// SPDX-License-Identifier: Apache-2.0 // ---------------------------------------------------------------------------- // Copyright 2011-2021 Arm Limited // // Licensed under the Apache License, Version 2.0 (the "License"); you may not // use this file except in compliance with the License. You may obtain a copy // of the License at: // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, WITHOUT // WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the // License for the specific language governing permissions and limitations // under the License. // ---------------------------------------------------------------------------- /** * @brief Functions for finding dominant direction of a set of colors. */ #if !defined(ASTCENC_DECOMPRESS_ONLY) #include "astcenc_internal.h" #include /* See header for documentation. */ void compute_avgs_and_dirs_4_comp( const partition_info& pi, const image_block& blk, const error_weight_block& ewb, partition_metrics pm[BLOCK_MAX_PARTITIONS] ) { int partition_count = pi.partition_count; promise(partition_count > 0); for (int partition = 0; partition < partition_count; partition++) { const uint8_t *weights = pi.texels_of_partition[partition]; vfloat4 error_sum = vfloat4::zero(); vfloat4 base_sum = vfloat4::zero(); vfloat4 rgba_min(1e38f); vfloat4 rgba_max(-1e38f); float partition_weight = 0.0f; int texel_count = pi.partition_texel_count[partition]; promise(texel_count > 0); for (int i = 0; i < texel_count; i++) { int iwt = weights[i]; float weight = ewb.texel_weight[iwt]; vfloat4 texel_datum = blk.texel(iwt); vfloat4 error_weight = ewb.error_weights[iwt]; if (weight > 1e-10f) { rgba_min = min(texel_datum, rgba_min); rgba_max = max(texel_datum, rgba_max); } partition_weight += weight; base_sum += texel_datum * weight; error_sum += error_weight; } error_sum = error_sum / texel_count; vfloat4 csf = normalize(sqrt(error_sum)) * 2.0f; vfloat4 average = base_sum * (1.0f / astc::max(partition_weight, 1e-7f)); pm[partition].error_weight = error_sum; pm[partition].avg = average * csf; pm[partition].color_scale = csf; pm[partition].icolor_scale = 1.0f / max(csf, 1e-7f); vfloat4 range = max(rgba_max - rgba_min, 1e-10f); pm[partition].range_sq = range * range; vfloat4 sum_xp = vfloat4::zero(); vfloat4 sum_yp = vfloat4::zero(); vfloat4 sum_zp = vfloat4::zero(); vfloat4 sum_wp = vfloat4::zero(); for (int i = 0; i < texel_count; i++) { int iwt = weights[i]; float weight = ewb.texel_weight[iwt]; vfloat4 texel_datum = blk.texel(iwt); texel_datum = (texel_datum - average) * weight; vfloat4 zero = vfloat4::zero(); vmask4 tdm0 = vfloat4(texel_datum.lane<0>()) > zero; sum_xp += select(zero, texel_datum, tdm0); vmask4 tdm1 = vfloat4(texel_datum.lane<1>()) > zero; sum_yp += select(zero, texel_datum, tdm1); vmask4 tdm2 = vfloat4(texel_datum.lane<2>()) > zero; sum_zp += select(zero, texel_datum, tdm2); vmask4 tdm3 = vfloat4(texel_datum.lane<3>()) > zero; sum_wp += select(zero, texel_datum, tdm3); } float prod_xp = dot_s(sum_xp, sum_xp); float prod_yp = dot_s(sum_yp, sum_yp); float prod_zp = dot_s(sum_zp, sum_zp); float prod_wp = dot_s(sum_wp, sum_wp); vfloat4 best_vector = sum_xp; float best_sum = prod_xp; if (prod_yp > best_sum) { best_vector = sum_yp; best_sum = prod_yp; } if (prod_zp > best_sum) { best_vector = sum_zp; best_sum = prod_zp; } if (prod_wp > best_sum) { best_vector = sum_wp; } pm[partition].dir = best_vector; } } /* See header for documentation. */ void compute_avgs_and_dirs_3_comp( const partition_info& pi, const image_block& blk, const error_weight_block& ewb, unsigned int omitted_component, partition_metrics pm[BLOCK_MAX_PARTITIONS] ) { const float *texel_weights = ewb.texel_weight_rgb; const float* data_vr = blk.data_r; const float* data_vg = blk.data_g; const float* data_vb = blk.data_b; const float* error_vr = ewb.texel_weight_r; const float* error_vg = ewb.texel_weight_g; const float* error_vb = ewb.texel_weight_b; if (omitted_component == 0) { texel_weights = ewb.texel_weight_gba; data_vr = blk.data_g; data_vg = blk.data_b; data_vb = blk.data_a; error_vr = ewb.texel_weight_g; error_vg = ewb.texel_weight_b; error_vb = ewb.texel_weight_a; } else if (omitted_component == 1) { texel_weights = ewb.texel_weight_rba; data_vg = blk.data_b; data_vb = blk.data_a; error_vg = ewb.texel_weight_b; error_vb = ewb.texel_weight_a; } else if (omitted_component == 2) { texel_weights = ewb.texel_weight_rga; data_vb = blk.data_a; error_vb = ewb.texel_weight_a; } int partition_count = pi.partition_count; promise(partition_count > 0); for (int partition = 0; partition < partition_count; partition++) { const uint8_t *weights = pi.texels_of_partition[partition]; vfloat4 error_sum = vfloat4::zero(); vfloat4 base_sum = vfloat4::zero(); vfloat4 rgb_min(1e38f); vfloat4 rgb_max(-1e38f); float partition_weight = 0.0f; int texel_count = pi.partition_texel_count[partition]; promise(texel_count > 0); for (int i = 0; i < texel_count; i++) { int iwt = weights[i]; float weight = texel_weights[iwt]; vfloat4 texel_datum(data_vr[iwt], data_vg[iwt], data_vb[iwt], 0.0f); vfloat4 error_weight(error_vr[iwt], error_vg[iwt], error_vb[iwt], 0.0f); if (weight > 1e-10f) { rgb_min = min(texel_datum, rgb_min); rgb_max = max(texel_datum, rgb_max); } partition_weight += weight; base_sum += texel_datum * weight; error_sum += error_weight; } error_sum = error_sum / texel_count; vfloat4 csf = normalize(sqrt(error_sum)) * 1.73205080f; vfloat4 average = base_sum * (1.0f / astc::max(partition_weight, 1e-7f)); pm[partition].error_weight = error_sum; pm[partition].avg = average * csf; pm[partition].color_scale = csf; pm[partition].icolor_scale = 1.0f / max(csf, 1e-7f); vfloat4 range = max(rgb_max - rgb_min, 1e-10f); pm[partition].range_sq = range * range; vfloat4 sum_xp = vfloat4::zero(); vfloat4 sum_yp = vfloat4::zero(); vfloat4 sum_zp = vfloat4::zero(); for (int i = 0; i < texel_count; i++) { int iwt = weights[i]; float weight = texel_weights[iwt]; vfloat4 texel_datum = vfloat3(data_vr[iwt], data_vg[iwt], data_vb[iwt]); texel_datum = (texel_datum - average) * weight; vfloat4 zero = vfloat4::zero(); vmask4 tdm0 = vfloat4(texel_datum.lane<0>()) > zero; sum_xp += select(zero, texel_datum, tdm0); vmask4 tdm1 = vfloat4(texel_datum.lane<1>()) > zero; sum_yp += select(zero, texel_datum, tdm1); vmask4 tdm2 = vfloat4(texel_datum.lane<2>()) > zero; sum_zp += select(zero, texel_datum, tdm2); } float prod_xp = dot3_s(sum_xp, sum_xp); float