Compute Library
 22.05
gemv_pretransposed.hpp
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24 #pragma once
25 
26 #include <stdio.h>
27 
28 #include "arm_gemm.hpp"
29 #include "bias_adder.hpp"
30 #include "mergeresults.hpp"
31 #include "transform.hpp"
32 
33 #ifdef CYCLE_PROFILING
34 #include "profiler.hpp"
35 #endif
36 
37 namespace arm_gemm {
38 
39 namespace {
40 
41 template<typename OutputStage>
42 class run_gemv_kernel {
43 public:
44  template<typename strategy, typename To, typename Tr>
45  static void run (
46  const strategy &strat,
47  const To *A_ptr, const To *B_ptr, Tr *c_ptr,
48  size_t N, size_t K,
49  const Tr *bias, const Activation &act, bool Accumulate,
50  const OutputStage &os, const int32_t *col_bias, unsigned int col_base
51  );
52 };
53 
54 template<>
55 template<typename strategy, typename To, typename Tr>
57  const strategy &strat,
58  const To *A_ptr, const To *B_ptr, Tr *C_ptr,
59  size_t N, size_t K,
60  const Tr *bias, const Activation &act, bool Accumulate,
61  const Nothing &, const int32_t *, unsigned int
62  ) {
63 
64  strat.kernel(A_ptr, B_ptr, C_ptr, N, K, bias, act, Accumulate);
65 }
66 
67 template<>
68 template<typename strategy, typename To, typename Tr>
70  const strategy &strat,
71  const To *A_ptr, const To *B_ptr, Tr *C_ptr,
72  size_t N, size_t K,
73  const Tr *, const Activation &, bool,
74  const Requantize32 &qp, const int32_t *col_bias, unsigned int col_base
75  ) {
76 
77  strat.kernel(A_ptr, B_ptr, C_ptr, N, K, &qp, col_bias + col_base, col_base);
78 }
79 
80 } // anonymous namespace
81 
82 // Implementation of the GemmCommon abstract class.
83 //
84 // This is implementation is for GEMV with pretransposition.
85 //
86 // batches are not supported as a batched GEMV makes no sense (can be converted to a GEMM).
87 template<typename strategy, typename To, typename Tr, typename OutputStage=Nothing>
88 class GemvPretransposed : public GemmCommon<To, Tr> {
89  typedef typename strategy::operand_type Toi;
90  typedef typename strategy::result_type Tri;
91 
92  const GemmArgs _args;
93 
94  const unsigned int _buffer_per_multi;
95 
96  unsigned int k_block=0;
97  unsigned int n_block=0;
98 
99  const Toi *_B_pretransposed = nullptr;
100 
101  OutputStage _os;
102 
103  // Pointer to the column sums (for quantized cases)
104  int32_t *col_bias = nullptr;
105 
106  // Get size of the column sums
107  unsigned int get_col_sum_size() const {
108  if(std::is_same<OutputStage, Requantize32>::value) {
109  return _args._Nsize * _args._nmulti * sizeof(int32_t);
110  } else {
111  return 0;
112  }
113  }
114 
115 public:
117  GemvPretransposed & operator= (GemvPretransposed &) = delete;
118 
119  GemvPretransposed(const GemmArgs &args, const OutputStage &os = {})
120  : _args(args),
121  _buffer_per_multi(roundup(args._Ksize, strategy::k_unroll()) * roundup(args._Nsize, strategy::out_width())),
122  _os(os) {
123  /* For now don't do any blocking. TODO: figure out if we should. */
124  if (strategy::supports_accumulate() && args._cfg && args._cfg->inner_block_size) {
125  k_block = args._cfg->inner_block_size;
126  } else {
127  k_block = args._Ksize;
128  }
129 
130  if (args._cfg && args._cfg->outer_block_size) {
131  n_block = args._cfg->outer_block_size;
132  } else {
133  n_block = args._Nsize;
134  }
135  }
136 
137  // Window is number of out_width blocks, times number of multis.
138  ndrange_t get_window_size() const override {
139  return { iceildiv(_args._Nsize, strategy::out_width()) * _args._nmulti };
140  }
141 
142  // Actually execute the GEMV.
