/****************************************************************************** * Copyright (c) 2011, Duane Merrill. All rights reserved. * Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the * names of its contributors may be used to endorse or promote products * derived from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * ******************************************************************************/ /** * \file * cub::AgentHistogram implements a stateful abstraction of CUDA thread blocks for participating in device-wide histogram . */ #pragma once #include #include "../util_type.cuh" #include "../block/block_load.cuh" #include "../grid/grid_queue.cuh" #include "../iterator/cache_modified_input_iterator.cuh" #include "../util_namespace.cuh" /// Optional outer namespace(s) CUB_NS_PREFIX /// CUB namespace namespace cub { /****************************************************************************** * Tuning policy ******************************************************************************/ /** * */ enum BlockHistogramMemoryPreference { GMEM, SMEM, BLEND }; /** * Parameterizable tuning policy type for AgentHistogram */ template < int _BLOCK_THREADS, ///< Threads per thread block int _PIXELS_PER_THREAD, ///< Pixels per thread (per tile of input) BlockLoadAlgorithm _LOAD_ALGORITHM, ///< The BlockLoad algorithm to use CacheLoadModifier _LOAD_MODIFIER, ///< Cache load modifier for reading input elements bool _RLE_COMPRESS, ///< Whether to perform localized RLE to compress samples before histogramming BlockHistogramMemoryPreference _MEM_PREFERENCE, ///< Whether to prefer privatized shared-memory bins (versus privatized global-memory bins) bool _WORK_STEALING> ///< Whether to dequeue tiles from a global work queue struct AgentHistogramPolicy { enum { BLOCK_THREADS = _BLOCK_THREADS, ///< Threads per thread block PIXELS_PER_THREAD = _PIXELS_PER_THREAD, ///< Pixels per thread (per tile of input) IS_RLE_COMPRESS = _RLE_COMPRESS, ///< Whether to perform localized RLE to compress samples before histogramming MEM_PREFERENCE = _MEM_PREFERENCE, ///< Whether to prefer privatized shared-memory bins (versus privatized global-memory bins) IS_WORK_STEALING = _WORK_STEALING, ///< Whether to dequeue tiles from a global work queue }; static const BlockLoadAlgorithm LOAD_ALGORITHM = _LOAD_ALGORITHM; ///< The BlockLoad algorithm to use static const CacheLoadModifier LOAD_MODIFIER = _LOAD_MODIFIER; ///< Cache load modifier for reading input elements }; /****************************************************************************** * Thread block abstractions ******************************************************************************/ /** * \brief AgentHistogram implements a stateful abstraction of CUDA thread blocks for participating in device-wide histogram . */ template < typename AgentHistogramPolicyT, ///< Parameterized AgentHistogramPolicy tuning policy type int PRIVATIZED_SMEM_BINS, ///< Number of privatized shared-memory histogram bins of any channel. Zero indicates privatized counters to be maintained in device-accessible memory. int NUM_CHANNELS, ///< Number of channels interleaved in the input data. Supports up to four channels. int NUM_ACTIVE_CHANNELS, ///< Number of channels actively being histogrammed typename SampleIteratorT, ///< Random-access input iterator type for reading samples typename CounterT, ///< Integer type for counting sample occurrences per histogram bin typename PrivatizedDecodeOpT, ///< The transform operator type for determining privatized counter indices from samples, one for each channel typename OutputDecodeOpT, ///< The transform operator type for determining output bin-ids from privatized counter indices, one for each channel typename OffsetT, ///< Signed integer type for global offsets int PTX_ARCH = CUB_PTX_ARCH> ///< PTX compute capability struct AgentHistogram { //--------------------------------------------------------------------- // Types and constants //--------------------------------------------------------------------- /// The