prod_yp = dot3_s(sum_yp, sum_yp); float prod_zp = dot3_s(sum_zp, sum_zp); vfloat4 best_vector = sum_xp; float best_sum = prod_xp; if (prod_yp > best_sum) { best_vector = sum_yp; best_sum = prod_yp; } if (prod_zp > best_sum) { best_vector = sum_zp; } pm[partition].dir = best_vector; } } /* See header for documentation. */ void compute_avgs_and_dirs_2_comp( const partition_info& pt, const image_block& blk, const error_weight_block& ewb, unsigned int component1, unsigned int component2, partition_metrics pm[BLOCK_MAX_PARTITIONS] ) { const float *texel_weights; const float* data_vr = nullptr; const float* data_vg = nullptr; const float* error_vr = nullptr; const float* error_vg = nullptr; if (component1 == 0 && component2 == 1) { texel_weights = ewb.texel_weight_rg; data_vr = blk.data_r; data_vg = blk.data_g; error_vr = ewb.texel_weight_r; error_vg = ewb.texel_weight_g; } else if (component1 == 0 && component2 == 2) { texel_weights = ewb.texel_weight_rb; data_vr = blk.data_r; data_vg = blk.data_b; error_vr = ewb.texel_weight_r; error_vg = ewb.texel_weight_b; } else // (component1 == 1 && component2 == 2) { assert(component1 == 1 && component2 == 2); texel_weights = ewb.texel_weight_gb; data_vr = blk.data_g; data_vg = blk.data_b; error_vr = ewb.texel_weight_g; error_vg = ewb.texel_weight_b; } unsigned int partition_count = pt.partition_count; promise(partition_count > 0); for (unsigned int partition = 0; partition < partition_count; partition++) { const uint8_t *weights = pt.texels_of_partition[partition]; vfloat4 error_sum = vfloat4::zero(); vfloat4 base_sum = vfloat4::zero(); float partition_weight = 0.0f; unsigned int texel_count = pt.partition_texel_count[partition]; promise(texel_count > 0); for (unsigned int i = 0; i < texel_count; i++) { unsigned int iwt = weights[i]; float weight = texel_weights[iwt]; vfloat4 texel_datum = vfloat2(data_vr[iwt], data_vg[iwt]) * weight; vfloat4 error_weight = vfloat2(error_vr[iwt], error_vg[iwt]); partition_weight += weight; base_sum += texel_datum; error_sum += error_weight; } error_sum = error_sum / texel_count; vfloat4 csf = normalize(sqrt(error_sum)) * 1.41421356f; vfloat4 average = base_sum * (1.0f / astc::max(partition_weight, 1e-7f)); pm[partition].error_weight = error_sum; pm[partition].avg = average * csf; pm[partition].color_scale = csf; pm[partition].icolor_scale = 1.0f / max(csf, 1e-7f); vfloat4 sum_xp = vfloat4::zero(); vfloat4 sum_yp = vfloat4::zero(); for (unsigned int i = 0; i < texel_count; i++) { unsigned int iwt = weights[i]; float weight = texel_weights[iwt]; vfloat4 texel_datum = vfloat2(data_vr[iwt], data_vg[iwt]); texel_datum = (texel_datum - average) * weight; vfloat4 zero = vfloat4::zero(); vmask4 tdm0 = vfloat4(texel_datum.lane<0>()) > zero; sum_xp += select(zero, texel_datum, tdm0); vmask4 tdm1 = vfloat4(texel_datum.lane<1>()) > zero; sum_yp += select(zero, texel_datum, tdm1); } float prod_xp = dot_s(sum_xp, sum_xp); float prod_yp = dot_s(sum_yp, sum_yp); vfloat4 best_vector = sum_xp; float best_sum = prod_xp; if (prod_yp > best_sum) { best_vector = sum_yp; } pm[partition].dir = best_vector; } } /* See header for documentation. */ void compute_error_squared_rgba( const