blob: 9958e2593a00545137456525348f74a6d12e39a1 [file] [log] [blame] [edit]
// Copyright 2022 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
$assert BATCH_TILE >= 16
$assert BATCH_TILE == 16 or BATCH_TILE % 32 == 0
$SIMD_TILE = BATCH_TILE // 32
$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
#include <assert.h>
#include <immintrin.h>
#include <xnnpack/common.h>
#include <xnnpack/intrinsics-polyfill.h>
#include <xnnpack/vcvt.h>
$XINT8_T = {"QS8": "int8_t", "QU8": "uint8_t"}[DATATYPE]
$_MM256_CVTEPX8_EPI16 = {"QS8": "_mm256_cvtepi8_epi16", "QU8": "_mm256_cvtepu8_epi16"}[DATATYPE]
$_MM256_PACKXS_EPI16 = {"QS8": "_mm256_packs_epi16", "QU8": "_mm256_packus_epi16"}[DATATYPE]
$_MM_PACKXS_EPI16 = {"QS8": "_mm_packs_epi16", "QU8": "_mm_packus_epi16"}[DATATYPE]
void xnn_${DATATYPE.lower()}_vcvt_ukernel__avx2_x${BATCH_TILE}(
size_t n,
const ${XINT8_T}* x,
${XINT8_T}* y,
const union xnn_${DATATYPE.lower()}_cvt_params params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS
{
assert(n != 0);
assert(n % sizeof(${XINT8_T}) == 0);
assert(x != NULL);
assert(y != NULL);
const __m256i vinput_zero_point = _mm256_load_si256((const __m256i*) params->avx2.input_zero_point);
const __m256i vmultiplier = _mm256_load_si256((const __m256i*) params->avx2.multiplier);
const __m256i voutput_zero_point = _mm256_load_si256((const __m256i*) params->avx2.output_zero_point);
$if BATCH_TILE > 16:
for (; n >= ${BATCH_TILE} * sizeof(${XINT8_T}); n -= ${BATCH_TILE} * sizeof(${XINT8_T})) {
__m256i vacc${ABC[0]} = ${_MM256_CVTEPX8_EPI16}(_mm_loadu_si128((const __m128i*) x));
$for N in range(1, 2*SIMD_TILE):
__m256i vacc${ABC[N]} = ${_MM256_CVTEPX8_EPI16}(_mm_loadu_si128((const __m128i*) (x + ${N * 16})));
x += ${BATCH_TILE};
$for N in range(2*SIMD_TILE):
vacc${ABC[N]} = _mm256_sub_epi16(vinput_zero_point, vacc${ABC[N]});
$for N in range(2*SIMD_TILE):
vacc${ABC[N]} = _mm256_slli_epi16(vacc${ABC[N]}, 7);
$for N in range(2*SIMD_TILE):
vacc${ABC[N]} = _mm256_mulhrs_epi16(vacc${ABC[N]}, vmultiplier);
$for N in range(2*SIMD_TILE):
vacc${ABC[N]} = _mm256_adds_epi16(vacc${ABC[N]}, voutput_zero_point);
$for N in range(SIMD_TILE):
__m256i vy${ABC[N]} = ${_MM256_PACKXS_EPI16}(vacc${ABC[2*N]}, vacc${ABC[2*N+1]});
$for N in range(SIMD_TILE):
vy${ABC[N]} = _mm256_permute4x64_epi64(vy${ABC[N]}, _MM_SHUFFLE(3, 1, 2, 0));
_mm256_storeu_si256((__m256i*) y, vy${ABC[0]});
$for N in range(1, SIMD_TILE):
_mm256_storeu_si256((__m256i*) (y + ${N * 32}), vy${ABC[N]});
y += ${BATCH_TILE};
}
for (; n >= 16 * sizeof(${XINT8_T}); n -= 16 * sizeof(${XINT8_T})) {
__m256i vacc = ${_MM256_CVTEPX8_EPI16}(_mm_loadu_si128((const __m128i*) x));
vacc = _mm256_sub_epi16(vinput_zero_point, vacc);
vacc = _mm256_slli_epi16(vacc, 7);
vacc = _mm256_mulhrs_epi16(vacc, vmultiplier);
vacc = _mm256_adds_epi16(vacc, voutput_zero_point);
x += 16;
const __m128i vacc_hi = _mm256_extracti128_si256(vacc, 1);
const __m128i vy = ${_MM_PACKXS_EPI16}(_mm256_castsi256_si128(vacc), vacc_hi);
_mm_storeu_si128((__m128i*) y, vy);
y += 16;
}
if XNN_UNLIKELY(n != 0) {
assert(n >= 1 * sizeof(${XINT8_T}));
assert(n <= 15 * sizeof(${XINT8_T}));
__m256i vacc = ${_MM256_CVTEPX8_EPI16}(_mm_loadu_si128((const __m128i*) x));
vacc = _mm256_sub_epi16(vinput_zero_point, vacc);
vacc = _mm256_slli_epi16(vacc, 7);
vacc = _mm256_mulhrs_epi16(vacc, vmultiplier);
vacc = _mm256_adds_epi16(vacc, voutput_zero_point);
const __m128i vacc_hi = _mm256_extracti128_si256(vacc, 1);
__m128i vy = ${_MM_PACKXS_EPI16}(_mm256_castsi256_si128(vacc), vacc_hi);
if (n & (8 * sizeof(${XINT8_T}))) {
_mm_storel_epi64((__m128i*) y, vy);
vy = _mm_unpackhi_epi64(vy, vy);
y += 8;
}
if (n & (4 * sizeof(${XINT8_T}))) {
_mm_storeu_si32(y, vy);
vy = _mm_srli_epi64(vy, 32);
y += 4;
}
if (n & (2 * sizeof(${XINT8_T}))) {
_mm_storeu_si16(y, vy);
vy = _mm_srli_epi32(vy, 16);
y += 2;
}
if (n & (1 * sizeof(${XINT8_T}))) {
*y = (${XINT8_T}) _mm_extract_epi8(vy, 0);
}
}
}