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381 lines
10 KiB
C++
381 lines
10 KiB
C++
// Copyright NVIDIA Corporation 2007 -- Ignacio Castano <icastano@nvidia.com>
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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#include <nvcore/Debug.h>
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#include <nvcore/Containers.h>
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#include <nvmath/Color.h>
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#include <nvimage/Image.h>
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#include <nvimage/ColorBlock.h>
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#include <nvimage/BlockDXT.h>
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#include <nvtt/CompressionOptions.h>
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#include <nvtt/OutputOptions.h>
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#include <nvtt/QuickCompressDXT.h>
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#include <nvtt/OptimalCompressDXT.h>
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#include "CudaCompressDXT.h"
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#include "CudaUtils.h"
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#if defined HAVE_CUDA
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#include <cuda_runtime_api.h>
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#endif
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#include <time.h>
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#include <stdio.h>
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using namespace nv;
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using namespace nvtt;
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#if defined HAVE_CUDA
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#define MAX_BLOCKS 8192U // 32768, 65535
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extern "C" void setupCompressKernel(const float weights[3]);
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extern "C" void compressKernelDXT1(uint blockNum, uint * d_data, uint * d_result, uint * d_bitmaps);
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extern "C" void compressKernelDXT1_Level4(uint blockNum, uint * d_data, uint * d_result, uint * d_bitmaps);
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extern "C" void compressWeightedKernelDXT1(uint blockNum, uint * d_data, uint * d_result, uint * d_bitmaps);
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#include "Bitmaps.h" // @@ Rename to BitmapTable.h
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// Convert linear image to block linear.
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static void convertToBlockLinear(const Image * image, uint * blockLinearImage)
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{
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const uint w = (image->width() + 3) / 4;
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const uint h = (image->height() + 3) / 4;
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for(uint by = 0; by < h; by++) {
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for(uint bx = 0; bx < w; bx++) {
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const uint bw = min(image->width() - bx * 4, 4U);
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const uint bh = min(image->height() - by * 4, 4U);
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for (uint i = 0; i < 16; i++) {
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const int x = (i % 4) % bw;
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const int y = (i / 4) % bh;
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blockLinearImage[(by * w + bx) * 16 + i] = image->pixel(bx * 4 + x, by * 4 + y).u;
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}
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}
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}
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}
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#endif
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CudaCompressor::CudaCompressor() : m_bitmapTable(NULL), m_data(NULL), m_result(NULL)
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{
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#if defined HAVE_CUDA
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// Allocate and upload bitmaps.
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cudaMalloc((void**) &m_bitmapTable, 992 * sizeof(uint));
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if (m_bitmapTable != NULL)
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{
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cudaMemcpy(m_bitmapTable, s_bitmapTable, 992 * sizeof(uint), cudaMemcpyHostToDevice);
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}
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// Allocate scratch buffers.
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cudaMalloc((void**) &m_data, MAX_BLOCKS * 64U);
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cudaMalloc((void**) &m_result, MAX_BLOCKS * 8U);
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#endif
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}
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CudaCompressor::~CudaCompressor()
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{
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#if defined HAVE_CUDA
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// Free device mem allocations.
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cudaFree(m_data);
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cudaFree(m_result);
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cudaFree(m_bitmapTable);
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#endif
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}
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bool CudaCompressor::isValid() const
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{
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#if defined HAVE_CUDA
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if (cudaGetLastError() != cudaSuccess)
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{
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return false;
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}
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#endif
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return m_data != NULL && m_result != NULL && m_bitmapTable != NULL;
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}
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// @@ This code is very repetitive and needs to be cleaned up.
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void CudaCompressor::setImage(const Image * image, nvtt::AlphaMode alphaMode)
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{
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m_image = image;
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m_alphaMode = alphaMode;
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}
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/// Compress image using CUDA.
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void CudaCompressor::compressDXT1(const CompressionOptions::Private & compressionOptions, const OutputOptions::Private & outputOptions)
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{
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nvDebugCheck(cuda::isHardwarePresent());
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#if defined HAVE_CUDA
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// Image size in blocks.
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const uint w = (m_image->width() + 3) / 4;
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const uint h = (m_image->height() + 3) / 4;
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uint imageSize = w * h * 16 * sizeof(Color32);
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uint * blockLinearImage = (uint *) ::malloc(imageSize);
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convertToBlockLinear(m_image, blockLinearImage); // @@ Do this in parallel with the GPU, or in the GPU!
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const uint blockNum = w * h;
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const uint compressedSize = blockNum * 8;
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clock_t start = clock();
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setupCompressKernel(compressionOptions.colorWeight.ptr());
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// TODO: Add support for multiple GPUs.
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uint bn = 0;
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while(bn != blockNum)
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{
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uint count = min(blockNum - bn, MAX_BLOCKS);
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cudaMemcpy(m_data, blockLinearImage + bn * 16, count * 64, cudaMemcpyHostToDevice);
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// Launch kernel.
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compressKernelDXT1(count, m_data, m_result, m_bitmapTable);
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// Check for errors.
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cudaError_t err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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nvDebug("CUDA Error: %s\n", cudaGetErrorString(err));
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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}
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// Copy result to host, overwrite swizzled image.
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cudaMemcpy(blockLinearImage, m_result, count * 8, cudaMemcpyDeviceToHost);
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// Output result.
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if (outputOptions.outputHandler != NULL)
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{
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outputOptions.outputHandler->writeData(blockLinearImage, count * 8);
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}
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bn += count;
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}
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clock_t end = clock();
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//printf("\rCUDA time taken: %.3f seconds\n", float(end-start) / CLOCKS_PER_SEC);
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free(blockLinearImage);
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#else
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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#endif
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}
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/// Compress image using CUDA.
