// 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 #include // Table of exp2(k / 64) values decremented (as integer) by (k << 17), k = 0..63 extern XNN_INTERNAL const uint32_t xnn_table_exp2minus_k_over_64[64]; void xnn_math_f32_expminus__scalar_rr2_lut64_p2( size_t n, const float* input, float* output) { assert(n % sizeof(float) == 0); // Large number such that ulp(magic bias) == exp2(-6) const float vmagic_bias = 0x1.800000p17f; const float vlog2e = 0x1.715476p0f; // Mask for the lowest 6 bits const uint32_t vindex_mask = UINT32_C(0x3F); // Last 13 bits are zeroes const float vminus_ln2_hi = -0x1.630000p-1f; const float vminus_ln2_lo = 0x1.BD0106p-13f; // Coefficient of polynomial approximation // exp(t) ~ 1 + t * (1 + t * c2) // on [-log(2)/128, log(2)/128] const float vc2 = 0x1.FFFF0Ap-2f; // The smallest x for which expf(x) is normalized. const float vdenorm_cutoff = -0x1.5D589Ep6f; for (; n != 0; n -= sizeof(float)) { const float vx = *input++; // Compute reduced argument n := round(x / log(2), 6). // We do it by adding a large number (magic bias), which cause rounding of the result to 6 fractional bits, then // subtracing the large number back. The trick with adding large number is valid only within certain bounds // (|x / log(2)| <= 2**16, i.e. |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs x // outside of [-87.336544, 0] underflow expf(x). We fixup the result for such inputs at the very end of the // algorithm. float vn = vx * vlog2e + vmagic_bias; // Create a floating-point number s (scale) such that s := 2**n for such inputs that expf(x) is normalized, i.e. // -87.336544 <= x <= 0. As n has 6 fractional bits, we split s == 2**n = 2**int(n) * 2**frac(n). We create s in // two steps: // 1. Fetch 2**frac(n) from the table using the 6 low bits of n, as integer. Note that the fetched values are in // the [1.0, 2.0) range, i.e. their floating-point exponent is 0. // 2. Adjust fecthed value by addition of int(n) to its floating-point exponent. The result is always a normalized // number, because for -87.33642 <= x <= 0 (inputs for which expf(x) is normalized) we have -126 <= int(n) <= 0, // and thus the adjusted exponent is not lower than -126. // // Shift bits 6:14 into 23:31 (position of floating-point exponent). const uint32_t ve = fp32_to_bits(vn) << 17; // Use bits 0:6 of n, as integer, as an index for table lookup of l := 2**frac(n). const uint32_t vidx = fp32_to_bits(vn) & vindex_mask; // Adjust exponent of the value l fetched from the table to get the final s value. const float vs = fp32_from_bits(xnn_table_exp2minus_k_over_64[vidx] + ve); // Subtract the large number back to get the final n := round(x / log(2), 6) as a floating-point number. vn -= vmagic_bias; // Compute reduced argument t := x - n * log(2) // Use Cody-Waite range reduction method (note the two constants representing log(2)) to improve accuracy. float vt = vn * vminus_ln2_hi + vx; vt = vn * vminus_ln2_lo + vt; // Compute degree-2 polynomial approximation for exp(t) on [-log(2)/128, log(2)/128]. // P(t) = 1 + t * (1 + t * c2) = 1 + (t + t * (t * c2)) = 1 + p float vp = vt * vc2; vp = vp * vt + vt; // Reconstruct the exp(x) value: // exp(x) = s * (1 + t * (1 + t * c2)) // = s * (1 + p) // = s + s * p float vf = vp * vs + vs; // For inputs below denormal cutoff, replace output with +0.0f. // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. if XNN_UNPREDICTABLE(vx < vdenorm_cutoff) { vf = 0.0f; } *output++ = vf; } }