| // Auto-generated file. Do not edit! |
| // Template: src/f32-raddstoreexpminusmax/psimd-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 <psimd.h> |
| |
| #include <xnnpack/common.h> |
| #include <xnnpack/raddstoreexpminusmax.h> |
| |
| |
| void xnn_f32_raddstoreexpminusmax_ukernel__psimd_p5_x20( |
| size_t elements, |
| const float* input, |
| float* output, |
| float* sum, |
| float max) |
| { |
| assert(elements % sizeof(float) == 0); |
| |
| const psimd_f32 vmagic_bias = psimd_splat_f32(0x1.8000FEp23f); |
| // The smallest x for which expf(x) is normalized. |
| const psimd_f32 vdenorm_cutoff = psimd_splat_f32(-0x1.5D589Ep6f); |
| const psimd_f32 vlog2e = psimd_splat_f32(0x1.715476p+0f); |
| // Last 7 bits are zeroes |
| const psimd_f32 vminus_ln2_hi = psimd_splat_f32(-0x1.62E400p-1f); |
| const psimd_f32 vminus_ln2_lo = psimd_splat_f32(-0x1.7F7D1Cp-20f); |
| |
| const psimd_f32 vc1 = psimd_splat_f32(0x1.FFFFF6p-1f); |
| const psimd_f32 vc2 = psimd_splat_f32(0x1.FFFDC6p-2f); |
| const psimd_f32 vc3 = psimd_splat_f32(0x1.555A80p-3f); |
| const psimd_f32 vc4 = psimd_splat_f32(0x1.573A1Ap-5f); |
| const psimd_f32 vc5 = psimd_splat_f32(0x1.0F9F9Cp-7f); |
| |
| const psimd_f32 vi_max = psimd_splat_f32(max); |
| |
| psimd_f32 vacc0 = psimd_zero_f32(); |
| for (; elements >= 20 * sizeof(float); elements -= 20 * sizeof(float)) { |
| // Load 20 (5x4) inputs at a time. |
| const psimd_f32 vi0123 = psimd_load_f32(input); |
| const psimd_f32 vi4567 = psimd_load_f32(input + 4); |
| const psimd_f32 vi89AB = psimd_load_f32(input + 8); |
| const psimd_f32 viCDEF = psimd_load_f32(input + 12); |
| const psimd_f32 viGHIJ = psimd_load_f32(input + 16); |
| input += 20; |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const psimd_f32 vx0123 = psimd_sub_f32(vi0123, vi_max); |
| const psimd_f32 vx4567 = psimd_sub_f32(vi4567, vi_max); |
| const psimd_f32 vx89AB = psimd_sub_f32(vi89AB, vi_max); |
| const psimd_f32 vxCDEF = psimd_sub_f32(viCDEF, vi_max); |
| const psimd_f32 vxGHIJ = psimd_sub_f32(viGHIJ, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| psimd_f32 vn0123 = psimd_qfma_f32(vmagic_bias, vx0123, vlog2e); |
| psimd_f32 vn4567 = psimd_qfma_f32(vmagic_bias, vx4567, vlog2e); |
| psimd_f32 vn89AB = psimd_qfma_f32(vmagic_bias, vx89AB, vlog2e); |
| psimd_f32 vnCDEF = psimd_qfma_f32(vmagic_bias, vxCDEF, vlog2e); |
| psimd_f32 vnGHIJ = psimd_qfma_f32(vmagic_bias, vxGHIJ, vlog2e); |
| |
| // 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 psimd_f32 vs0123 = (psimd_f32) ((psimd_u32) vn0123 << 23); |
| const psimd_f32 vs4567 = (psimd_f32) ((psimd_u32) vn4567 << 23); |
| const psimd_f32 vs89AB = (psimd_f32) ((psimd_u32) vn89AB << 23); |
| const psimd_f32 vsCDEF = (psimd_f32) ((psimd_u32) vnCDEF << 23); |
| const psimd_f32 vsGHIJ = (psimd_f32) ((psimd_u32) vnGHIJ << 23); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn0123 = psimd_sub_f32(vn0123, vmagic_bias); |
| vn4567 = psimd_sub_f32(vn4567, vmagic_bias); |
| vn89AB = psimd_sub_f32(vn89AB, vmagic_bias); |
| vnCDEF = psimd_sub_f32(vnCDEF, vmagic_bias); |
| vnGHIJ = psimd_sub_f32(vnGHIJ, 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. |
| psimd_f32 vt0123 = psimd_qfma_f32(vx0123, vn0123, vminus_ln2_hi); |
| psimd_f32 vt4567 = psimd_qfma_f32(vx4567, vn4567, vminus_ln2_hi); |
