return _mm512_add_epi32(_mm512_permutexvar_epi32(indices, x), bias);
};
- [[maybe_unused]] auto m512_add_dpbusd_epi32 = [=](__m512i& acc, __m512i a, __m512i b) {
#if defined (USE_VNNI)
+ [[maybe_unused]] auto m512_add_dpbusd_epi32 = [=](__m512i& acc, __m512i a, __m512i b) {
acc = _mm512_dpbusd_epi32(acc, a, b);
#else
+ [[maybe_unused]] auto m512_dpbusd_epi32 = [=](__m512i a, __m512i b) -> __m512i {
__m512i product0 = _mm512_maddubs_epi16(a, b);
- product0 = _mm512_madd_epi16(product0, kOnes512);
- acc = _mm512_add_epi32(acc, product0);
+ return _mm512_madd_epi16(product0, kOnes512);
#endif
};
return _mm_add_epi32(_mm_add_epi32(sum128lo, sum128hi), bias);
};
-
- [[maybe_unused]] auto m256_add_dpbusd_epi32 = [=](__m256i& acc, __m256i a, __m256i b) {
#if defined (USE_VNNI)
+ [[maybe_unused]] auto m256_add_dpbusd_epi32 = [=](__m256i& acc, __m256i a, __m256i b) {
acc = _mm256_dpbusd_epi32(acc, a, b);
#else
+ [[maybe_unused]] auto m256_dpbusd_epi32 = [=](__m256i a, __m256i b) -> __m256i {
__m256i product0 = _mm256_maddubs_epi16(a, b);
- product0 = _mm256_madd_epi16(product0, kOnes256);
- acc = _mm256_add_epi32(acc, product0);
+ return _mm256_madd_epi16(product0, kOnes256);
#endif
};
return _mm_add_epi32(sum0, bias);
};
- [[maybe_unused]] auto m128_add_dpbusd_epi32 = [=](__m128i& acc, __m128i a, __m128i b) {
+ [[maybe_unused]] auto m128_dpbusd_epi32 = [=](__m128i a, __m128i b) -> __m128i {
__m128i product0 = _mm_maddubs_epi16(a, b);
- product0 = _mm_madd_epi16(product0, kOnes128);
- acc = _mm_add_epi32(acc, product0);
+ return _mm_madd_epi16(product0, kOnes128);
};
#endif
const __m512i bias = *reinterpret_cast<const __m512i*>(&biases_[i]);
__m512i* outptr = reinterpret_cast<__m512i*>(&output[i]);
- __m512i sum01a = _mm512_setzero_si512();
- __m512i sum23a = _mm512_setzero_si512();
- __m512i sum45a = _mm512_setzero_si512();
- __m512i sum67a = _mm512_setzero_si512();
- __m512i sum01b = _mm512_setzero_si512();
- __m512i sum23b = _mm512_setzero_si512();
- __m512i sum45b = _mm512_setzero_si512();
- __m512i sum67b = _mm512_setzero_si512();
-
const auto row01a = *reinterpret_cast<const __m512i*>(&weights_[offset01a]);
const auto row23a = *reinterpret_cast<const __m512i*>(&weights_[offset23a]);
const auto row45a = *reinterpret_cast<const __m512i*>(&weights_[offset45a]);
const __m256i in256 = input_vector256[0];
const __m512i in = _mm512_inserti64x4(_mm512_castsi256_si512(in256), in256, 1);
+#if defined (USE_VNNI)
+ __m512i sum01a = _mm512_setzero_si512();
+ __m512i sum23a = _mm512_setzero_si512();
+ __m512i sum45a = _mm512_setzero_si512();
+ __m512i sum67a = _mm512_setzero_si512();
+ __m512i sum01b = _mm512_setzero_si512();
+ __m512i sum23b = _mm512_setzero_si512();
+ __m512i sum45b = _mm512_setzero_si512();
+ __m512i sum67b = _mm512_setzero_si512();
+
m512_add_dpbusd_epi32(sum01a, in, row01a);
m512_add_dpbusd_epi32(sum23a, in, row23a);
m512_add_dpbusd_epi32(sum45a, in, row45a);
m512_add_dpbusd_epi32(sum23b, in, row23b);
m512_add_dpbusd_epi32(sum45b, in, row45b);
