blob: 73b7948cb9753aada78f5cdc5b8cb75c0596b4f8 [file] [log] [blame]
// Copyright 2020 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 == 0
$assert BATCH_TILE >= 16
$assert DIV_ALGO in ["div", "nr1fma", "nr1fma1adj"]
$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
$SIMD_TILE = BATCH_TILE // 16
#include <assert.h>
#include <immintrin.h>
#include <xnnpack/common.h>
#include <xnnpack/intrinsics-polyfill.h>
#include <xnnpack/vunary.h>
void xnn_f32_vsigmoid_ukernel__avx512f_rr1_lut16_p3_perm_scalef_${DIV_ALGO}_x${BATCH_TILE}(
size_t n,
const float* x,
float* y,
const union xnn_f32_sigmoid_params params[restrict XNN_MIN_ELEMENTS(1)])
{
assert(n % sizeof(float) == 0);
const __m512i vsign_mask = _mm512_set1_epi32((int) params->avx512_rr1_lut16_p3.sign_mask);
const __m512 vmagic_bias = _mm512_set1_ps(params->avx512_rr1_lut16_p3.magic_bias);
const __m512 vlog2e = _mm512_set1_ps(params->avx512_rr1_lut16_p3.log2e);
const __m512 vtable = _mm512_load_ps(params->avx512_rr1_lut16_p3.table);
const __m512 vminus_ln2 = _mm512_set1_ps(params->avx512_rr1_lut16_p3.minus_ln2);
const __m512 vc3 = _mm512_set1_ps(params->avx512_rr1_lut16_p3.c3);
const __m512 vc2 = _mm512_set1_ps(params->avx512_rr1_lut16_p3.c2);
const __m512 vone = _mm512_set1_ps(params->avx512_rr1_lut16_p3.one);
$if BATCH_TILE > 16:
for (; n >= ${BATCH_TILE} * sizeof(float); n -= ${BATCH_TILE} * sizeof(float)) {
const __m512 vx${ABC[0]} = _mm512_loadu_ps(x);
$for N in range(1, SIMD_TILE):
const __m512 vx${ABC[N]} = _mm512_loadu_ps(x + ${N * 16});
x += ${BATCH_TILE};
$for N in range(SIMD_TILE):
const __m512 vz${ABC[N]} = _mm512_castsi512_ps(_mm512_or_epi32(_mm512_castps_si512(vx${ABC[N]}), vsign_mask));
$for N in range(SIMD_TILE):
__m512 vn${ABC[N]} = _mm512_fmadd_ps(vz${ABC[N]}, vlog2e, vmagic_bias);
$for N in range(SIMD_TILE):
const __m512 vl${ABC[N]} = _mm512_permutexvar_ps(_mm512_castps_si512(vn${ABC[N]}), vtable);
$for N in range(SIMD_TILE):
vn${ABC[N]} = _mm512_sub_ps(vn${ABC[N]}, vmagic_bias);
$for N in range(SIMD_TILE):
__m512 vt${ABC[N]} = _mm512_fmadd_ps(vn${ABC[N]}, vminus_ln2, vz${ABC[N]});
$for N in range(SIMD_TILE):
__m512 vp${ABC[N]} = _mm512_fmadd_ps(vt${ABC[N]}, vc3, vc2);
$for N in range(SIMD_TILE):
vp${ABC[N]} = _mm512_mul_ps(vp${ABC[N]}, vt${ABC[N]});
$for N in range(SIMD_TILE):
vp${ABC[N]} = _mm512_fmadd_ps(vt${ABC[N]}, vp${ABC[N]}, vt${ABC[N]});
$for N in range(SIMD_TILE):
vp${ABC[N]} = _mm512_fmadd_ps(vl${ABC[N]}, vp${ABC[N]}, vl${ABC[N]});
$for N in range(SIMD_TILE):
const __m512 ve${ABC[N]} = _mm512_scalef_ps(vp${ABC[N]}, vn${ABC[N]});
$for N in range(SIMD_TILE):
const __m512 vd${ABC[N]} = _mm512_add_ps(ve${ABC[N]}, vone);
$if DIV_ALGO == "div":
$for N in range(SIMD_TILE):
__m512 vf${ABC[N]} = _mm512_div_ps(ve${ABC[N]}, vd${ABC[N]});
$else:
$for N in range(SIMD_TILE):
__m512 vr${ABC[N]} = _mm512_rcp14_ps(vd${ABC[N]});
$for N in range(SIMD_TILE):
vr${ABC[N]} = _mm512_fmadd_ps(_mm512_fnmadd_ps(vr${ABC[N]}, vd${ABC[N]}, vone), vr${ABC[N]}, vr${ABC[N]});