| psimd_f32 vt89AB = psimd_qfma_f32(vx89AB, vn89AB, vminus_ln2_hi); |
| psimd_f32 vtCDEF = psimd_qfma_f32(vxCDEF, vnCDEF, vminus_ln2_hi); |
| psimd_f32 vtGHIJ = psimd_qfma_f32(vxGHIJ, vnGHIJ, vminus_ln2_hi); |
| |
| vt0123 = psimd_qfma_f32(vt0123, vn0123, vminus_ln2_lo); |
| vt4567 = psimd_qfma_f32(vt4567, vn4567, vminus_ln2_lo); |
| vt89AB = psimd_qfma_f32(vt89AB, vn89AB, vminus_ln2_lo); |
| vtCDEF = psimd_qfma_f32(vtCDEF, vnCDEF, vminus_ln2_lo); |
| vtGHIJ = psimd_qfma_f32(vtGHIJ, vnGHIJ, vminus_ln2_lo); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| psimd_f32 vp0123 = psimd_qfma_f32(vc4, vc5, vt0123); |
| psimd_f32 vp4567 = psimd_qfma_f32(vc4, vc5, vt4567); |
| psimd_f32 vp89AB = psimd_qfma_f32(vc4, vc5, vt89AB); |
| psimd_f32 vpCDEF = psimd_qfma_f32(vc4, vc5, vtCDEF); |
| psimd_f32 vpGHIJ = psimd_qfma_f32(vc4, vc5, vtGHIJ); |
| |
| vp0123 = psimd_qfma_f32(vc3, vp0123, vt0123); |
| vp4567 = psimd_qfma_f32(vc3, vp4567, vt4567); |
| vp89AB = psimd_qfma_f32(vc3, vp89AB, vt89AB); |
| vpCDEF = psimd_qfma_f32(vc3, vpCDEF, vtCDEF); |
| vpGHIJ = psimd_qfma_f32(vc3, vpGHIJ, vtGHIJ); |
| |
| vp0123 = psimd_qfma_f32(vc2, vp0123, vt0123); |
| vp4567 = psimd_qfma_f32(vc2, vp4567, vt4567); |
| vp89AB = psimd_qfma_f32(vc2, vp89AB, vt89AB); |
| vpCDEF = psimd_qfma_f32(vc2, vpCDEF, vtCDEF); |
| vpGHIJ = psimd_qfma_f32(vc2, vpGHIJ, vtGHIJ); |
| |
| vp0123 = psimd_qfma_f32(vc1, vp0123, vt0123); |
| vp4567 = psimd_qfma_f32(vc1, vp4567, vt4567); |
| vp89AB = psimd_qfma_f32(vc1, vp89AB, vt89AB); |
| vpCDEF = psimd_qfma_f32(vc1, vpCDEF, vtCDEF); |
| vpGHIJ = psimd_qfma_f32(vc1, vpGHIJ, vtGHIJ); |
| |
| // 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 |
| vt0123 = psimd_mul_f32(vt0123, vs0123); |
| vt4567 = psimd_mul_f32(vt4567, vs4567); |
| vt89AB = psimd_mul_f32(vt89AB, vs89AB); |
| vtCDEF = psimd_mul_f32(vtCDEF, vsCDEF); |
| vtGHIJ = psimd_mul_f32(vtGHIJ, vsGHIJ); |
| |
| psimd_f32 vf0123 = psimd_qfma_f32(vs0123, vt0123, vp0123); |
| psimd_f32 vf4567 = psimd_qfma_f32(vs4567, vt4567, vp4567); |
| psimd_f32 vf89AB = psimd_qfma_f32(vs89AB, vt89AB, vp89AB); |
| psimd_f32 vfCDEF = psimd_qfma_f32(vsCDEF, vtCDEF, vpCDEF); |
| psimd_f32 vfGHIJ = psimd_qfma_f32(vsGHIJ, vtGHIJ, vpGHIJ); |
| |
| // For inputs below zero cutoff, replace output with +0.0f. |
| // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| vf0123 = psimd_andnotmask_f32(vx0123 < vdenorm_cutoff, vf0123); |
| vf4567 = psimd_andnotmask_f32(vx4567 < vdenorm_cutoff, vf4567); |
| vf89AB = psimd_andnotmask_f32(vx89AB < vdenorm_cutoff, vf89AB); |
| vfCDEF = psimd_andnotmask_f32(vxCDEF < vdenorm_cutoff, vfCDEF); |
| vfGHIJ = psimd_andnotmask_f32(vxGHIJ < vdenorm_cutoff, vfGHIJ); |
| |
| // Store 20 (5x4) outputs at a time. |
| psimd_store_f32(output, vf0123); |
| psimd_store_f32(output + 4, vf4567); |
| psimd_store_f32(output + 8, vf89AB); |
| psimd_store_f32(output + 12, vfCDEF); |
| psimd_store_f32(output + 16, vfGHIJ); |
| output += 20; |
| |
| // Accumulate computed exponents. |
| vacc0 = psimd_add_f32(vacc0, vf0123); |
| vacc0 = psimd_add_f32(vacc0, vf4567); |
| vacc0 = psimd_add_f32(vacc0, vf89AB); |
| vacc0 = psimd_add_f32(vacc0, vfCDEF); |
| vacc0 = psimd_add_f32(vacc0, vfGHIJ); |
| } |
| |
| psimd_f32 vacc = vacc0; |
| for (; elements >= 4 * sizeof(float); elements -= 4 * sizeof(float)) { |