m512_add_dpbusd_epi32(sum67b, in, row67b);
+#else
+ __m512i sum01a = m512_dpbusd_epi32(in, row01a);
+ __m512i sum23a = m512_dpbusd_epi32(in, row23a);
+ __m512i sum45a = m512_dpbusd_epi32(in, row45a);
+ __m512i sum67a = m512_dpbusd_epi32(in, row67a);
+ __m512i sum01b = m512_dpbusd_epi32(in, row01b);
+ __m512i sum23b = m512_dpbusd_epi32(in, row23b);
+ __m512i sum45b = m512_dpbusd_epi32(in, row45b);
+ __m512i sum67b = m512_dpbusd_epi32(in, row67b);
+#endif
*outptr = m512_hadd256x16(
sum01a, sum23a, sum45a, sum67a,
if constexpr (kPaddedInputDimensions % (kSimdWidth * 2) == 0)
{
- __m512i sum0 = _mm512_setzero_si512();
- __m512i sum1 = _mm512_setzero_si512();
- __m512i sum2 = _mm512_setzero_si512();
- __m512i sum3 = _mm512_setzero_si512();
-
const auto row0 = reinterpret_cast<const __m512i*>(&weights_[offset0]);
const auto row1 = reinterpret_cast<const __m512i*>(&weights_[offset1]);
const auto row2 = reinterpret_cast<const __m512i*>(&weights_[offset2]);
const auto row3 = reinterpret_cast<const __m512i*>(&weights_[offset3]);
- for (IndexType j = 0; j < kNumChunks512; ++j)
+#if defined (USE_VNNI)
+ __m512i sum0 = _mm512_setzero_si512();
+ __m512i sum1 = _mm512_setzero_si512();
+ __m512i sum2 = _mm512_setzero_si512();
+ __m512i sum3 = _mm512_setzero_si512();
+ const IndexType kStart = 0;
+#else
+ __m512i sum0 = m512_dpbusd_epi32(input_vector512[0], row0[0]);
+ __m512i sum1 = m512_dpbusd_epi32(input_vector512[0], row1[0]);
+ __m512i sum2 = m512_dpbusd_epi32(input_vector512[0], row2[0]);
+ __m512i sum3 = m512_dpbusd_epi32(input_vector512[0], row3[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks512; ++j)
{
const __m512i in = input_vector512[j];
+#if defined (USE_VNNI)
m512_add_dpbusd_epi32(sum0, in, row0[j]);
m512_add_dpbusd_epi32(sum1, in, row1[j]);
m512_add_dpbusd_epi32(sum2, in, row2[j]);
m512_add_dpbusd_epi32(sum3, in, row3[j]);
+#else
+ sum0 = _mm512_add_epi32(sum0, m512_dpbusd_epi32(in, row0[j]));
+ sum1 = _mm512_add_epi32(sum1, m512_dpbusd_epi32(in, row1[j]));
+ sum2 = _mm512_add_epi32(sum2, m512_dpbusd_epi32(in, row2[j]));
+ sum3 = _mm512_add_epi32(sum3, m512_dpbusd_epi32(in, row3[j]));
+#endif
}
*outptr = m512_haddx4(sum0, sum1, sum2, sum3, bias);
}
else
{
- __m256i sum0 = _mm256_setzero_si256();
- __m256i sum1 = _mm256_setzero_si256();
- __m256i sum2 = _mm256_setzero_si256();
- __m256i sum3 = _mm256_setzero_si256();
-
const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
- for (IndexType j = 0; j < kNumChunks256; ++j)
+#if defined (USE_VNNI)
+ __m256i sum0 = _mm256_setzero_si256();
+ __m256i sum1 = _mm256_setzero_si256();
+ __m256i sum2 = _mm256_setzero_si256();
+ __m256i sum3 = _mm256_setzero_si256();
+ const IndexType kStart = 0;
+#else
+ __m256i sum0 = m256_dpbusd_epi32(input_vector256[0], row0[0]);
+ __m256i sum1 = m256_dpbusd_epi32(input_vector256[0], row1[0]);
+ __m256i sum2 = m256_dpbusd_epi32(input_vector256[0], row2[0]);
+ __m256i sum3 = m256_dpbusd_epi32(input_vector256[0], row3[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks256; ++j)