sample type of the input iterator typedef typename std::iterator_traits::value_type SampleT; /// The pixel type of SampleT typedef typename CubVector::Type PixelT; /// The quad type of SampleT typedef typename CubVector::Type QuadT; /// Constants enum { BLOCK_THREADS = AgentHistogramPolicyT::BLOCK_THREADS, PIXELS_PER_THREAD = AgentHistogramPolicyT::PIXELS_PER_THREAD, SAMPLES_PER_THREAD = PIXELS_PER_THREAD * NUM_CHANNELS, QUADS_PER_THREAD = SAMPLES_PER_THREAD / 4, TILE_PIXELS = PIXELS_PER_THREAD * BLOCK_THREADS, TILE_SAMPLES = SAMPLES_PER_THREAD * BLOCK_THREADS, IS_RLE_COMPRESS = AgentHistogramPolicyT::IS_RLE_COMPRESS, MEM_PREFERENCE = (PRIVATIZED_SMEM_BINS > 0) ? AgentHistogramPolicyT::MEM_PREFERENCE : GMEM, IS_WORK_STEALING = AgentHistogramPolicyT::IS_WORK_STEALING, }; /// Cache load modifier for reading input elements static const CacheLoadModifier LOAD_MODIFIER = AgentHistogramPolicyT::LOAD_MODIFIER; /// Input iterator wrapper type (for applying cache modifier) typedef typename If::VALUE, CacheModifiedInputIterator, // Wrap the native input pointer with CacheModifiedInputIterator SampleIteratorT>::Type // Directly use the supplied input iterator type WrappedSampleIteratorT; /// Pixel input iterator type (for applying cache modifier) typedef CacheModifiedInputIterator WrappedPixelIteratorT; /// Qaud input iterator type (for applying cache modifier) typedef CacheModifiedInputIterator WrappedQuadIteratorT; /// Parameterized BlockLoad type for samples typedef BlockLoad< SampleT, BLOCK_THREADS, SAMPLES_PER_THREAD, AgentHistogramPolicyT::LOAD_ALGORITHM> BlockLoadSampleT; /// Parameterized BlockLoad type for pixels typedef BlockLoad< PixelT, BLOCK_THREADS, PIXELS_PER_THREAD, AgentHistogramPolicyT::LOAD_ALGORITHM> BlockLoadPixelT; /// Parameterized BlockLoad type for quads typedef BlockLoad< QuadT, BLOCK_THREADS, QUADS_PER_THREAD, AgentHistogramPolicyT::LOAD_ALGORITHM> BlockLoadQuadT; /// Shared memory type required by this thread block struct _TempStorage { CounterT histograms[NUM_ACTIVE_CHANNELS][PRIVATIZED_SMEM_BINS + 1]; // Smem needed for block-privatized smem histogram (with 1 word of padding) int tile_idx; // Aliasable storage layout union Aliasable { typename BlockLoadSampleT::TempStorage sample_load; // Smem needed for loading a tile of samples typename BlockLoadPixelT::TempStorage pixel_load; // Smem needed for loading a tile of pixels typename BlockLoadQuadT::TempStorage quad_load; // Smem needed for loading a tile of quads } aliasable; }; /// Temporary storage type (unionable) struct TempStorage : Uninitialized<_TempStorage> {}; //--------------------------------------------------------------------- // Per-thread fields //--------------------------------------------------------------------- /// Reference to temp_storage _TempStorage &temp_storage; /// Sample input iterator (with cache modifier applied, if possible) WrappedSampleIteratorT d_wrapped_samples; /// Native pointer for input samples (possibly NULL if unavailable) SampleT* d_native_samples; /// The number of output bins for each channel int (&num_output_bins)[NUM_ACTIVE_CHANNELS]; /// The number of privatized bins for each channel int (&num_privatized_bins)[NUM_ACTIVE_CHANNELS]; /// Reference to gmem privatized histograms for each channel CounterT* d_privatized_histograms[NUM_ACTIVE_CHANNELS]; /// Reference to final output histograms (gmem) CounterT* (&d_output_histograms)[NUM_ACTIVE_CHANNELS]; /// The transform operator for determining output bin-ids from privatized counter indices, one for each channel OutputDecodeOpT (&output_decode_op)[NUM_ACTIVE_CHANNELS]; /// The transform operator for determining privatized counter indices from samples, one for each channel PrivatizedDecodeOpT (&privatized_decode_op)[NUM_ACTIVE_CHANNELS]; /// Whether to prefer privatized smem counters vs privatized global counters bool prefer_smem; //--------------------------------------------------------------------- // Initialize privatized bin counters //--------------------------------------------------------------------- // Initialize privatized bin counters __device__ __forceinline__ void InitBinCounters(CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS]) { // Initialize histogram bin counts to zeros #pragma unroll for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) { for (int privatized_bin = threadIdx.x; privatized_bin < num_privatized_bins[CHANNEL]; privatized_bin += BLOCK_THREADS) { privatized_histograms[CHANNEL][privatized_bin] = 0; } } // Barrier to make sure all threads are done updating counters CTA_SYNC(); } // Initialize privatized bin counters. Specialized for privatized shared-memory counters __device__ __forceinline__ void InitSmemBinCounters() { CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS]; for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) privatized_histograms[CHANNEL] = temp_storage.histograms[CHANNEL]; InitBinCounters(privatized_histograms); } // Initialize privatized bin counters. Specialized for privatized global-memory counters __device__ __forceinline__ void InitGmemBinCounters() { InitBinCounters(d_privatized_histograms); } //--------------------------------------------------------------------- // Update final output histograms //--------------------------------------------------------------------- // Update final output histograms from privatized histograms __device__ __forceinline__ void StoreOutput(CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS]) { // Barrier to make sure all threads are done updating counters CTA_SYNC(); // Apply privatized bin counts to output bin counts #pragma unroll for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) { int channel_bins = num_privatized_bins[CHANNEL]; for (int privatized_bin = threadIdx.x; privatized_bin < channel_bins; privatized_bin += BLOCK_THREADS) { int output_bin = -1; CounterT count = privatized_histograms[CHANNEL][privatized_bin]; bool is_valid = count > 0; output_decode_op[CHANNEL].template BinSelect((SampleT) privatized_bin, output_bin, is_valid); if (output_bin >= 0) { atomicAdd(&d_output_histograms[CHANNEL][output_bin], count); } } } } // Update final output histograms from privatized histograms. Specialized for privatized shared-memory counters __device__ __forceinline__ void StoreSmemOutput() { CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS]; for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) privatized_histograms[CHANNEL] = temp_storage.histograms[CHANNEL]; StoreOutput(privatized_histograms); } // Update final output histograms from privatized histograms. Specialized for privatized global-memory counters __device__ __forceinline__ void StoreGmemOutput() { StoreOutput(d_privatized_histograms); } //--------------------------------------------------------------------- // Tile accumulation //--------------------------------------------------------------------- // Accumulate pixels. Specialized for RLE compression. __device__ __forceinline__ void AccumulatePixels( SampleT samples[PIXELS_PER_THREAD][NUM_CHANNELS], bool is_valid[PIXELS_PER_THREAD], CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS], Int2Type is_rle_compress) { #pragma unroll for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) { // Bin pixels int bins[PIXELS_PER_THREAD]; #pragma unroll for (int PIXEL = 0; PIXEL < PIXELS_PER_THREAD; ++PIXEL) { bins[PIXEL] = -1; privatized_decode_op[CHANNEL].template BinSelect(samples[PIXEL][CHANNEL], bins[PIXEL], is_valid[PIXEL]); } CounterT accumulator = 1; #pragma unroll for (int PIXEL = 0; PIXEL < PIXELS_PER_THREAD - 1; ++PIXEL) { if (bins[PIXEL] != bins[PIXEL + 1]) { if (bins[PIXEL] >= 0) atomicAdd(privatized_histograms[CHANNEL] + bins[PIXEL], accumulator); accumulator = 0; } accumulator++; } // Last pixel if (bins[PIXELS_PER_THREAD - 1] >= 0) atomicAdd(privatized_histograms[CHANNEL] + bins[PIXELS_PER_THREAD - 1], accumulator); } } // Accumulate pixels. Specialized for individual accumulation of each pixel. __device__ __forceinline__ void AccumulatePixels( SampleT