
+        // 01 23 89 AB 45 CD 67 EF // Packed Result
+
+        std::swap(v[4], v[2]);
+        std::swap(v[5], v[3]);
+
+        // Current _mm512_packus_epi16 order:
+        // 01    45    89    67    // Vector 0
+        //    23    AB    CD    EF // Vector 1
+        // 01 23 45 AB 89 CD 67 EF // Packed Result
+
+        std::swap(v[6], v[10]);
+        std::swap(v[7], v[11]);
+
+        // Current _mm512_packus_epi16 order:
+        // 01    45    89    AB    // Vector 0
+        //    23    67    CD    EF // Vector 1
+        // 01 23 45 67 89 CD AB EF // Packed Result
+
+        std::swap(v[12], v[6]);  // Now v[6] holds the original v[10]
+        std::swap(v[13], v[7]);  // Now v[7] holds the original v[11]
+
+            // clang-format off
+
+        // Current _mm512_packus_epi16 order:
+        // 01    45    89    AB    // Vector 0
+        //    23    67    AB    EF // Vector 1
+        // 01 23 45 67 89 AB CD EF // Packed Result
+
+            // clang-format on
+#elif defined(USE_AVX2)  // Inverse _mm256_packus_epi16 ordering
         std::swap(v[2], v[4]);
         std::swap(v[3], v[5]);
 #endif
@@ -300,22 +341,22 @@ class FeatureTransformer {
         read_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
         read_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
 
-        permute_weights(inverse_order_packs);
+        permute_weights(inverse_order_packus);
         scale_weights(true);
         return !stream.fail();
     }
 
     // Write network parameters
     bool write_parameters(std::ostream& stream) {
 
-        permute_weights(order_packs);
+        permute_weights(order_packus);
         scale_weights(false);
 
         write_leb_128<BiasType>(stream, biases, HalfDimensions);
         write_leb_128<WeightType>(stream, weights, HalfDimensions * InputDimensions);
         write_leb_128<PSQTWeightType>(stream, psqtWeights, PSQTBuckets * InputDimensions);
 
-        permute_weights(inverse_order_packs);
+        permute_weights(inverse_order_packus);
         scale_weights(true);
         return !stream.fail();
     }