{
const __m256i in = input_vector256[j];
+#if defined (USE_VNNI)
m256_add_dpbusd_epi32(sum0, in, row0[j]);
m256_add_dpbusd_epi32(sum1, in, row1[j]);
m256_add_dpbusd_epi32(sum2, in, row2[j]);
m256_add_dpbusd_epi32(sum3, in, row3[j]);
+#else
+ sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
+ sum1 = _mm256_add_epi32(sum1, m256_dpbusd_epi32(in, row1[j]));
+ sum2 = _mm256_add_epi32(sum2, m256_dpbusd_epi32(in, row2[j]));
+ sum3 = _mm256_add_epi32(sum3, m256_dpbusd_epi32(in, row3[j]));
+#endif
}
*outptr = m256_haddx4(sum0, sum1, sum2, sum3, bias);
{
if constexpr (kPaddedInputDimensions % (kSimdWidth * 2) == 0)
{
- __m512i sum0 = _mm512_setzero_si512();
-
const auto row0 = reinterpret_cast<const __m512i*>(&weights_[0]);
- for (IndexType j = 0; j < kNumChunks512; ++j)
+#if defined (USE_VNNI)
+ __m512i sum0 = _mm512_setzero_si512();
+ const IndexType kStart = 0;
+#else
+ __m512i sum0 = m512_dpbusd_epi32(input_vector512[0], row0[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks512; ++j)
{
const __m512i in = input_vector512[j];
+#if defined (USE_VNNI)
m512_add_dpbusd_epi32(sum0, in, row0[j]);
+#else
+ sum0 = _mm512_add_epi32(sum0, m512_dpbusd_epi32(in, row0[j]));
+#endif
}
output[0] = m512_hadd(sum0, biases_[0]);
}
else
{
- __m256i sum0 = _mm256_setzero_si256();
-
const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
- for (IndexType j = 0; j < kNumChunks256; ++j)
+#if defined (USE_VNNI)
+ __m256i sum0 = _mm256_setzero_si256();
+ const IndexType kStart = 0;
+#else
+ __m256i sum0 = m256_dpbusd_epi32(input_vector256[0], row0[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks256; ++j)
{
const __m256i in = input_vector256[j];
+#if defined (USE_VNNI)
m256_add_dpbusd_epi32(sum0, in, row0[j]);
+#else
+ sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
+#endif
}
output[0] = m256_hadd(sum0, biases_[0]);
const __m128i bias = *reinterpret_cast<const __m128i*>(&biases_[i]);
__m128i* outptr = reinterpret_cast<__m128i*>(&output[i]);
- __m256i sum0 = _mm256_setzero_si256();
- __m256i sum1 = _mm256_setzero_si256();
- __m256i sum2 = _mm256_setzero_si256();
- __m256i sum3 = _mm256_setzero_si256();
-
const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
- for (IndexType j = 0; j < kNumChunks; ++j)
+#if defined (USE_VNNI)
+ __m256i sum0 = _mm256_setzero_si256();
+ __m256i sum1 = _mm256_setzero_si256();
+ __m256i sum2 = _mm256_setzero_si256();
+ __m256i sum3 = _mm256_setzero_si256();
+ const IndexType kStart = 0;
+#else
+ __m256i sum0 = m256_dpbusd_epi32(input_vector[0], row0[0]);
+ __m256i sum1 = m256_dpbusd_epi32(input_vector[0], row1[0]);
+ __m256i sum2 = m256_dpbusd_epi32(input_vector[0], row2[0]);
+ __m256i sum3 = m256_dpbusd_epi32(input_vector[0], row3[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks; ++j)
{
const __m256i in = input_vector[j];
+#if defined (USE_VNNI)
m256_add_dpbusd_epi32(sum0, in, row0[j]);
m256_add_dpbusd_epi32(sum1, in, row1[j]);
m256_add_dpbusd_epi32(sum2, in, row2[j]);
m256_add_dpbusd_epi32(sum3, in, row3[j]);