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void CudaCompressor::compressDXT3(const CompressionOptions::Private & compressionOptions, const OutputOptions::Private & outputOptions)
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{
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nvDebugCheck(cuda::isHardwarePresent());
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#if defined HAVE_CUDA
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// Image size in blocks.
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const uint w = (m_image->width() + 3) / 4;
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const uint h = (m_image->height() + 3) / 4;
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uint imageSize = w * h * 16 * sizeof(Color32);
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uint * blockLinearImage = (uint *) ::malloc(imageSize);
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convertToBlockLinear(m_image, blockLinearImage);
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const uint blockNum = w * h;
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const uint compressedSize = blockNum * 8;
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AlphaBlockDXT3 * alphaBlocks = NULL;
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alphaBlocks = (AlphaBlockDXT3 *)::malloc(min(compressedSize, MAX_BLOCKS * 8U));
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setupCompressKernel(compressionOptions.colorWeight.ptr());
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clock_t start = clock();
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uint bn = 0;
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while(bn != blockNum)
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{
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uint count = min(blockNum - bn, MAX_BLOCKS);
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cudaMemcpy(m_data, blockLinearImage + bn * 16, count * 64, cudaMemcpyHostToDevice);
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// Launch kernel.
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if (m_alphaMode == AlphaMode_Transparency)
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{
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compressWeightedKernelDXT1(count, m_data, m_result, m_bitmapTable);
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}
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else
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{
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compressKernelDXT1_Level4(count, m_data, m_result, m_bitmapTable);
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}
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// Compress alpha in parallel with the GPU.
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for (uint i = 0; i < count; i++)
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{
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ColorBlock rgba(blockLinearImage + (bn + i) * 16);
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OptimalCompress::compressDXT3A(rgba, alphaBlocks + i);
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}
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// Check for errors.
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cudaError_t err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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nvDebug("CUDA Error: %s\n", cudaGetErrorString(err));
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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}
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// Copy result to host, overwrite swizzled image.
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cudaMemcpy(blockLinearImage, m_result, count * 8, cudaMemcpyDeviceToHost);
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// Output result.
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if (outputOptions.outputHandler != NULL)
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{
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for (uint i = 0; i < count; i++)
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{
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outputOptions.outputHandler->writeData(alphaBlocks + i, 8);
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outputOptions.outputHandler->writeData(blockLinearImage + i * 2, 8);
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}
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}
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bn += count;
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}
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clock_t end = clock();
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//printf("\rCUDA time taken: %.3f seconds\n", float(end-start) / CLOCKS_PER_SEC);
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free(alphaBlocks);
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free(blockLinearImage);
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#else
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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#endif
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}
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/// Compress image using CUDA.
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void CudaCompressor::compressDXT5(const CompressionOptions::Private & compressionOptions, const OutputOptions::Private & outputOptions)
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{
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nvDebugCheck(cuda::isHardwarePresent());
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#if defined HAVE_CUDA
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// Image size in blocks.
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const uint w = (m_image->width() + 3) / 4;
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const uint h = (m_image->height() + 3) / 4;
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uint imageSize = w * h * 16 * sizeof(Color32);
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uint * blockLinearImage = (uint *) ::malloc(imageSize);
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convertToBlockLinear(m_image, blockLinearImage);
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const uint blockNum = w * h;
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const uint compressedSize = blockNum * 8;
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AlphaBlockDXT5 * alphaBlocks = NULL;
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alphaBlocks = (AlphaBlockDXT5 *)::malloc(min(compressedSize, MAX_BLOCKS * 8U));
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setupCompressKernel(compressionOptions.colorWeight.ptr());
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clock_t start = clock();
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uint bn = 0;
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while(bn != blockNum)
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{
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uint count = min(blockNum - bn, MAX_BLOCKS);
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cudaMemcpy(m_data, blockLinearImage + bn * 16, count * 64, cudaMemcpyHostToDevice);
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// Launch kernel.
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if (m_alphaMode == AlphaMode_Transparency)
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{
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compressWeightedKernelDXT1(count, m_data, m_result, m_bitmapTable);
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}
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else
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{
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compressKernelDXT1_Level4(count, m_data, m_result, m_bitmapTable);
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}
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// Compress alpha in parallel with the GPU.
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for (uint i = 0; i < count; i++)
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{
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ColorBlock rgba(blockLinearImage + (bn + i) * 16);
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QuickCompress::compressDXT5A(rgba, alphaBlocks + i);
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}
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// Check for errors.
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cudaError_t err = cudaGetLastError();
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if (err != cudaSuccess)
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{
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nvDebug("CUDA Error: %s\n", cudaGetErrorString(err));
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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}
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// Copy result to host, overwrite swizzled image.
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cudaMemcpy(blockLinearImage, m_result, count * 8, cudaMemcpyDeviceToHost);
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// Output result.
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if (outputOptions.outputHandler != NULL)
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{
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for (uint i = 0; i < count; i++)
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{
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outputOptions.outputHandler->writeData(alphaBlocks + i, 8);
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outputOptions.outputHandler->writeData(blockLinearImage + i * 2, 8);
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}
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}
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bn += count;
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}
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clock_t end = clock();
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//printf("\rCUDA time taken: %.3f seconds\n", float(end-start) / CLOCKS_PER_SEC);
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free(alphaBlocks);
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free(blockLinearImage);
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#else
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if (outputOptions.errorHandler != NULL)
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{
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outputOptions.errorHandler->error(Error_CudaError);
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}
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#endif
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}
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