// 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. #include #include #include #include #include #include // Table of exp2(k / 64) values, k = 0..63 extern XNN_INTERNAL const float xnn_table_exp2_k_over_64[64]; void xnn_math_f32_exp__sse2_rr2_lut64_p2( size_t n, const float* input, float* output) { assert(n % (4 * sizeof(float)) == 0); const __m128 vmagic_bias = _mm_set1_ps(0x1.800000p+23f); // The smallest x for which expf(x) is non-zero. const __m128 vzero_cutoff = _mm_set1_ps(-0x1.9FE368p+6f); // The largest x for which expf(x) is finite. const __m128 vinf_cutoff = _mm_set1_ps(0x1.62E42Ep+6f); const __m128 vlog2e_x64 = _mm_set1_ps(0x1.715476p+6f); // Last 13 bits are zeroes const __m128 vminus_ln2_o64_hi = _mm_set1_ps(-0x1.630000p-7f); const __m128 vminus_ln2_o64_lo = _mm_set1_ps(0x1.BD0106p-19f); const __m128 vplus_inf = _mm_set1_ps(INFINITY); const __m128 vc2 = _mm_set1_ps(0x1.FFFF0Ap-2f); const __m128i vmin_exponent = _mm_set1_epi32(0xC1000000); const __m128i vmax_exponent = _mm_set1_epi32(0x3F800000); const __m128i vdefault_exponent = vmax_exponent; const __m128i vindex_mask = _mm_set1_epi32(0x3F); for (; n != 0; n -= 4 * sizeof(float)) { const __m128 vx = _mm_loadu_ps(input); // Compute reduced argument n := round(x * 64 / log(2)). // We do it by adding a large number (magic bias) to the product x * (64/log(2)), which cause rounding of the // result to an integer, then subtracing the large number back. The trick with adding large number is valid only // within certain bounds (|x| <= 2**22), but thats ok, because inputs outside of [-103.97207, 88.72283] underflow // or overflow expf(x) anyway. We fixup the result for such inputs at the very end of the algorithm. __m128 vn = _mm_add_ps(_mm_mul_ps(vx, vlog2e_x64), vmagic_bias); // Create two floating-point numbers, sn (scale, normal) and so (scale, overflow) such that sn * so == 2**n // for inputs which don't cause overflow, i.e. -103.97207 <= x <= 88.72283, and -150 <= n <= 128 accordingly. // We need to use two numbers rather than one because a normalized single-precision exponent must be in [-127, 126] // range, which is insufficient to cover [-150, 128] range of n. // - When n is within [-127, 126], sn == 2**n and so == 1.0. // - When n < -127, sn == 2**(-127) and so == 2**(n + 127). // - When n > 126, sn == 2**126 and so == 2**(n - 126). // While we explicitly compute sn, the so is fused into the value l fetched from a table by adjusting its exponential. __m128i veo = _mm_slli_epi32(_mm_andnot_si128(vindex_mask, _mm_castps_si128(vn)), 17); __m128i ven = _mm_max_epi16(veo, vmin_exponent); ven = _mm_min_epi16(ven, vmax_exponent); veo = _mm_sub_epi32(veo, ven); const __m128 vsn = _mm_castsi128_ps(_mm_add_epi32(ven, vdefault_exponent)); // Use the low 6 bits of n (as integer) for table lookup. const __m128i vidx = _mm_slli_epi32(_mm_and_si128(_mm_castps_si128(vn), vindex_mask), 2); #if XNN_ARCH_X86_64 const uint64_t vidx01 = (uint64_t) _mm_cvtsi128_si64(vidx); const uint64_t vidx23 = (uint64_t) _mm_cvtsi128_si64(_mm_unpackhi_epi64(vidx, vidx)); const __m128i vl0 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) &xnn_table_exp2_k_over_64 + (uint32_t) vidx01))); const __m128i vl2 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + (uint32_t) vidx23))); const __m128i vl1 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + (uint32_t) (vidx01 >> 32)))); const __m128i vl3 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + (uint32_t) (vidx23 >> 32)))); #else const uint32_t vidx0 = (uint32_t) _mm_cvtsi128_si32(vidx); const uint32_t vidx1 = (uint32_t) _mm_extract_epi16(vidx, 2); const uint32_t vidx2 = (uint32_t) _mm_extract_epi16(vidx, 4); const uint32_t vidx3 = (uint32_t) _mm_extract_epi16(vidx, 6); const __m128i vl0 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + vidx0))); const __m128i vl2 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + vidx2))); const __m128i vl1 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + vidx1))); const __m128i vl3 = _mm_cvtsi32_si128(*((const int*) ((uintptr_t) xnn_table_exp2_k_over_64 + vidx3))); #endif // Fuse so into the value l fetched from a table by adjusting its exponential. const __m128 vl = _mm_castsi128_ps(_mm_add_epi32(_mm_unpacklo_epi64(_mm_unpacklo_epi32(vl0, vl1), _mm_unpacklo_epi32(vl2, vl3)), veo)); // Subtract the large number back to get final n := round(x * 64 / log(2)). vn = _mm_sub_ps(vn, vmagic_bias); // Compute reduced argument t := x - n * log(2). // Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy. __m128 vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_o64_hi), vx); vt = _mm_add_ps(_mm_mul_ps(vn, vminus_ln2_o64_lo), vt); // Compute degree-2 polynomial approximation for exp(t) on [-log(2)/128, log(2)/128]. __m128 vp = _mm_mul_ps(vt, vc2); vp = _mm_add_ps(vt, _mm_mul_ps(vt, vp)); // Reconstruct the final f value: // f = sn * (so * l) * (1 + t * (1 + t * c2)) // = sn * (so * l) * (1 + t + t * (t * c2)) // = sn * ((so * l) + (so * l) * (t + t * (t * c2))) __m128 vf = _mm_add_ps(vl, _mm_mul_ps(vl, vp)); vf = _mm_mul_ps(vf, vsn); // 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 = _mm_andnot_ps(_mm_cmplt_ps(vx, vzero_cutoff), vf); // For inputs above inf cutoff, replace output with +inf. // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. const __m128 vm = _mm_cmpgt_ps(vx, vinf_cutoff); vf = _mm_or_ps(_mm_and_ps(vplus_inf, vm), _mm_andnot_ps(vm, vf)); _mm_storeu_ps(output, vf); input += 4; output += 4; } }