CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
198 lines
6.7 KiB
Plaintext
198 lines
6.7 KiB
Plaintext
// SPDX-FileCopyrightText: Copyright (c) 2011, Duane Merrill. All rights reserved.
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// SPDX-FileCopyrightText: Copyright (c) 2011-2018, NVIDIA CORPORATION. All rights reserved.
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// SPDX-License-Identifier: BSD-3
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/**
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* @file
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* cub::GridEvenShare is a descriptor utility for distributing input among CUDA thread blocks in an
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* "even-share" fashion. Each thread block gets roughly the same number of fixed-size work units
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* (grains).
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*/
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#pragma once
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#include <cub/config.cuh>
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#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
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# pragma GCC system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
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# pragma clang system_header
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#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
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# pragma system_header
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#endif // no system header
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#include <cub/grid/grid_mapping.cuh>
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#include <cub/util_math.cuh>
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#include <cub/util_type.cuh>
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#include <cuda/__cmath/ceil_div.h>
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#include <cuda/std/__algorithm/min.h>
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#include <cuda/std/limits>
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CUB_NAMESPACE_BEGIN
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/**
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* @brief GridEvenShare is a descriptor utility for distributing input among
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* CUDA thread blocks in an "even-share" fashion. Each thread block gets roughly
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* the same number of input tiles.
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*
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* @par Overview
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* Each thread block is assigned a consecutive sequence of input tiles. To help
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* preserve alignment and eliminate the overhead of guarded loads for all but the
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* last thread block, to GridEvenShare assigns one of three different amounts of
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* work to a given thread block: "big", "normal", or "last". The "big" workloads
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* are one scheduling grain larger than "normal". The "last" work unit for the
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* last thread block may be partially-full if the input is not an even multiple of
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* the scheduling grain size.
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*
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* @par
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* Before invoking a child grid, a parent thread will typically construct an
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* instance of GridEvenShare. The instance can be passed to child thread blocks
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* which can initialize their per-thread block offsets using \p BlockInit().
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*
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* @rst
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* .. versionadded:: 2.2.0
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* First appears in CUDA Toolkit 12.3.
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* @endrst
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*/
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template <typename OffsetT>
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struct GridEvenShare
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{
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private:
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int total_tiles{0};
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int big_shares{0};
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OffsetT big_share_items{0};
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OffsetT normal_share_items{0};
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OffsetT normal_base_offset{0};
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public:
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/// Total number of input items
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OffsetT num_items{0};
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/// Grid size in thread blocks
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int grid_size{0};
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/// OffsetT into input marking the beginning of the owning thread block's segment of input tiles
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OffsetT block_offset{0};
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/// OffsetT into input of marking the end (one-past) of the owning thread block's segment of input tiles
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OffsetT block_end{0};
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/// Stride between input tiles
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OffsetT block_stride{0};
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/**
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* \brief Constructor.
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*/
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_CCCL_FORCEINLINE GridEvenShare() = default;
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/**
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* @brief Dispatch initializer. To be called prior to kernel launch.
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*
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* @param num_items_
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* Total number of input items
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*
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* @param max_grid_size
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* Maximum grid size allowable (actual grid size may be less if not warranted by the the
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* number of input items)
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*
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* @param tile_items
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* Number of data items per input tile
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*/
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_CCCL_HOST_DEVICE _CCCL_FORCEINLINE void DispatchInit(OffsetT num_items_, int max_grid_size, int tile_items)
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{
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if (num_items_ <= 0 || max_grid_size <= 0 || tile_items <= 0)
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{
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this->num_items = 0;
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this->grid_size = 0;
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this->block_offset = 0;
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this->block_end = 0;
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return;
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}
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this->block_offset = num_items_; // Initialize past-the-end
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this->block_end = num_items_; // Initialize past-the-end
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this->num_items = num_items_;
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this->total_tiles = static_cast<int>(
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::cuda::std::min(OffsetT{::cuda::std::numeric_limits<int>::max()}, ::cuda::ceil_div(num_items_, tile_items)));
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this->grid_size = ::cuda::std::min(total_tiles, max_grid_size);
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int avg_tiles_per_block = total_tiles / grid_size;
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// leftover grains go to big blocks:
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this->big_shares = total_tiles - (avg_tiles_per_block * grid_size);
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this->normal_share_items = static_cast<OffsetT>(avg_tiles_per_block) * tile_items;
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this->normal_base_offset = static_cast<OffsetT>(big_shares) * tile_items;
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this->big_share_items = normal_share_items + tile_items;
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}
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/**
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* @brief Initializes ranges for the specified thread block index. Specialized
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* for a "raking" access pattern in which each thread block is assigned a
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* consecutive sequence of input tiles.
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*/
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template <int TILE_ITEMS>
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_CCCL_DEVICE _CCCL_FORCEINLINE void BlockInit(int block_id, detail::constant_t<GRID_MAPPING_RAKE> /*strategy_tag*/)
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{
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block_stride = TILE_ITEMS;
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if (block_id < big_shares)
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{
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// This thread block gets a big share of grains (avg_tiles_per_block + 1)
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block_offset = (block_id * big_share_items);
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block_end = block_offset + big_share_items;
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}
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else if (block_id < total_tiles)
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{
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// This thread block gets a normal share of grains (avg_tiles_per_block)
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block_offset = normal_base_offset + (block_id * normal_share_items);
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// Avoid generating values greater than num_items, as it may cause overflow
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block_end = block_offset + ::cuda::std::min(num_items - block_offset, normal_share_items);
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}
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// Else default past-the-end
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}
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/**
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* @brief Block-initialization, specialized for a "raking" access
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* pattern in which each thread block is assigned a consecutive sequence
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* of input tiles.
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*/
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template <int TILE_ITEMS>
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_CCCL_DEVICE _CCCL_FORCEINLINE void
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BlockInit(int block_id, detail::constant_t<GRID_MAPPING_STRIP_MINE> /*strategy_tag*/)
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{
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block_stride = grid_size * OffsetT{TILE_ITEMS};
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block_offset = block_id * OffsetT{TILE_ITEMS};
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block_end = num_items;
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}
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/**
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* @brief Block-initialization, specialized for "strip mining" access
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* pattern in which the input tiles assigned to each thread block are
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* separated by a stride equal to the the extent of the grid.
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*/
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template <int TILE_ITEMS, GridMappingStrategy STRATEGY>
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_CCCL_DEVICE _CCCL_FORCEINLINE void BlockInit()
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{
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BlockInit<TILE_ITEMS>(blockIdx.x, detail::constant_v<STRATEGY>);
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}
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/**
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* @brief Block-initialization, specialized for a "raking" access
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* pattern in which each thread block is assigned a consecutive sequence
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* of input tiles.
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*
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* @param[in] block_offset
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* Threadblock begin offset (inclusive)
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*
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* @param[in] block_end
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* Threadblock end offset (exclusive)
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*/
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template <int TILE_ITEMS, typename OffsetT1 = OffsetT>
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_CCCL_DEVICE _CCCL_FORCEINLINE void BlockInit(OffsetT1 block_offset, OffsetT1 block_end)
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{
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this->block_offset = block_offset;
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this->block_end = block_end;
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this->block_stride = TILE_ITEMS;
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}
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};
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CUB_NAMESPACE_END
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