Brecht Van Lommel
3669a3e2e9
Something in this update broke the floor() function in CUDA, instead use floorf() like we do everywhere else in the kernel code. Thanks to Ray Molenkamp for identifying the solution.
266 lines
8.3 KiB
C++
266 lines
8.3 KiB
C++
/*
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* Copyright 2017 Blender Foundation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifdef WITH_NANOVDB
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# define NDEBUG /* Disable "assert" in device code */
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# define NANOVDB_USE_INTRINSICS
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# include "nanovdb/NanoVDB.h"
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# include "nanovdb/util/SampleFromVoxels.h"
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#endif
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/* w0, w1, w2, and w3 are the four cubic B-spline basis functions. */
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ccl_device float cubic_w0(float a)
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{
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return (1.0f / 6.0f) * (a * (a * (-a + 3.0f) - 3.0f) + 1.0f);
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}
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ccl_device float cubic_w1(float a)
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{
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return (1.0f / 6.0f) * (a * a * (3.0f * a - 6.0f) + 4.0f);
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}
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ccl_device float cubic_w2(float a)
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{
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return (1.0f / 6.0f) * (a * (a * (-3.0f * a + 3.0f) + 3.0f) + 1.0f);
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}
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ccl_device float cubic_w3(float a)
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{
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return (1.0f / 6.0f) * (a * a * a);
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}
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/* g0 and g1 are the two amplitude functions. */
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ccl_device float cubic_g0(float a)
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{
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return cubic_w0(a) + cubic_w1(a);
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}
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ccl_device float cubic_g1(float a)
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{
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return cubic_w2(a) + cubic_w3(a);
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}
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/* h0 and h1 are the two offset functions */
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ccl_device float cubic_h0(float a)
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{
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return (cubic_w1(a) / cubic_g0(a)) - 1.0f;
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}
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ccl_device float cubic_h1(float a)
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{
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return (cubic_w3(a) / cubic_g1(a)) + 1.0f;
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}
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/* Fast bicubic texture lookup using 4 bilinear lookups, adapted from CUDA samples. */
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template<typename T>
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ccl_device T kernel_tex_image_interp_bicubic(const TextureInfo &info, float x, float y)
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{
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CUtexObject tex = (CUtexObject)info.data;
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x = (x * info.width) - 0.5f;
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y = (y * info.height) - 0.5f;
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float px = floorf(x);
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float py = floorf(y);
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float fx = x - px;
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float fy = y - py;
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float g0x = cubic_g0(fx);
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float g1x = cubic_g1(fx);
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/* Note +0.5 offset to compensate for CUDA linear filtering convention. */
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float x0 = (px + cubic_h0(fx) + 0.5f) / info.width;
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float x1 = (px + cubic_h1(fx) + 0.5f) / info.width;
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float y0 = (py + cubic_h0(fy) + 0.5f) / info.height;
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float y1 = (py + cubic_h1(fy) + 0.5f) / info.height;
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return cubic_g0(fy) * (g0x * tex2D<T>(tex, x0, y0) + g1x * tex2D<T>(tex, x1, y0)) +
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cubic_g1(fy) * (g0x * tex2D<T>(tex, x0, y1) + g1x * tex2D<T>(tex, x1, y1));
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}
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/* Fast tricubic texture lookup using 8 trilinear lookups. */
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template<typename T>
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ccl_device T kernel_tex_image_interp_tricubic(const TextureInfo &info, float x, float y, float z)
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{
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CUtexObject tex = (CUtexObject)info.data;
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x = (x * info.width) - 0.5f;
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y = (y * info.height) - 0.5f;
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z = (z * info.depth) - 0.5f;
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float px = floorf(x);
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float py = floorf(y);
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float pz = floorf(z);
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float fx = x - px;
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float fy = y - py;
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float fz = z - pz;
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float g0x = cubic_g0(fx);
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float g1x = cubic_g1(fx);
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float g0y = cubic_g0(fy);
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float g1y = cubic_g1(fy);
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float g0z = cubic_g0(fz);
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float g1z = cubic_g1(fz);
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/* Note +0.5 offset to compensate for CUDA linear filtering convention. */
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float x0 = (px + cubic_h0(fx) + 0.5f) / info.width;
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float x1 = (px + cubic_h1(fx) + 0.5f) / info.width;
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float y0 = (py + cubic_h0(fy) + 0.5f) / info.height;
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float y1 = (py + cubic_h1(fy) + 0.5f) / info.height;
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float z0 = (pz + cubic_h0(fz) + 0.5f) / info.depth;
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float z1 = (pz + cubic_h1(fz) + 0.5f) / info.depth;
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return g0z * (g0y * (g0x * tex3D<T>(tex, x0, y0, z0) + g1x * tex3D<T>(tex, x1, y0, z0)) +
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g1y * (g0x * tex3D<T>(tex, x0, y1, z0) + g1x * tex3D<T>(tex, x1, y1, z0))) +
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g1z * (g0y * (g0x * tex3D<T>(tex, x0, y0, z1) + g1x * tex3D<T>(tex, x1, y0, z1)) +
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g1y * (g0x * tex3D<T>(tex, x0, y1, z1) + g1x * tex3D<T>(tex, x1, y1, z1)));
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}
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#ifdef WITH_NANOVDB
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template<typename T, typename S>
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ccl_device T kernel_tex_image_interp_tricubic_nanovdb(S &s, float x, float y, float z)
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{
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float px = floorf(x);
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float py = floorf(y);
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float pz = floorf(z);
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float fx = x - px;
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float fy = y - py;
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float fz = z - pz;
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float g0x = cubic_g0(fx);
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float g1x = cubic_g1(fx);