| // Load 4 inputs at a time. |
| const psimd_f32 vi = psimd_load_f32(input); |
| input += 4; |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const psimd_f32 vx = psimd_sub_f32(vi, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| psimd_f32 vn = psimd_qfma_f32(vmagic_bias, vx, vlog2e); |
| |
| // 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 psimd_f32 vs = (psimd_f32) ((psimd_u32) vn << 23); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn = psimd_sub_f32(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. |
| psimd_f32 vt = psimd_qfma_f32(vx, vn, vminus_ln2_hi); |
| vt = psimd_qfma_f32(vt, vn, vminus_ln2_lo); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| psimd_f32 vp = psimd_qfma_f32(vc4, vc5, vt); |
| vp = psimd_qfma_f32(vc3, vp, vt); |
| vp = psimd_qfma_f32(vc2, vp, vt); |
| vp = psimd_qfma_f32(vc1, vp, vt); |
| |
| // 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 = psimd_mul_f32(vt, vs); |
| psimd_f32 vf = psimd_qfma_f32(vs, vt, vp); |
| |
| // 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 = psimd_andnotmask_f32(vx < vdenorm_cutoff, vf); |
| |
| // Store 4 outputs at a time. |
| psimd_store_f32(output, vf); |
| output += 4; |
| |
| // Accumulate computed exponents. |
| vacc = psimd_add_f32(vacc, vf); |
| } |
| if (elements != 0) { |
| assert(elements >= 1 * sizeof(float)); |
| assert(elements <= 3 * sizeof(float)); |
| // Load 4 inputs at a time. |
| const psimd_f32 vi = psimd_load_f32(input); |
| |
| // Subtract maximum input x := i - i_max. This implies x <= 0. |
| const psimd_f32 vx = psimd_sub_f32(vi, vi_max); |
| |
| // Compute reduced argument elements := round(x / log(2)). |
| psimd_f32 vn = psimd_qfma_f32(vmagic_bias, vx, vlog2e); |
| |
| // 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 psimd_f32 vs = (psimd_f32) ((psimd_u32) vn << 23); |
| |
| // Subtract the large number back to get final elements := round(x / log(2)). |
| vn = psimd_sub_f32(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. |
| psimd_f32 vt = psimd_qfma_f32(vx, vn, vminus_ln2_hi); |
| vt = psimd_qfma_f32(vt, vn, vminus_ln2_lo); |
| |
| // Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2]. |
| psimd_f32 vp = psimd_qfma_f32(vc4, vc5, vt); |
| vp = psimd_qfma_f32(vc3, vp, vt); |
| vp = psimd_qfma_f32(vc2, vp, vt); |
| vp = psimd_qfma_f32(vc1, vp, vt); |
| |
| // 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 = psimd_mul_f32(vt, vs); |
| psimd_f32 vf = psimd_qfma_f32(vs, vt, vp); |
| |
| // 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 = psimd_andnotmask_f32(vx < vdenorm_cutoff, vf); |
| |
| if (elements & (2 * sizeof(float))) { |
| // Store 2 outputs at a time. |
| psimd_store2_f32(output, vf); |
| output += 2; |
| |
| // Accumulate 2 computed exponents. |
| vacc = psimd_add_f32(vacc, psimd_concat_lo_f32(vf, psimd_zero_f32())); |
| |
| vf = psimd_concat_hi_f32(vf, vf); |
| } |
| if (elements & (1 * sizeof(float))) { |
| // Store 1 output at a time. |
| psimd_store1_f32(output, vf); |
| |
| // Accumulate 1 computed exponent. |
| const psimd_f32 vzero = psimd_zero_f32(); |
| vf = psimd_concat_lo_f32(vf, vzero); |
| vf = psimd_concat_even_f32(vf, vzero); |
| vacc = psimd_add_f32(vacc, vf); |
| } |
| } |
| // Reduce 4 elements in the SIMD register |
| *sum = psimd_reduce_sum_f32(vacc); |
| } |