+#else
+ sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
+ sum1 = _mm256_add_epi32(sum1, m256_dpbusd_epi32(in, row1[j]));
+ sum2 = _mm256_add_epi32(sum2, m256_dpbusd_epi32(in, row2[j]));
+ sum3 = _mm256_add_epi32(sum3, m256_dpbusd_epi32(in, row3[j]));
+#endif
}
*outptr = m256_haddx4(sum0, sum1, sum2, sum3, bias);
}
else if constexpr (kOutputDimensions == 1)
{
- __m256i sum0 = _mm256_setzero_si256();
-
const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
- for (IndexType j = 0; j < kNumChunks; ++j)
+#if defined (USE_VNNI)
+ __m256i sum0 = _mm256_setzero_si256();
+ const IndexType kStart = 0;
+#else
+ __m256i sum0 = m256_dpbusd_epi32(input_vector[0], row0[0]);
+ const IndexType kStart = 1;
+#endif
+
+ for (IndexType j = kStart; j < kNumChunks; ++j)
{
const __m256i in = input_vector[j];
- m256_add_dpbusd_epi32(sum0, in, row0[j]);
+#if defined (USE_VNNI)
+ m256_add_dpbusd_epi32(sum0, in, row0[j]);
+#else
+ sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
+#endif
}
output[0] = m256_hadd(sum0, biases_[0]);
const __m128i bias = *reinterpret_cast<const __m128i*>(&biases_[i]);
__m128i* outptr = reinterpret_cast<__m128i*>(&output[i]);
- __m128i sum0 = _mm_setzero_si128();
- __m128i sum1 = _mm_setzero_si128();
- __m128i sum2 = _mm_setzero_si128();
- __m128i sum3 = _mm_setzero_si128();
-
const auto row0 = reinterpret_cast<const __m128i*>(&weights_[offset0]);
const auto row1 = reinterpret_cast<const __m128i*>(&weights_[offset1]);
const auto row2 = reinterpret_cast<const __m128i*>(&weights_[offset2]);
const auto row3 = reinterpret_cast<const __m128i*>(&weights_[offset3]);
- for (int j = 0; j < (int)kNumChunks; j += 1)
+ __m128i sum0 = m128_dpbusd_epi32(input_vector[0], row0[0]);
+ __m128i sum1 = m128_dpbusd_epi32(input_vector[0], row1[0]);
+ __m128i sum2 = m128_dpbusd_epi32(input_vector[0], row2[0]);
+ __m128i sum3 = m128_dpbusd_epi32(input_vector[0], row3[0]);
+
+ for (int j = 1; j < (int)kNumChunks; ++j)
{
const __m128i in = input_vector[j];
- m128_add_dpbusd_epi32(sum0, in, row0[j]);
- m128_add_dpbusd_epi32(sum1, in, row1[j]);
- m128_add_dpbusd_epi32(sum2, in, row2[j]);
- m128_add_dpbusd_epi32(sum3, in, row3[j]);
+ sum0 = _mm_add_epi32(sum0, m128_dpbusd_epi32(in, row0[j]));
+ sum1 = _mm_add_epi32(sum1, m128_dpbusd_epi32(in, row1[j]));
+ sum2 = _mm_add_epi32(sum2, m128_dpbusd_epi32(in, row2[j]));
+ sum3 = _mm_add_epi32(sum3, m128_dpbusd_epi32(in, row3[j]));
}
*outptr = m128_haddx4(sum0, sum1, sum2, sum3, bias);
}
else if constexpr (kOutputDimensions == 1)
{
- __m128i sum0 = _mm_setzero_si128();
-
const auto row0 = reinterpret_cast<const __m128i*>(&weights_[0]);
- for (int j = 0; j < (int)kNumChunks; j += 1)
- {
- const __m128i in = input_vector[j];
+ __m128i sum0 = m128_dpbusd_epi32(input_vector[0], row0[0]);
- m128_add_dpbusd_epi32(sum0, in, row0[j]);
- }
+ for (int j = 1; j < (int)kNumChunks; ++j)
+ sum0 = _mm_add_epi32(sum0, m128_dpbusd_epi32(input_vector[j], row0[j]));
output[0] = m128_hadd(sum0, biases_[0]);
}
projects / stockfish / blobdiff