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float g0y = cubic_g0(fy);
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float g1y = cubic_g1(fy);
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float g0z = cubic_g0(fz);
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float g1z = cubic_g1(fz);
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float x0 = px + cubic_h0(fx);
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float x1 = px + cubic_h1(fx);
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float y0 = py + cubic_h0(fy);
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float y1 = py + cubic_h1(fy);
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float z0 = pz + cubic_h0(fz);
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float z1 = pz + cubic_h1(fz);
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using namespace nanovdb;
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return g0z * (g0y * (g0x * s(Vec3f(x0, y0, z0)) + g1x * s(Vec3f(x1, y0, z0))) +
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g1y * (g0x * s(Vec3f(x0, y1, z0)) + g1x * s(Vec3f(x1, y1, z0)))) +
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g1z * (g0y * (g0x * s(Vec3f(x0, y0, z1)) + g1x * s(Vec3f(x1, y0, z1))) +
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g1y * (g0x * s(Vec3f(x0, y1, z1)) + g1x * s(Vec3f(x1, y1, z1))));
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}
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template<typename T>
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ccl_device_inline T kernel_tex_image_interp_nanovdb(
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const TextureInfo &info, float x, float y, float z, uint interpolation)
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{
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using namespace nanovdb;
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NanoGrid<T> *const grid = (NanoGrid<T> *)info.data;
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typedef typename nanovdb::NanoGrid<T>::AccessorType AccessorType;
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AccessorType acc = grid->getAccessor();
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switch (interpolation) {
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case INTERPOLATION_CLOSEST:
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return SampleFromVoxels<AccessorType, 0, false>(acc)(Vec3f(x, y, z));
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case INTERPOLATION_LINEAR:
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return SampleFromVoxels<AccessorType, 1, false>(acc)(Vec3f(x - 0.5f, y - 0.5f, z - 0.5f));
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default:
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SampleFromVoxels<AccessorType, 1, false> s(acc);
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return kernel_tex_image_interp_tricubic_nanovdb<T>(s, x - 0.5f, y - 0.5f, z - 0.5f);
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}
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}
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#endif
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ccl_device float4 kernel_tex_image_interp(KernelGlobals *kg, int id, float x, float y)
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{
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const TextureInfo &info = kernel_tex_fetch(__texture_info, id);
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/* float4, byte4, ushort4 and half4 */
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const int texture_type = info.data_type;
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if (texture_type == IMAGE_DATA_TYPE_FLOAT4 || texture_type == IMAGE_DATA_TYPE_BYTE4 ||
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texture_type == IMAGE_DATA_TYPE_HALF4 || texture_type == IMAGE_DATA_TYPE_USHORT4) {
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if (info.interpolation == INTERPOLATION_CUBIC) {
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return kernel_tex_image_interp_bicubic<float4>(info, x, y);
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}
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else {
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CUtexObject tex = (CUtexObject)info.data;
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return tex2D<float4>(tex, x, y);
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}
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}
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/* float, byte and half */
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else {
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float f;
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if (info.interpolation == INTERPOLATION_CUBIC) {
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f = kernel_tex_image_interp_bicubic<float>(info, x, y);
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}
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else {
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CUtexObject tex = (CUtexObject)info.data;
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f = tex2D<float>(tex, x, y);
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}
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return make_float4(f, f, f, 1.0f);
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}
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}
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ccl_device float4 kernel_tex_image_interp_3d(KernelGlobals *kg,
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int id,
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float3 P,
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InterpolationType interp)
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{
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const TextureInfo &info = kernel_tex_fetch(__texture_info, id);
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if (info.use_transform_3d) {
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P = transform_point(&info.transform_3d, P);
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}
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const float x = P.x;
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const float y = P.y;
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const float z = P.z;
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uint interpolation = (interp == INTERPOLATION_NONE) ? info.interpolation : interp;
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const int texture_type = info.data_type;
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#ifdef WITH_NANOVDB
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if (texture_type == IMAGE_DATA_TYPE_NANOVDB_FLOAT) {
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float f = kernel_tex_image_interp_nanovdb<float>(info, x, y, z, interpolation);
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return make_float4(f, f, f, 1.0f);
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}
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if (texture_type == IMAGE_DATA_TYPE_NANOVDB_FLOAT3) {
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nanovdb::Vec3f f = kernel_tex_image_interp_nanovdb<nanovdb::Vec3f>(
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info, x, y, z, interpolation);
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return make_float4(f[0], f[1], f[2], 1.0f);
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}
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#endif
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if (texture_type == IMAGE_DATA_TYPE_FLOAT4 || texture_type == IMAGE_DATA_TYPE_BYTE4 ||
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texture_type == IMAGE_DATA_TYPE_HALF4 || texture_type == IMAGE_DATA_TYPE_USHORT4) {
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if (interpolation == INTERPOLATION_CUBIC) {
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return kernel_tex_image_interp_tricubic<float4>(info, x, y, z);
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}
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else {
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CUtexObject tex = (CUtexObject)info.data;
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return tex3D<float4>(tex, x, y, z);
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}
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}
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else {
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float f;
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if (interpolation == INTERPOLATION_CUBIC) {
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f = kernel_tex_image_interp_tricubic<float>(info, x, y, z);
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}
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else {
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CUtexObject tex = (CUtexObject)info.data;
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f = tex3D<float>(tex, x, y, z);
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}
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return make_float4(f, f, f, 1.0f);
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}
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}
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