Alien-XGBoost
view release on metacpan or search on metacpan
xgboost/cub/cub/block/block_load.cuh view on Meta::CPAN
/**
* \par Overview
*
* A [<em>striped arrangement</em>](index.html#sec5sec3) of data is read
* efficiently from memory and then locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3).
*
* \par Performance Considerations
* - The utilization of memory transactions (coalescing) remains high regardless
* of items loaded per thread.
* - The local reordering incurs slightly longer latencies and throughput than the
* direct cub::BLOCK_LOAD_DIRECT and cub::BLOCK_LOAD_VECTORIZE alternatives.
*/
BLOCK_LOAD_TRANSPOSE,
/**
* \par Overview
*
* A [<em>warp-striped arrangement</em>](index.html#sec5sec3) of data is
* read efficiently from memory and then locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3).
*
* \par Usage Considerations
* - BLOCK_THREADS must be a multiple of WARP_THREADS
*
* \par Performance Considerations
* - The utilization of memory transactions (coalescing) remains high regardless
* of items loaded per thread.
* - The local reordering incurs slightly larger latencies than the
* direct cub::BLOCK_LOAD_DIRECT and cub::BLOCK_LOAD_VECTORIZE alternatives.
* - Provisions more shared storage, but incurs smaller latencies than the
* BLOCK_LOAD_WARP_TRANSPOSE_TIMESLICED alternative.
*/
BLOCK_LOAD_WARP_TRANSPOSE,
/**
* \par Overview
*
* Like \p BLOCK_LOAD_WARP_TRANSPOSE, a [<em>warp-striped arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory and then is locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3). To reduce the shared memory
* requirement, only one warp's worth of shared memory is provisioned and is
* subsequently time-sliced among warps.
*
* \par Usage Considerations
* - BLOCK_THREADS must be a multiple of WARP_THREADS
*
* \par Performance Considerations
* - The utilization of memory transactions (coalescing) remains high regardless
* of items loaded per thread.
* - Provisions less shared memory temporary storage, but incurs larger
* latencies than the BLOCK_LOAD_WARP_TRANSPOSE alternative.
*/
BLOCK_LOAD_WARP_TRANSPOSE_TIMESLICED,
};
/**
* \brief The BlockLoad class provides [<em>collective</em>](index.html#sec0) data movement methods for loading a linear segment of items from memory into a [<em>blocked arrangement</em>](index.html#sec5sec3) across a CUDA thread block. .
* \tparam BLOCK_DIM_X The thread block length in threads along the X dimension
* \tparam ITEMS_PER_THREAD The number of consecutive items partitioned onto each thread.
* \tparam ALGORITHM <b>[optional]</b> cub::BlockLoadAlgorithm tuning policy. default: cub::BLOCK_LOAD_DIRECT.
* \tparam WARP_TIME_SLICING <b>[optional]</b> Whether or not only one warp's worth of shared memory should be allocated and time-sliced among block-warps during any load-related data transpositions (versus each warp having its own storage). (defa...
* \tparam BLOCK_DIM_Y <b>[optional]</b> The thread block length in threads along the Y dimension (default: 1)
* \tparam BLOCK_DIM_Z <b>[optional]</b> The thread block length in threads along the Z dimension (default: 1)
* \tparam PTX_ARCH <b>[optional]</b> \ptxversion
*
* \par Overview
* - The BlockLoad class provides a single data movement abstraction that can be specialized
* to implement different cub::BlockLoadAlgorithm strategies. This facilitates different
* performance policies for different architectures, data types, granularity sizes, etc.
* - BlockLoad can be optionally specialized by different data movement strategies:
* -# <b>cub::BLOCK_LOAD_DIRECT</b>. A [<em>blocked arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory. [More...](\ref cub::BlockLoadAlgorithm)
* -# <b>cub::BLOCK_LOAD_VECTORIZE</b>. A [<em>blocked arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory using CUDA's built-in vectorized loads as a
* coalescing optimization. [More...](\ref cub::BlockLoadAlgorithm)
* -# <b>cub::BLOCK_LOAD_TRANSPOSE</b>. A [<em>striped arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory and is then locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3). [More...](\ref cub::BlockLoadAlgorithm)
* -# <b>cub::BLOCK_LOAD_WARP_TRANSPOSE</b>. A [<em>warp-striped arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory and is then locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3). [More...](\ref cub::BlockLoadAlgorithm)
* -# <b>cub::BLOCK_LOAD_WARP_TRANSPOSE_TIMESLICED,</b>. A [<em>warp-striped arrangement</em>](index.html#sec5sec3)
* of data is read directly from memory and is then locally transposed into a
* [<em>blocked arrangement</em>](index.html#sec5sec3) one warp at a time. [More...](\ref cub::BlockLoadAlgorithm)
* - \rowmajor
*
* \par A Simple Example
* \blockcollective{BlockLoad}
* \par
* The code snippet below illustrates the loading of a linear
* segment of 512 integers into a "blocked" arrangement across 128 threads where each
* thread owns 4 consecutive items. The load is specialized for \p BLOCK_LOAD_WARP_TRANSPOSE,
* meaning memory references are efficiently coalesced using a warp-striped access
* pattern (after which items are locally reordered among threads).
* \par
* \code
* #include <cub/cub.cuh> // or equivalently <cub/block/block_load.cuh>
*
* __global__ void ExampleKernel(int *d_data, ...)
* {
* // Specialize BlockLoad for a 1D block of 128 threads owning 4 integer items each
* typedef cub::BlockLoad<int, 128, 4, BLOCK_LOAD_WARP_TRANSPOSE> BlockLoad;
*
* // Allocate shared memory for BlockLoad
* __shared__ typename BlockLoad::TempStorage temp_storage;
*
* // Load a segment of consecutive items that are blocked across threads
* int thread_data[4];
* BlockLoad(temp_storage).Load(d_data, thread_data);
*
* \endcode
* \par
* Suppose the input \p d_data is <tt>0, 1, 2, 3, 4, 5, ...</tt>.
( run in 0.476 second using v1.01-cache-2.11-cpan-5623c5533a1 )