tesseract  4.00.00dev
intsimdmatrix.h
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1 // File: intsimdmatrix.h
3 // Description: Base class for 8-bit int SIMD matrix multipliers.
4 // Author: Ray Smith
5 // Created: Tue Aug 15 07:37:20 PST 2017
6 //
7 // (C) Copyright 2017, Google Inc.
8 // Licensed under the Apache License, Version 2.0 (the "License");
9 // you may not use this file except in compliance with the License.
10 // You may obtain a copy of the License at
11 // http://www.apache.org/licenses/LICENSE-2.0
12 // Unless required by applicable law or agreed to in writing, software
13 // distributed under the License is distributed on an "AS IS" BASIS,
14 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
15 // See the License for the specific language governing permissions and
16 // limitations under the License.
18 
19 #ifndef TESSERACT_ARCH_INTSIMDMATRIX_H_
20 #define TESSERACT_ARCH_INTSIMDMATRIX_H_
21 
22 #include <stdint.h>
23 #include <vector>
24 #include "genericvector.h"
25 #include "matrix.h"
26 
27 namespace tesseract {
28 
29 // Base class for a SIMD function to multiply a matrix by a vector, with sources
30 // of 8-bit signed integer, and result in a double, after appropriate scaling.
31 // Assumes a specific method of multiplication that can be applied to any size
32 // and number of SIMD registers as follows:
33 // int32_t results are computed with num_outputs_per_register_ in each of
34 // max_output_registers_ result registers, repeatedly until it would make too
35 // many results, then the number of registers is halved, and so-on down to a
36 // single result register. The last calculation only outputs the required number
37 // of results instead of writing beyond the bounds. Eg: matrix has 75 outputs,
38 // num_outputs_per_register_ = 4, and max_output_registers_ = 8,
39 // Step 1: 8x4=32 results are computed,
40 // Step 2: 8x4=32 again, total 64,
41 // Step 3: 2x4=8 (since 8x4 is too many, so is 4x4), total 72,
42 // Step 4: 1x3, total 75.
43 // Each step above is computed using a PartialFunc, which runs over the input
44 // vector once. The input is read one registerful of num_inputs_per_register_
45 // at a time (presumably 4x num_outputs_per_register_ since they are int8_t)
46 // so the inputs MUST BE PADDED to a multiple of num_inputs_per_register_.
47 // Since it is slow (on Intel at least) to horizontally add in a register,
48 // provision is made to process num_inputs_per_group_ inputs at a time, with
49 // the group being replicated num_input_groups_ times and multiplied by a
50 // num_inputs_per_group_ by num_input_groups_ rectangle of the weights matrix.
51 // This is most convenient if num_inputs_per_group_ is 4, and the product
52 // sign-extends and sums 8x8=16 bit results to 32 bits, adding 4 adjacent
53 // results in the process, but it doesn't have to be implemented that way.
54 // The weights are re-ordered by Init() to be used sequentially by the above
55 // algorithm, followed by the biases, so they can be added at the end.
56 // The base class computes the base C++ implementation.
57 // NOTE that, although the subclasses execute on different SIMD hardware, no
58 // virtual methods are needed, as the constructor sets up everything that
59 // is required to allow the base class implementation to do all the work.
61  public:
62  // Constructor should set the data members to indicate the sizes.
63  // NOTE: Base constructor public only for test purposes.
69  num_input_groups_(1) {}
70 
71  // Factory makes and returns an IntSimdMatrix (sub)class of the best
72  // available type for the current architecture.
74 
75  // Computes a reshaped copy of the weight matrix w. If there are no
76  // partial_funcs_, it does nothing.
77  void Init(const GENERIC_2D_ARRAY<int8_t>& w);
78 
79  // Rounds the size up to a multiple of the input register size (in int8_t).
80  int RoundInputs(int size) const {
81  return Roundup(size, num_inputs_per_register_);
82  }
83  // Rounds the size up to a multiple of the output register size (in int32_t).
84  int RoundOutputs(int size) const {
85  return Roundup(size, num_outputs_per_register_);
86  }
87 
88  // Computes matrix.vector v = Wu.
89  // u is of size W.dim2() - 1 and the output v is of size W.dim1().
90  // u is imagined to have an extra element at the end with value 1, to
91  // implement the bias, but it doesn't actually have it.
92  // Computes the base C++ implementation, if there are no partial_funcs_.
93  // NOTE: The size of the input vector (u) must be padded using
94  // RoundInputs above.
95  // The input will be over-read to the extent of the padding. There are no
96  // alignment requirements.
98  const GenericVector<double>& scales, const int8_t* u,
99  double* v) const;
100 
101  protected:
102  // Function to compute part of a matrix.vector multiplication. The weights
103  // are in a very specific order (see above) in w, which is multiplied by
104  // u of length num_in, to produce output v after scaling the integer results
105  // by the corresponding member of scales.
106  // The amount of w and scales consumed is fixed and not available to the
107  // caller. The number of outputs written to v will be at most num_out.
108  typedef void (*PartialFunc)(const int8_t* w, const double* scales,
109  const int8_t* u, int num_in, int num_out,
110  double* v);
111 
112  // Rounds the input up to a multiple of the given factor.
113  static int Roundup(int input, int factor) {
114  return (input + factor - 1) / factor * factor;
115  }
116 
117  // Number of 32 bit outputs held in each register.
119  // Maximum number of registers that we will use to hold outputs.
121  // Number of 8 bit inputs in the inputs register.
123  // Number of inputs in each weight group.
125  // Number of groups of inputs to be broadcast.
127  // The weights matrix reorganized in whatever way suits this instance.
128  std::vector<int8_t> shaped_w_;
129  // A series of functions to compute a partial result.
130  std::vector<PartialFunc> partial_funcs_;
131 };
132 
133 } // namespace tesseract
134 
135 #endif // TESSERACT_ARCH_INTSIMDMATRIX_H_
void MatrixDotVector(const GENERIC_2D_ARRAY< int8_t > &w, const GenericVector< double > &scales, const int8_t *u, double *v) const
int RoundInputs(int size) const
Definition: intsimdmatrix.h:80
void(* PartialFunc)(const int8_t *w, const double *scales, const int8_t *u, int num_in, int num_out, double *v)
std::vector< PartialFunc > partial_funcs_
void Init(const GENERIC_2D_ARRAY< int8_t > &w)
int RoundOutputs(int size) const
Definition: intsimdmatrix.h:84
std::vector< int8_t > shaped_w_
static int Roundup(int input, int factor)
static IntSimdMatrix * GetFastestMultiplier()