partition_info& pi, const image_block& blk, const error_weight_block& ewb, const processed_line4 uncor_plines[BLOCK_MAX_PARTITIONS], const processed_line4 samec_plines[BLOCK_MAX_PARTITIONS], float uncor_lengths[BLOCK_MAX_PARTITIONS], float samec_lengths[BLOCK_MAX_PARTITIONS], float& uncor_error, float& samec_error ) { unsigned int partition_count = pi.partition_count; promise(partition_count > 0); uncor_error = 0.0f; samec_error = 0.0f; for (unsigned int partition = 0; partition < partition_count; partition++) { const uint8_t *weights = pi.texels_of_partition[partition]; float uncor_loparam = 1e10f; float uncor_hiparam = -1e10f; float samec_loparam = 1e10f; float samec_hiparam = -1e10f; processed_line4 l_uncor = uncor_plines[partition]; processed_line4 l_samec = samec_plines[partition]; unsigned int texel_count = pi.partition_texel_count[partition]; promise(texel_count > 0); // Vectorize some useful scalar inputs vfloat l_uncor_bs0(l_uncor.bs.lane<0>()); vfloat l_uncor_bs1(l_uncor.bs.lane<1>()); vfloat l_uncor_bs2(l_uncor.bs.lane<2>()); vfloat l_uncor_bs3(l_uncor.bs.lane<3>()); vfloat l_uncor_amod0(l_uncor.amod.lane<0>()); vfloat l_uncor_amod1(l_uncor.amod.lane<1>()); vfloat l_uncor_amod2(l_uncor.amod.lane<2>()); vfloat l_uncor_amod3(l_uncor.amod.lane<3>()); vfloat l_uncor_bis0(l_uncor.bis.lane<0>()); vfloat l_uncor_bis1(l_uncor.bis.lane<1>()); vfloat l_uncor_bis2(l_uncor.bis.lane<2>()); vfloat l_uncor_bis3(l_uncor.bis.lane<3>()); vfloat l_samec_bs0(l_samec.bs.lane<0>()); vfloat l_samec_bs1(l_samec.bs.lane<1>()); vfloat l_samec_bs2(l_samec.bs.lane<2>()); vfloat l_samec_bs3(l_samec.bs.lane<3>()); assert(all(l_samec.amod == vfloat4(0.0f))); vfloat l_samec_bis0(l_samec.bis.lane<0>()); vfloat l_samec_bis1(l_samec.bis.lane<1>()); vfloat l_samec_bis2(l_samec.bis.lane<2>()); vfloat l_samec_bis3(l_samec.bis.lane<3>()); vfloat uncor_loparamv(1e10f); vfloat uncor_hiparamv(-1e10f); vfloat4 uncor_errorsumv = vfloat4::zero(); vfloat samec_loparamv(1e10f); vfloat samec_hiparamv(-1e10f); vfloat4 samec_errorsumv = vfloat4::zero(); // This implementation over-shoots, but this is safe as we initialize the weights array // to extend the last value. This means min/max are not impacted, but we need to mask // out the dummy values when we compute the line weighting. vint lane_ids = vint::lane_id(); for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH) { vmask mask = lane_ids < vint(texel_count); vint texel_idxs(&(weights[i])); vfloat data_r = gatherf(blk.data_r, texel_idxs); vfloat data_g = gatherf(blk.data_g, texel_idxs); vfloat data_b = gatherf(blk.data_b, texel_idxs); vfloat data_a = gatherf(blk.data_a, texel_idxs); vfloat ew_r = gatherf(ewb.texel_weight_r, texel_idxs); vfloat ew_g = gatherf(ewb.texel_weight_g, texel_idxs); vfloat ew_b = gatherf(ewb.texel_weight_b, texel_idxs); vfloat ew_a = gatherf(ewb.texel_weight_a, texel_idxs); vfloat uncor_param = (data_r * l_uncor_bs0) + (data_g * l_uncor_bs1) + (data_b * l_uncor_bs2) + (data_a * l_uncor_bs3); uncor_loparamv = min(uncor_param, uncor_loparamv); uncor_hiparamv = max(uncor_param, uncor_hiparamv); vfloat uncor_dist0 = (l_uncor_amod0 - data_r) + (uncor_param * l_uncor_bis0); vfloat uncor_dist1 = (l_uncor_amod1 - data_g) + (uncor_param * l_uncor_bis1); vfloat uncor_dist2 = (l_uncor_amod2 - data_b) + (uncor_param * l_uncor_bis2); vfloat uncor_dist3 = (l_uncor_amod3 - data_a) + (uncor_param * l_uncor_bis3); vfloat uncor_err = (ew_r * uncor_dist0 * uncor_dist0) + (ew_g * uncor_dist1 * uncor_dist1) + (ew_b * uncor_dist2 * uncor_dist2) + (ew_a * uncor_dist3 * uncor_dist3); uncor_err = select(vfloat::zero(), uncor_err, mask); haccumulate(uncor_errorsumv, uncor_err); // Process samechroma data vfloat samec_param = (data_r * l_samec_bs0) + (data_g * l_samec_bs1) + (data_b * l_samec_bs2) + (data_a * l_samec_bs3); samec_loparamv = min(samec_param, samec_loparamv); samec_hiparamv = max(samec_param, samec_hiparamv); vfloat samec_dist0 = samec_param * l_samec_bis0 - data_r; vfloat samec_dist1 = samec_param * l_samec_bis1 - data_g; vfloat samec_dist2 = samec_param * l_samec_bis2 - data_b; vfloat samec_dist3 = samec_param * l_samec_bis3 - data_a; vfloat samec_err = (ew_r * samec_dist0 * samec_dist0) + (ew_g * samec_dist1 * samec_dist1) + (ew_b * samec_dist2 * samec_dist2) + (ew_a * samec_dist3 * samec_dist3); samec_err = select(vfloat::zero(), samec_err, mask); haccumulate(samec_errorsumv, samec_err); lane_ids = lane_ids + vint(ASTCENC_SIMD_WIDTH); } uncor_loparam = hmin_s(uncor_loparamv); uncor_hiparam = hmax_s(uncor_hiparamv); samec_loparam = hmin_s(samec_loparamv); samec_hiparam = hmax_s(samec_hiparamv); // Resolve the final scalar accumulator sum haccumulate(uncor_error, uncor_errorsumv); haccumulate(samec_error, samec_errorsumv); float uncor_linelen = uncor_hiparam - uncor_loparam; float samec_linelen = samec_hiparam - samec_loparam; // Turn very small numbers and NaNs into a small number uncor_lengths[partition] = astc::max(uncor_linelen, 1e-7f); samec_lengths[partition] = astc::max(samec_linelen, 1e-7f); } } /* See header for documentation. */ void compute_error_squared_rgb( const partition_info& pi, const image_block& blk, const error_weight_block& ewb, partition_lines3 plines[BLOCK_MAX_PARTITIONS], float& uncor_error, float& samec_error ) { unsigned int partition_count = pi.partition_count; promise(partition_count > 0); uncor_error = 0.0f; samec_error = 0.0f; for (unsigned int partition = 0; partition < partition_count; partition++) { partition_lines3& pl = plines[partition]; const uint8_t *weights = pi.texels_of_partition[partition]; unsigned int texel_count = pi.partition_texel_count[partition]; promise(texel_count > 0); float uncor_loparam = 1e10f; float uncor_hiparam = -1e10f; float samec_loparam = 1e10f; float samec_hiparam = -1e10f; processed_line3 l_uncor = pl.uncor_pline; processed_line3 l_samec = pl.samec_pline; // This implementation is an example vectorization of this function. // It works for - the codec is a 2-4% faster than not vectorizing - but // the benefit is limited by the use of gathers and register pressure // Vectorize some useful scalar inputs vfloat l_uncor_bs0(l_uncor.bs.lane<0>()); vfloat l_uncor_bs1(l_uncor.bs.lane<1>()); vfloat l_uncor_bs2(l_uncor.bs.lane<2>()); vfloat l_uncor_amod0(l_uncor.amod.lane<0>()); vfloat l_uncor_amod1(l_uncor.amod.lane<1>()); vfloat l_uncor_amod2(l_uncor.amod.lane<2>()); vfloat l_uncor_bis0(l_uncor.bis.lane<0>()); vfloat