CUTLASS
CUDA Templates for Linear Algebra Subroutines and Solvers
device/tensor_foreach.h
Go to the documentation of this file.
1 /***************************************************************************************************
2  * Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
3  *
4  * Redistribution and use in source and binary forms, with or without modification, are permitted
5  * provided that the following conditions are met:
6  * * Redistributions of source code must retain the above copyright notice, this list of
7  * conditions and the following disclaimer.
8  * * Redistributions in binary form must reproduce the above copyright notice, this list of
9  * conditions and the following disclaimer in the documentation and/or other materials
10  * provided with the distribution.
11  * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
12  * to endorse or promote products derived from this software without specific prior written
13  * permission.
14  *
15  * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
16  * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
17  * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
18  * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
19  * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
20  * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
21  * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
22  * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
23  *
24  **************************************************************************************************/
25 #pragma once
26 
27 #include <stdexcept>
28 #include "cutlass/cutlass.h"
30 
31 namespace cutlass {
32 namespace reference {
33 namespace device {
34 
36 
38 template <typename Func, int Rank, typename Params>
39 struct TensorForEach {
40 
42  TensorForEach(Coord<Rank> size, Params params = Params(), int grid_size = 0, int block_size = 0) {
43 
44  if (!grid_size || !block_size) {
45 
46  // if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
47  cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
48  &grid_size,
49  &block_size,
50  reinterpret_cast<void const *>(kernel::TensorForEach<Func, Rank, Params>));
51 
52  if (result != cudaSuccess) {
53  throw std::runtime_error("Failed to query occupancy.");
54  }
55 
56  // Limit block size. This has the effect of increasing the number of items processed by a
57  // single thread and reduces the impact of initialization overhead.
58  block_size = (block_size < 128 ? block_size : 128);
59  }
60 
61  dim3 grid(grid_size, 1, 1);
62  dim3 block(block_size, 1, 1);
63 
64  kernel::TensorForEach<Func, Rank, Params><<< grid, block >>>(size, params);
65  }
66 };
67 
69 
71 template <typename Func, int Rank, typename Params>
73 
75  TensorDiagonalForEach(Coord<Rank> size, Params params = Params(), int start = 0, int end = -1, int block_size = 128) {
76 
77  if (end < 0) {
78  end = size.min();
79  }
80 
81  dim3 block(block_size, 1, 1);
82  dim3 grid((end - start + block_size - 1) / block_size, 1, 1);
83 
84  kernel::TensorDiagonalForEach<Func, Rank, Params><<< grid, block >>>(size, params, start, end);
85  }
86 };
87 
88 
90 
91 template <typename Element, typename Func>
92 struct BlockForEach {
93 
96  Element *ptr,
97  size_t capacity,
98  typename Func::Params params = typename Func::Params(),
99  int grid_size = 0,
100  int block_size = 0) {
101 
102  if (!grid_size || !block_size) {
103 
104  // if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
105  cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
106  &grid_size,
107  &block_size,
108  reinterpret_cast<void const *>(kernel::BlockForEach<Element, Func>));
109 
110  if (result != cudaSuccess) {
111  throw std::runtime_error("Failed to query occupancy.");
112  }
113 
114  // Limit block size. This has the effect of increasing the number of items processed by a
115  // single thread and reduces the impact of initialization overhead.
116  block_size = (block_size < 128 ? block_size : 128);
117  }
118 
119  dim3 grid(grid_size, 1, 1);
120  dim3 block(block_size, 1, 1);
121 
122  kernel::BlockForEach<Element, Func><<< grid, block >>>(ptr, capacity, params);
123  }
124 };
125 
127 
128 } // namespace device
129 } // namespace reference
130 } // namesace cutlass
Definition: aligned_buffer.h:35
TensorDiagonalForEach(Coord< Rank > size, Params params=Params(), int start=0, int end=-1, int block_size=128)
Constructor performs the operation.
Definition: device/tensor_foreach.h:75
TensorForEach(Coord< Rank > size, Params params=Params(), int grid_size=0, int block_size=0)
Constructor performs the operation.
Definition: device/tensor_foreach.h:42
Launches a kernel calling a functor for each element along a tensor&#39;s diagonal.
Definition: device/tensor_foreach.h:72
BlockForEach(Element *ptr, size_t capacity, typename Func::Params params=typename Func::Params(), int grid_size=0, int block_size=0)
Constructor performs the operation.
Definition: device/tensor_foreach.h:95
Launches a kernel calling a functor for each element in a tensor&#39;s index space.
Definition: device/tensor_foreach.h:39
Statically-sized array specifying Coords within a tensor.
Definition: coord.h:43
Definition: device/tensor_foreach.h:92
Basic include for CUTLASS.