samples[PIXELS_PER_THREAD][NUM_CHANNELS], bool is_valid[PIXELS_PER_THREAD], CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS], Int2Type is_rle_compress) { #pragma unroll for (int PIXEL = 0; PIXEL < PIXELS_PER_THREAD; ++PIXEL) { #pragma unroll for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) { int bin = -1; privatized_decode_op[CHANNEL].template BinSelect(samples[PIXEL][CHANNEL], bin, is_valid[PIXEL]); if (bin >= 0) atomicAdd(privatized_histograms[CHANNEL] + bin, 1); } } } /** * Accumulate pixel, specialized for smem privatized histogram */ __device__ __forceinline__ void AccumulateSmemPixels( SampleT samples[PIXELS_PER_THREAD][NUM_CHANNELS], bool is_valid[PIXELS_PER_THREAD]) { CounterT* privatized_histograms[NUM_ACTIVE_CHANNELS]; for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) privatized_histograms[CHANNEL] = temp_storage.histograms[CHANNEL]; AccumulatePixels(samples, is_valid, privatized_histograms, Int2Type()); } /** * Accumulate pixel, specialized for gmem privatized histogram */ __device__ __forceinline__ void AccumulateGmemPixels( SampleT samples[PIXELS_PER_THREAD][NUM_CHANNELS], bool is_valid[PIXELS_PER_THREAD]) { AccumulatePixels(samples, is_valid, d_privatized_histograms, Int2Type()); } //--------------------------------------------------------------------- // Tile loading //--------------------------------------------------------------------- // Load full, aligned tile using pixel iterator (multi-channel) template __device__ __forceinline__ void LoadFullAlignedTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type<_NUM_ACTIVE_CHANNELS> num_active_channels) { typedef PixelT AliasedPixels[PIXELS_PER_THREAD]; WrappedPixelIteratorT d_wrapped_pixels((PixelT*) (d_native_samples + block_offset)); // Load using a wrapped pixel iterator BlockLoadPixelT(temp_storage.aliasable.pixel_load).Load( d_wrapped_pixels, reinterpret_cast(samples)); } // Load full, aligned tile using quad iterator (single-channel) __device__ __forceinline__ void LoadFullAlignedTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type<1> num_active_channels) { typedef QuadT AliasedQuads[QUADS_PER_THREAD]; WrappedQuadIteratorT d_wrapped_quads((QuadT*) (d_native_samples + block_offset)); // Load using a wrapped quad iterator BlockLoadQuadT(temp_storage.aliasable.quad_load).Load( d_wrapped_quads, reinterpret_cast(samples)); } // Load full, aligned tile __device__ __forceinline__ void LoadTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type is_full_tile, Int2Type is_aligned) { LoadFullAlignedTile(block_offset, valid_samples, samples, Int2Type()); } // Load full, mis-aligned tile using sample iterator __device__ __forceinline__ void LoadTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type is_full_tile, Int2Type is_aligned) { typedef SampleT AliasedSamples[SAMPLES_PER_THREAD]; // Load using sample iterator BlockLoadSampleT(temp_storage.aliasable.sample_load).Load( d_wrapped_samples + block_offset, reinterpret_cast(samples)); } // Load partially-full, aligned tile using the pixel iterator __device__ __forceinline__ void LoadTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type is_full_tile, Int2Type is_aligned) { typedef PixelT AliasedPixels[PIXELS_PER_THREAD]; WrappedPixelIteratorT d_wrapped_pixels((PixelT*) (d_native_samples + block_offset)); int valid_pixels = valid_samples / NUM_CHANNELS; // Load using a wrapped pixel iterator BlockLoadPixelT(temp_storage.aliasable.pixel_load).Load( d_wrapped_pixels, reinterpret_cast(samples), valid_pixels); } // Load partially-full, mis-aligned tile using sample iterator __device__ __forceinline__ void LoadTile( OffsetT block_offset, int valid_samples, SampleT (&samples)[PIXELS_PER_THREAD][NUM_CHANNELS], Int2Type is_full_tile, Int2Type is_aligned) { typedef SampleT AliasedSamples[SAMPLES_PER_THREAD]; BlockLoadSampleT(temp_storage.aliasable.sample_load).Load( d_wrapped_samples + block_offset, reinterpret_cast(samples), valid_samples); } //--------------------------------------------------------------------- // Tile