l_uncor_bis1(l_uncor.bis.lane<1>()); vfloat l_uncor_bis2(l_uncor.bis.lane<2>()); vfloat l_samec_bs0(l_samec.bs.lane<0>()); vfloat l_samec_bs1(l_samec.bs.lane<1>()); vfloat l_samec_bs2(l_samec.bs.lane<2>()); assert(all(l_samec.amod == vfloat4(0.0f))); vfloat l_samec_bis0(l_samec.bis.lane<0>()); vfloat l_samec_bis1(l_samec.bis.lane<1>()); vfloat l_samec_bis2(l_samec.bis.lane<2>()); vfloat uncor_loparamv(1e10f); vfloat uncor_hiparamv(-1e10f); vfloat4 uncor_errorsumv = vfloat4::zero(); vfloat samec_loparamv(1e10f); vfloat samec_hiparamv(-1e10f); vfloat4 samec_errorsumv = vfloat4::zero(); // This implementation over-shoots, but this is safe as we initialize the weights array // to extend the last value. This means min/max are not impacted, but we need to mask // out the dummy values when we compute the line weighting. vint lane_ids = vint::lane_id(); for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH) { vmask mask = lane_ids < vint(texel_count); vint texel_idxs(&(weights[i])); vfloat data_r = gatherf(blk.data_r, texel_idxs); vfloat data_g = gatherf(blk.data_g, texel_idxs); vfloat data_b = gatherf(blk.data_b, texel_idxs); vfloat ew_r = gatherf(ewb.texel_weight_r, texel_idxs); vfloat ew_g = gatherf(ewb.texel_weight_g, texel_idxs); vfloat ew_b = gatherf(ewb.texel_weight_b, texel_idxs); vfloat uncor_param = (data_r * l_uncor_bs0) + (data_g * l_uncor_bs1) + (data_b * l_uncor_bs2); uncor_loparamv = min(uncor_param, uncor_loparamv); uncor_hiparamv = max(uncor_param, uncor_hiparamv); vfloat uncor_dist0 = (l_uncor_amod0 - data_r) + (uncor_param * l_uncor_bis0); vfloat uncor_dist1 = (l_uncor_amod1 - data_g) + (uncor_param * l_uncor_bis1); vfloat uncor_dist2 = (l_uncor_amod2 - data_b) + (uncor_param * l_uncor_bis2); vfloat uncor_err = (ew_r * uncor_dist0 * uncor_dist0) + (ew_g * uncor_dist1 * uncor_dist1) + (ew_b * uncor_dist2 * uncor_dist2); uncor_err = select(vfloat::zero(), uncor_err, mask); haccumulate(uncor_errorsumv, uncor_err); // Process samechroma data vfloat samec_param = (data_r * l_samec_bs0) + (data_g * l_samec_bs1) + (data_b * l_samec_bs2); samec_loparamv = min(samec_param, samec_loparamv); samec_hiparamv = max(samec_param, samec_hiparamv); vfloat samec_dist0 = samec_param * l_samec_bis0 - data_r; vfloat samec_dist1 = samec_param * l_samec_bis1 - data_g; vfloat samec_dist2 = samec_param * l_samec_bis2 - data_b; vfloat samec_err = (ew_r * samec_dist0 * samec_dist0) + (ew_g * samec_dist1 * samec_dist1) + (ew_b * samec_dist2 * samec_dist2); samec_err = select(vfloat::zero(), samec_err, mask); haccumulate(samec_errorsumv, samec_err); lane_ids = lane_ids + vint(ASTCENC_SIMD_WIDTH); } uncor_loparam = hmin_s(uncor_loparamv); uncor_hiparam = hmax_s(uncor_hiparamv); samec_loparam = hmin_s(samec_loparamv); samec_hiparam = hmax_s(samec_hiparamv); // Resolve the final scalar accumulator sum haccumulate(uncor_error, uncor_errorsumv); haccumulate(samec_error, samec_errorsumv); float uncor_linelen = uncor_hiparam - uncor_loparam; float samec_linelen = samec_hiparam - samec_loparam; // Turn very small numbers and NaNs into a small number pl.uncor_line_len = astc::max(uncor_linelen, 1e-7f); pl.samec_line_len = astc::max(samec_linelen, 1e-7f); } } #endif