// 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 #include #include #include void xnn_math_f32_extexp__avx2_p5( size_t n, const float* input, float* output_mantissa, float* output_exponent) { assert(n % (8 * sizeof(float)) == 0); 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 vc0 = _mm256_set1_ps(1.0f); 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); for (; n != 0; n -= 8 * sizeof(float)) { const __m256 vx = _mm256_loadu_ps(input); // Compute reduced argument n := round(x / log(2)). const __m256 vn = _mm256_round_ps(_mm256_mul_ps(vx, vlog2e), _MM_FROUND_TO_NEAREST_INT | _MM_FROUND_NO_EXC); // Compute reduced argument t := x - n * 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 approximation 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); vp = _mm256_fmadd_ps(vp, vt, vc0); // Skip reconstruction step and separately store "mantissa" and "exponent" of the output. _mm256_storeu_ps(output_mantissa, vp); _mm256_storeu_ps(output_exponent, vn); input += 8; output_mantissa += 8; output_exponent += 8; } }