processing //--------------------------------------------------------------------- // Consume a tile of data samples template < bool IS_ALIGNED, // Whether the tile offset is aligned (quad-aligned for single-channel, pixel-aligned for multi-channel) bool IS_FULL_TILE> // Whether the tile is full __device__ __forceinline__ void ConsumeTile(OffsetT block_offset, int valid_samples) { SampleT samples[PIXELS_PER_THREAD][NUM_CHANNELS]; bool is_valid[PIXELS_PER_THREAD]; // Load tile LoadTile( block_offset, valid_samples, samples, Int2Type(), Int2Type()); // Set valid flags #pragma unroll for (int PIXEL = 0; PIXEL < PIXELS_PER_THREAD; ++PIXEL) is_valid[PIXEL] = IS_FULL_TILE || (((threadIdx.x * PIXELS_PER_THREAD + PIXEL) * NUM_CHANNELS) < valid_samples); // Accumulate samples #if CUB_PTX_ARCH >= 120 if (prefer_smem) AccumulateSmemPixels(samples, is_valid); else AccumulateGmemPixels(samples, is_valid); #else AccumulateGmemPixels(samples, is_valid); #endif } // Consume row tiles. Specialized for work-stealing from queue template __device__ __forceinline__ void ConsumeTiles( OffsetT num_row_pixels, ///< The number of multi-channel pixels per row in the region of interest OffsetT num_rows, ///< The number of rows in the region of interest OffsetT row_stride_samples, ///< The number of samples between starts of consecutive rows in the region of interest int tiles_per_row, ///< Number of image tiles per row GridQueue tile_queue, Int2Type is_work_stealing) { int num_tiles = num_rows * tiles_per_row; int tile_idx = (blockIdx.y * gridDim.x) + blockIdx.x; OffsetT num_even_share_tiles = gridDim.x * gridDim.y; while (tile_idx < num_tiles) { int row = tile_idx / tiles_per_row; int col = tile_idx - (row * tiles_per_row); OffsetT row_offset = row * row_stride_samples; OffsetT col_offset = (col * TILE_SAMPLES); OffsetT tile_offset = row_offset + col_offset; if (col == tiles_per_row - 1) { // Consume a partially-full tile at the end of the row OffsetT num_remaining = (num_row_pixels * NUM_CHANNELS) - col_offset; ConsumeTile(tile_offset, num_remaining); } else { // Consume full tile ConsumeTile(tile_offset, TILE_SAMPLES); } CTA_SYNC(); // Get next tile if (threadIdx.x == 0) temp_storage.tile_idx = tile_queue.Drain(1) + num_even_share_tiles; CTA_SYNC(); tile_idx = temp_storage.tile_idx; } } // Consume row tiles. Specialized for even-share (striped across thread blocks) template __device__ __forceinline__ void ConsumeTiles( OffsetT num_row_pixels, ///< The number of multi-channel pixels per row in the region of interest OffsetT num_rows, ///< The number of rows in the region of interest OffsetT row_stride_samples, ///< The number of samples between starts of consecutive rows in the region of interest int tiles_per_row, ///< Number of image tiles per row GridQueue tile_queue, Int2Type is_work_stealing) { for (int row = blockIdx.y; row < num_rows; row += gridDim.y) { OffsetT row_begin = row * row_stride_samples; OffsetT row_end = row_begin + (num_row_pixels * NUM_CHANNELS); OffsetT tile_offset = row_begin + (blockIdx.x * TILE_SAMPLES); while (tile_offset < row_end) { OffsetT num_remaining = row_end - tile_offset; if (num_remaining < TILE_SAMPLES) { // Consume partial tile ConsumeTile(tile_offset, num_remaining); break; } // Consume full tile ConsumeTile(tile_offset, TILE_SAMPLES); tile_offset += gridDim.x * TILE_SAMPLES; } } } //--------------------------------------------------------------------- // Parameter extraction //--------------------------------------------------------------------- // Return a native pixel pointer (specialized for CacheModifiedInputIterator types) template < CacheLoadModifier _MODIFIER, typename _ValueT, typename _OffsetT> __device__ __forceinline__ SampleT* NativePointer(CacheModifiedInputIterator<_MODIFIER, _ValueT, _OffsetT> itr) { return itr.ptr; } // Return a native pixel pointer (specialized for other types) template __device__ __forceinline__ SampleT* NativePointer(IteratorT itr) { return