| // 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 <stddef.h> |
| |
| #include <arm_neon.h> |
| |
| #include <xnnpack/common.h> |
| #include <xnnpack/math-stubs.h> |
| |
| |
| // Table of exp2(k / 64) values decremented (as integer) by (k << 17), k = 0..63 |
| extern XNN_INTERNAL const float xnn_table_exp2minus_k_over_64[64]; |
| |
| void xnn_math_f32_expminus__neonfma_lut64_p2( |
| size_t n, |
| const float* input, |
| float* output) |
| { |
| assert(n % (4 * sizeof(float)) == 0); |
| |
| const float32x4_t vmagic_bias = vmovq_n_f32(0x1.800000p23f); |
| // The smallest x for which expf(x) is normalized. |
| const float32x4_t vdenorm_cutoff = vmovq_n_f32(-0x1.5D589Ep6f); |
| const float32x4_t vlog2e_x64 = vmovq_n_f32(0x1.715476p6f); |
| const float32x4_t vminus_ln2_o64_hi = vmovq_n_f32(-0x1.62e43p-7f); |
| const float32x4_t vminus_ln2_o64_lo = vmovq_n_f32(0x1.05c61p-35f); |
| |
| const float32x4_t vc2 = vmovq_n_f32(0x1.FFFF0Ap-2f); |
| |
| const int32x4_t vindex_mask = vmovq_n_s32(INT32_C(0x3F)); |
| |
| for (; n != 0; n -= 4 * sizeof(float)) { |
| const float32x4_t vx = vld1q_f32(input); input += 4; |
| |
| // Compute reduced argument n := round(x * 64 / log(2)). |
| // We do it by adding a large number (magic bias), which cause rounding of the result to an integer, then subtracing |
| // the large number back. The first addition is combined with multiplication by log2e into a single FMA instruction. |
| // The trick with adding large number is valid only within certain bounds (|x * 64 / log(2)| <= 2**22, i.e. |
| // |x| <= 0x1.62E43p+15 = 45426.09375), but that is acceptable, because inputs outside of [-87.336540, 0.0] |
| // result in denormalized or underflown expf(x). We fixup the result for such inputs at the very end of the |
| // algorithm. |
| float32x4_t vn = vfmaq_f32(vmagic_bias, vx, vlog2e_x64); |
| |
| // Create a floating-point number s (scale) such that s := 2**(n / 64) for such inputs that expf(x) is normalized, |
| // i.e. -87.33642 <= x <= 0.0. As n has 6 fractional bits, we split s == 2**(n / 64) = 2**e * 2**(n / 64 - e), where |
| // e := int(n / 64). We create s in two steps: |
| // 1. Fetch 2**(n / 64 - e) = 2**(n % 64) 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 e to its floating-point exponent. The result is always a normalized |
| // number, because for -87.33642 <= x <= 0.0 (inputs for which expf(x) is normalized) we have -126 <= e <= 0, |
| // and thus the adjusted exponent is not lower than -126. |
| // |
| // Shift bits 6:14 into 23:31 (position of floating-point exponent). |
| const int32x4_t ve = vshlq_n_s32(vreinterpretq_s32_f32(vn), 17); |
| |
| // Use bits 0:6 bits of n, as integer, as an index for table lookup of l := 2**(n % 64). |
| const uint64x2_t vidx = vreinterpretq_u64_s32(vshlq_n_s32(vandq_s32(vreinterpretq_s32_f32(vn), vindex_mask), 2)); |
| const uint64_t vidx01 = vgetq_lane_u64(vidx, 0); |
| const uint64_t vidx23 = vgetq_lane_u64(vidx, 1); |
| float32x2_t vl01 = vld1_dup_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) vidx01)); |
| float32x2_t vl23 = vld1_dup_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) vidx23)); |
| vl01 = vld1_lane_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) (vidx01 >> 32)), vl01, 1); |
| vl23 = vld1_lane_f32((const float*) ((uintptr_t) xnn_table_exp2minus_k_over_64 + (uint32_t) (vidx23 >> 32)), vl23, 1); |
| const float32x4_t vl = vcombine_f32(vl01, vl23); |
| // Adjust exponent of the value l fetched from the table to get the final s value. |
| const float32x4_t vs = vreinterpretq_f32_s32(vaddq_s32(vreinterpretq_s32_f32(vl), ve)); |
| |
| // Subtract the large number back to get final n := round(x * 64 / log(2)) as a floating-point number. |
| vn = vsubq_f32(vn, vmagic_bias); |
| |
| // Compute reduced argument t := x - n * log(2) / 64. |
| // Use Cody-Waite range reduction method (note the two constants representing log(2) / 64) to improve accuracy. |
| float32x4_t vt = vfmaq_f32(vx, vn, vminus_ln2_o64_hi); |
| vt = vfmaq_f32(vt, vn, vminus_ln2_o64_lo); |
| |
| // Compute degree-2 polynomial approxiatmion for exp(t) on [-log(2)/128, log(2)/128]. |
| float32x4_t vp = vmulq_f32(vt, vc2); |
| vp = vfmaq_f32(vt, vt, vp); |
| |
| // Reconstruct the final f value: |
| // f = s * (1 + t * (1 + t * c2)) |
| // = s * (1 + t + t * (t * c2)) |
| // = s + s * (t + t * (t * c2)) |
| // = s + s * p |
| float32x4_t vf = vfmaq_f32(vs, vs, vp); |
| |
| // For inputs below denormal cutoff, replace output with +0.0f. |
| // Note that for NaN inputs, comparison result is false, and outputs are left unchanged. |
| vf = vreinterpretq_f32_u32(vbicq_u32(vreinterpretq_u32_f32(vf), vcltq_f32(vx, vdenorm_cutoff))); |
| vst1q_f32(output, vf); output += 4; |
| } |
| } |