| // Auto-generated file. Do not edit! |
| // Template: src/f32-vscaleexpminusmax/avx2-p5.c.in |
| // Generator: tools/xngen |
| // |
| // Copyright 2019 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. |
| |
| #include <assert.h> |
| |
| #include <immintrin.h> |
| |
| #include <xnnpack/common.h> |
| #include <xnnpack/vscaleexpminusmax.h> |
| |
| |
| static const int32_t mask_table[14] = {-1, -1, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 0, 0}; |
| |
| void xnn_f32_vscaleexpminusmax_ukernel__avx2_p5_x8( |
| size_t elements, |
| const float* input, |
| float* output, |
| float scale, |
| float max) |
| { |
| assert(elements % sizeof(float) == 0); |
| |
| const __m256 vmagic_bias = _mm256_set1_ps(0x1.8000FEp23f); |
| // The smallest x for which expf(x) is normalized. |
| const __m256 vdenorm_cutoff = _mm256_set1_ps(-0x1.5D589Ep6f); |
| const __m256 vlog2e = _mm256_set1_ps(0x1.715476p+0f); |
| const __m256 vminus_ln2_hi = _mm256_set1_ps(-0x1.62E43p-1f); |
| const __m256 vminus_ln2_lo = _mm256_set1_ps(0x1.05C61p-29f); |
| |
| const __m256 vc1 = _mm256_set1_ps(0x1.FFFFF6p-1f); |
| const __m256 vc2 = _mm256_set1_ps(0x1.FFFDC6p-2f); |
| const __m256 vc3 = _mm256_set1_ps(0x1.555A80p-3f); |
| const __m256 vc4 = _mm256_set1_ps(0x1.573A1Ap-5f); |
| const __m256 vc5 = _mm256_set1_ps(0x1.0F9F9Cp-7f); |
| |
| const __m256 vscale = _mm256_set1_ps(scale); |
| const __m256 vi_max = _mm256_set1_ps(max); |
| |
| for (; elements >= 8 * sizeof(float); elements -= 8 * sizeof(float)) { |
| // Load 8 (1x8) inputs at a time. |
| const __m256 vi0 = _mm256_loadu_ps(input); |
| input += 8; |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const __m256 vx0 = _mm256_sub_ps(vi0, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| __m256 vn0 = _mm256_fmadd_ps(vx0, vlog2e, vmagic_bias); |
| |
| // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| const __m256 vs0 = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn0), 23)); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn0 = _mm256_sub_ps(vn0, vmagic_bias); |
| |
| // Compute reduced argument t := x - elements * log(2). |
| // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| __m256 vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_hi, vx0); |
| |
| vt0 = _mm256_fmadd_ps(vn0, vminus_ln2_lo, vt0); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| __m256 vp0 = _mm256_fmadd_ps(vc5, vt0, vc4); |
| |
| vp0 = _mm256_fmadd_ps(vp0, vt0, vc3); |
| |
| vp0 = _mm256_fmadd_ps(vp0, vt0, vc2); |
| |
| vp0 = _mm256_fmadd_ps(vp0, vt0, vc1); |
| |
| // Reconstruct the final f value: |
| // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| // = s + (t * s) * p |
| vt0 = _mm256_mul_ps(vt0, vs0); |
| |
| __m256 vf0 = _mm256_fmadd_ps(vt0, vp0, vs0); |
| |
| // For inputs below zero cutoff, replace output with +0.0f. |
| // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| vf0 = _mm256_andnot_ps(_mm256_cmp_ps(vx0, vdenorm_cutoff, _CMP_LT_OS), vf0); |
| |
| // Multiply by scale. |
| vf0 = _mm256_mul_ps(vf0, vscale); |
| |
| // Store 8 (1x8) outputs at a time. |
| _mm256_storeu_ps(output, vf0); |
| output += 8; |
| } |
| for (; elements >= 8 * sizeof(float); elements -= 8 * sizeof(float)) { |
| // Load 8 inputs at a time. |
| const __m256 vi = _mm256_loadu_ps(input); |
| input += 8; |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const __m256 vx = _mm256_sub_ps(vi, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| __m256 vn = _mm256_fmadd_ps(vx, vlog2e, vmagic_bias); |
| |
| // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn), 23)); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn = _mm256_sub_ps(vn, vmagic_bias); |
| |
| // Compute reduced argument t := x - elements * log(2). |
| // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx); |
| vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4); |
| vp = _mm256_fmadd_ps(vp, vt, vc3); |
| vp = _mm256_fmadd_ps(vp, vt, vc2); |
| vp = _mm256_fmadd_ps(vp, vt, vc1); |
| |
| // Reconstruct the final f value: |
| // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| // = s + (t * s) * p |
| vt = _mm256_mul_ps(vt, vs); |
| __m256 vf = _mm256_fmadd_ps(vt, vp, vs); |
| |
| // For inputs below zero cutoff, replace output with +0.0f. |
| // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| vf = _mm256_andnot_ps(_mm256_cmp_ps(vx, vdenorm_cutoff, _CMP_LT_OS), vf); |
| |
| // Multiply by scale. |
| vf = _mm256_mul_ps(vf, vscale); |
| |
| // Store 64 (8x8) outputs at a time. |
| _mm256_storeu_ps(output, vf); |
| output += 8; |
| } |
| if (elements != 0) { |
| assert(elements >= 1 * sizeof(float)); |
| assert(elements <= 7 * sizeof(float)); |
| const __m256i vmask = _mm256_loadu_si256((const __m256i*) ((uintptr_t) &mask_table[7] - elements)); |
| |
| // Load up to 7 inputs at a time. |
| const __m256 vi = _mm256_maskload_ps(input, vmask); |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const __m256 vx = _mm256_sub_ps(vi, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| __m256 vn = _mm256_fmadd_ps(vx, vlog2e, vmagic_bias); |
| |
| // Create a floating-point number s (scale) such that s == 2**elements for inputs which don't cause underflow, i.e. |
| // -87.33642 <= x <= 0.0, and -126 <= elements <= 0 accordingly. |
| const __m256 vs = _mm256_castsi256_ps(_mm256_slli_epi32(_mm256_castps_si256(vn), 23)); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn = _mm256_sub_ps(vn, vmagic_bias); |
| |
| // Compute reduced argument t := x - elements * log(2). |
| // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. |
| __m256 vt = _mm256_fmadd_ps(vn, vminus_ln2_hi, vx); |
| vt = _mm256_fmadd_ps(vn, vminus_ln2_lo, vt); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| __m256 vp = _mm256_fmadd_ps(vc5, vt, vc4); |
| vp = _mm256_fmadd_ps(vp, vt, vc3); |
| vp = _mm256_fmadd_ps(vp, vt, vc2); |
| vp = _mm256_fmadd_ps(vp, vt, vc1); |
| |
| // Reconstruct the final f value: |
| // f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))) |
| // = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))) |
| // = s + (t * s) * p |
| vt = _mm256_mul_ps(vt, vs); |
| __m256 vf = _mm256_fmadd_ps(vt, vp, vs); |
| |
| // For inputs below zero cutoff, replace output with +0.0f. |
| // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| vf = _mm256_andnot_ps(_mm256_cmp_ps(vx, vdenorm_cutoff, _CMP_LT_OS), vf); |
| |
| // Multiply by scale. |
| vf = _mm256_mul_ps(vf, vscale); |
| |
| // Store up to 7 outputs at a time. |
| _mm256_maskstore_ps(output, vmask, vf); |
| } |
| } |