$for N in range(SIMD_TILE):
__m512 vf${ABC[N]} = _mm512_mul_ps(ve${ABC[N]}, vr${ABC[N]});
$if DIV_ALGO == "nr1fma1adj":
$for N in range(SIMD_TILE):
vf${ABC[N]} = _mm512_fmadd_ps(_mm512_fnmadd_ps(vf${ABC[N]}, vd${ABC[N]}, ve${ABC[N]}), vr${ABC[N]}, vf${ABC[N]});
$for N in range(SIMD_TILE):
vf${ABC[N]} = _mm512_mask_sub_ps(vf${ABC[N]}, _mm512_testn_epi32_mask(_mm512_castps_si512(vx${ABC[N]}), vsign_mask), vone, vf${ABC[N]});
_mm512_storeu_ps(y, vf${ABC[0]});
$for N in range(1, SIMD_TILE):
_mm512_storeu_ps(y + ${N * 16}, vf${ABC[N]});
y += ${BATCH_TILE};
}
for (; n >= 16 * sizeof(float); n -= 16 * sizeof(float)) {
const __m512 vx = _mm512_loadu_ps(x);
x += 16;
const __m512 vz = _mm512_castsi512_ps(_mm512_or_epi32(_mm512_castps_si512(vx), vsign_mask));
__m512 vn = _mm512_fmadd_ps(vz, vlog2e, vmagic_bias);
const __m512 vl = _mm512_permutexvar_ps(_mm512_castps_si512(vn), vtable);
vn = _mm512_sub_ps(vn, vmagic_bias);
__m512 vt = _mm512_fmadd_ps(vn, vminus_ln2, vz);
__m512 vp = _mm512_fmadd_ps(vt, vc3, vc2);
vp = _mm512_mul_ps(vp, vt);
vp = _mm512_fmadd_ps(vt, vp, vt);
vp = _mm512_fmadd_ps(vl, vp, vl);
const __m512 ve = _mm512_scalef_ps(vp, vn);
const __m512 vd = _mm512_add_ps(ve, vone);
$if DIV_ALGO == "div":
__m512 vf = _mm512_div_ps(ve, vd);
$else:
__m512 vr = _mm512_rcp14_ps(vd);
vr = _mm512_fmadd_ps(_mm512_fnmadd_ps(vr, vd, vone), vr, vr);
__m512 vf = _mm512_mul_ps(ve, vr);
$if DIV_ALGO == "nr1fma1adj":
vf = _mm512_fmadd_ps(_mm512_fnmadd_ps(vf, vd, ve), vr, vf);
vf = _mm512_mask_sub_ps(vf, _mm512_testn_epi32_mask(_mm512_castps_si512(vx), vsign_mask), vone, vf);
_mm512_storeu_ps(y, vf);
y += 16;
}
if XNN_UNLIKELY(n != 0) {
assert(n >= 1 * sizeof(float));
assert(n <= 15 * sizeof(float));
// Prepare mask for valid 32-bit elements (depends on n).
n >>= 2 /* log2(sizeof(float)) */;
const __mmask16 vmask = _cvtu32_mask16((uint16_t) ((uint32_t) (UINT32_C(1) << n) - UINT32_C(1)));
const __m512 vx = _mm512_maskz_loadu_ps(vmask, x);
const __m512 vz = _mm512_castsi512_ps(_mm512_or_epi32(_mm512_castps_si512(vx), vsign_mask));
__m512 vn = _mm512_fmadd_ps(vz, vlog2e, vmagic_bias);
const __m512 vl = _mm512_permutexvar_ps(_mm512_castps_si512(vn), vtable);
vn = _mm512_sub_ps(vn, vmagic_bias);
__m512 vt = _mm512_fmadd_ps(vn, vminus_ln2, vz);
__m512 vp = _mm512_fmadd_ps(vt, vc3, vc2);
vp = _mm512_mul_ps(vp, vt);
vp = _mm512_fmadd_ps(vt, vp, vt);
vp = _mm512_fmadd_ps(vl, vp, vl);
const __m512 ve = _mm512_scalef_ps(vp, vn);
const __m512 vd = _mm512_add_ps(ve, vone);
$if DIV_ALGO == "div":
__m512 vf = _mm512_div_ps(ve, vd);
$else:
__m512 vr = _mm512_rcp14_ps(vd);
vr = _mm512_fmadd_ps(_mm512_fnmadd_ps(vr, vd, vone), vr, vr);
__m512 vf = _mm512_mul_ps(ve, vr);
$if DIV_ALGO == "nr1fma1adj":
vf = _mm512_fmadd_ps(_mm512_fnmadd_ps(vf, vd, ve), vr, vf);
vf = _mm512_mask_sub_ps(vf, _mm512_testn_epi32_mask(_mm512_castps_si512(vx), vsign_mask), vone, vf);
_mm512_mask_storeu_ps(y, vmask, vf);
}
}