src/gpu/ganesh/tessellate/GrTessellationShader.cpp

/*
 * Copyright 2021 Google LLC.
 *
 * Use of this source code is governed by a BSD-style license that can be
 * found in the LICENSE file.
 */

#include "src/gpu/ganesh/tessellate/GrTessellationShader.h"

#include "src/gpu/tessellate/WangsFormula.h"

const GrPipeline* GrTessellationShader::MakePipeline(const ProgramArgs& args,
                                                     GrAAType aaType,
                                                     GrAppliedClip&& appliedClip,
                                                     GrProcessorSet&& processors) {
    GrPipeline::InitArgs pipelineArgs;

    pipelineArgs.fCaps = args.fCaps;
    pipelineArgs.fDstProxyView = *args.fDstProxyView;
    pipelineArgs.fWriteSwizzle = args.fWriteView.swizzle();

    return args.fArena->make<GrPipeline>(pipelineArgs,
                                         std::move(processors),
                                         std::move(appliedClip));
}

const char* GrTessellationShader::WangsFormulaSkSL() {
    static_assert(skgpu::wangs_formula::length_term<3>(1) == 0.75);
    static_assert(skgpu::wangs_formula::length_term_pow2<3>(1) == 0.5625);

    return R"(
// Returns the length squared of the largest forward difference from Wang's cubic formula.
float wangs_formula_max_fdiff_pow2(float2 p0, float2 p1, float2 p2, float2 p3,
                                   float2x2 matrix) {
    float2 d0 = matrix * (fma(float2(-2), p1, p2) + p0);
    float2 d1 = matrix * (fma(float2(-2), p2, p3) + p1);
    return max(dot(d0,d0), dot(d1,d1));
}
float wangs_formula_cubic(float _precision_, float2 p0, float2 p1, float2 p2, float2 p3,
                          float2x2 matrix) {
    float m = wangs_formula_max_fdiff_pow2(p0, p1, p2, p3, matrix);
    return max(ceil(sqrt(0.75 * _precision_ * sqrt(m))), 1.0);
}
float wangs_formula_cubic_log2(float _precision_, float2 p0, float2 p1, float2 p2, float2 p3,
                               float2x2 matrix) {
    float m = wangs_formula_max_fdiff_pow2(p0, p1, p2, p3, matrix);
    return ceil(log2(max(0.5625 * _precision_ * _precision_ * m, 1.0)) * .25);
}
float wangs_formula_conic_pow2(float _precision_, float2 p0, float2 p1, float2 p2, float w) {
    // Translate the bounding box center to the origin.
    float2 C = (min(min(p0, p1), p2) + max(max(p0, p1), p2)) * 0.5;
    p0 -= C;
    p1 -= C;
    p2 -= C;

    // Compute max length.
    float m = sqrt(max(max(dot(p0,p0), dot(p1,p1)), dot(p2,p2)));

    // Compute forward differences.
    float2 dp = fma(float2(-2.0 * w), p1, p0) + p2;
    float dw = abs(fma(-2.0, w, 2.0));

    // Compute numerator and denominator for parametric step size of linearization. Here, the
    // epsilon referenced from the cited paper is 1/precision.
    float rp_minus_1 = max(0.0, fma(m, _precision_, -1.0));
    float numer = length(dp) * _precision_ + rp_minus_1 * dw;
    float denom = 4 * min(w, 1.0);

    return numer/denom;
}
float wangs_formula_conic(float _precision_, float2 p0, float2 p1, float2 p2, float w) {
    float n2 = wangs_formula_conic_pow2(_precision_, p0, p1, p2, w);
    return max(ceil(sqrt(n2)), 1.0);
}
float wangs_formula_conic_log2(float _precision_, float2 p0, float2 p1, float2 p2, float w) {
    float n2 = wangs_formula_conic_pow2(_precision_, p0, p1, p2, w);
    return ceil(log2(max(n2, 1.0)) * .5);
})";
}