NULL; } //--------------------------------------------------------------------- // Interface //--------------------------------------------------------------------- /** * Constructor */ __device__ __forceinline__ AgentHistogram( TempStorage &temp_storage, ///< Reference to temp_storage SampleIteratorT d_samples, ///< Input data to reduce int (&num_output_bins)[NUM_ACTIVE_CHANNELS], ///< The number bins per final output histogram int (&num_privatized_bins)[NUM_ACTIVE_CHANNELS], ///< The number bins per privatized histogram CounterT* (&d_output_histograms)[NUM_ACTIVE_CHANNELS], ///< Reference to final output histograms CounterT* (&d_privatized_histograms)[NUM_ACTIVE_CHANNELS], ///< Reference to privatized histograms OutputDecodeOpT (&output_decode_op)[NUM_ACTIVE_CHANNELS], ///< The transform operator for determining output bin-ids from privatized counter indices, one for each channel PrivatizedDecodeOpT (&privatized_decode_op)[NUM_ACTIVE_CHANNELS]) ///< The transform operator for determining privatized counter indices from samples, one for each channel : temp_storage(temp_storage.Alias()), d_wrapped_samples(d_samples), num_output_bins(num_output_bins), num_privatized_bins(num_privatized_bins), d_output_histograms(d_output_histograms), privatized_decode_op(privatized_decode_op), output_decode_op(output_decode_op), d_native_samples(NativePointer(d_wrapped_samples)), prefer_smem((MEM_PREFERENCE == SMEM) ? true : // prefer smem privatized histograms (MEM_PREFERENCE == GMEM) ? false : // prefer gmem privatized histograms blockIdx.x & 1) // prefer blended privatized histograms { int blockId = (blockIdx.y * gridDim.x) + blockIdx.x; // Initialize the locations of this block's privatized histograms for (int CHANNEL = 0; CHANNEL < NUM_ACTIVE_CHANNELS; ++CHANNEL) this->d_privatized_histograms[CHANNEL] = d_privatized_histograms[CHANNEL] + (blockId * num_privatized_bins[CHANNEL]); } /** * Consume image */ __device__ __forceinline__ void ConsumeTiles( OffsetT num_row_pixels, ///< The number of multi-channel pixels per row in the region of interest OffsetT num_rows, ///< The number of rows in the region of interest OffsetT row_stride_samples, ///< The number of samples between starts of consecutive rows in the region of interest int tiles_per_row, ///< Number of image tiles per row GridQueue tile_queue) ///< Queue descriptor for assigning tiles of work to thread blocks { // Check whether all row starting offsets are quad-aligned (in single-channel) or pixel-aligned (in multi-channel) int quad_mask = AlignBytes::ALIGN_BYTES - 1; int pixel_mask = AlignBytes::ALIGN_BYTES - 1; size_t row_bytes = sizeof(SampleT) * row_stride_samples; bool quad_aligned_rows = (NUM_CHANNELS == 1) && (SAMPLES_PER_THREAD % 4 == 0) && // Single channel ((size_t(d_native_samples) & quad_mask) == 0) && // ptr is quad-aligned ((num_rows == 1) || ((row_bytes & quad_mask) == 0)); // number of row-samples is a multiple of the alignment of the quad bool pixel_aligned_rows = (NUM_CHANNELS > 1) && // Multi channel ((size_t(d_native_samples) & pixel_mask) == 0) && // ptr is pixel-aligned ((row_bytes & pixel_mask) == 0); // number of row-samples is a multiple of the alignment of the pixel // Whether rows are aligned and can be vectorized if ((d_native_samples != NULL) && (quad_aligned_rows || pixel_aligned_rows)) ConsumeTiles(num_row_pixels, num_rows, row_stride_samples, tiles_per_row, tile_queue, Int2Type()); else ConsumeTiles(num_row_pixels, num_rows, row_stride_samples, tiles_per_row, tile_queue, Int2Type()); } /** * Initialize privatized bin counters. Specialized for privatized shared-memory counters */ __device__ __forceinline__ void InitBinCounters() { if (prefer_smem) InitSmemBinCounters(); else InitGmemBinCounters(); } /** * Store privatized histogram to device-accessible memory. Specialized for privatized shared-memory counters */ __device__ __forceinline__ void StoreOutput() { if (prefer_smem) StoreSmemOutput(); else StoreGmemOutput(); } }; } // CUB namespace CUB_NS_POSTFIX // Optional outer namespace(s)