143  void execute(const ndcoord_t &work_range, const ndcoord_t &, int) override {
144 #ifdef CYCLE_PROFILING
145  profiler prof;
146 #endif
147  strategy strat(_args._ci);
148 
149  const auto start = work_range.get_position(0);
150  const auto end = work_range.get_position_end(0);
151 
152  /* Break the window values down into multis of interest... */
153  const unsigned int window_per_multi = iceildiv(_args._Nsize, strategy::out_width());
154  const unsigned int multi_0 = start / window_per_multi;
155  const unsigned int multi_end = end / window_per_multi;
156 
157  /* ... and figure out where we start and end in the first and last multi. */
158  const unsigned int n_0 = (start - (multi_0 * window_per_multi)) * strategy::out_width();
159  const unsigned int n_max = (end - (multi_end * window_per_multi)) * strategy::out_width();
160 
161  static_assert(std::is_same<Tr, Tri>::value, "GemvPretransposed: Result types must be the same.");
162 
163  for (unsigned int multi=multi_0; multi<=multi_end; multi++) {
164  const unsigned int n_start = (multi==multi_0) ? n_0 : 0;
165  const unsigned int n_end = (multi==multi_end) ? n_max : _args._Nsize;
166 
167  if (n_end <= n_start)
168  continue;
169 
170  for (unsigned int k0=0; k0<_args._Ksize; k0+=k_block) {
171  unsigned int kmax = std::min(k0 + k_block, _args._Ksize);
172 
173  for (unsigned int n=n_start; n<n_end; n+=n_block) {
174  unsigned int nmax = std::min(n + n_block, n_end);
175 #ifdef CYCLE_PROFILING
176  auto p = prof.ScopedProfiler(PROFILE_KERNEL, (kmax-k0) * (nmax-n));
177 #endif
178  run_gemv_kernel<OutputStage>::run(strat, this->_Aptr + (multi * this->_A_multi_stride) + k0,
179  _B_pretransposed + (multi * _buffer_per_multi) + (n * roundup(_args._Ksize, strategy::k_unroll())) + (k0 * strategy::out_width()),
180  this->_Cptr + (multi * this->_C_multi_stride) + n,
181  (nmax - n), (kmax-k0),
182  this->_bias ? this->_bias + (multi * this->_bias_multi_stride) + n : nullptr,
183  _args._act, (k0 != 0),
184  _os, col_bias, n + (_args._Nsize * multi));
185  }
186  }
187  }
188  }
189 
190  /* Pretransposed interface implementation */
191  bool B_is_pretransposed() const override {
192  return true;
193  }
194 
195  bool B_pretranspose_required() const override {
196  /* Transpose is required if _B_pretransposed is still nullptr */
197  return (_B_pretransposed == nullptr);
198  }
199 
200  size_t get_B_pretransposed_array_size() const override {
201  return _buffer_per_multi * _args._nmulti * sizeof(To) + get_col_sum_size();
202  }
203 
204  void requantize_bias(void *in_buffer, const To *B, const int ldb, const int B_multi_stride) override {
205  // Column sums go on the front of the pretransposed buffer in requantized cases.
206  // We could optimize here in case we don't actually need to sum the columns, but this code is only run on setup.
207  if (std::is_same<OutputStage, Requantize32>::value) {
208  col_bias = reinterpret_cast<int32_t *>(in_buffer);
209 
210  Requantize32 *qp_ptr = reinterpret_cast<Requantize32 *>(&_os);
211 
212  for (unsigned int i=0; i<_args._nmulti; i++) {
213  compute_col_sums(*qp_ptr, _args._Nsize, _args._Ksize, B + (i * B_multi_stride), ldb, col_bias + (i * _args._Nsize), _args._Ksize, i, 0);
214  }
215  }
216  }
217 
218  void pretranspose_B_array(void *buffer, const To *B, const int ldb, const int B_multi_stride) override {
219  requantize_bias(buffer, B, ldb, B_multi_stride);
220 
221  // The actual transposed buffer goes after the column sums (if any)
222  uintptr_t buffer_int = reinterpret_cast<uintptr_t>(buffer);
223  Toi *B_buffer = reinterpret_cast<Toi *>(buffer_int + get_col_sum_size());
224 
225  strategy strat(_args._ci);
226 
227  for (unsigned int multi=0; multi<_args._nmulti; multi++) {
228  strat.transforms.PrepareB(B_buffer + (multi * _buffer_per_multi), B + (multi * B_multi_stride), ldb, 0, _args._Nsize, 0, _args._Ksize);
229  }
230 
231  _B_pretransposed = B_buffer;
232  }
233 
234  void set_pretransposed_B_data(void *buffer) override {
235  _B_pretransposed = reinterpret_cast<Toi *>(buffer);
236  }
237 
238  GemmConfig get_config() override {
239  GemmConfig c;
240 
242  c.inner_block_size = k_block;
243  c.outer_block_size = n_block;
244  c.filter = get_type_name<strategy>();
245 
246  return c;
247  }
248 };
249 
250 } // namespace arm_gemm
T roundup(const T a, const T b)
Definition: utils.hpp:70
const CPUInfo * _ci
Definition: arm_gemm.hpp:104
unsigned int _nmulti
Definition: arm_gemm.hpp:110
void set_pretransposed_B_data(void *buffer) override
unsigned int _Nsize
Definition: arm_gemm.hpp:106
Activation _act
Definition: arm_gemm.hpp:112
T iceildiv(const T a, const T b)
Definition: utils.hpp:65
const GemmConfig * _cfg
Definition: arm_gemm.hpp:115
unsigned int inner_block_size
Definition: arm_gemm.hpp:70
unsigned int outer_block_size
Definition: arm_gemm.hpp:71
void pretranspose_B_array(void *buffer, const To *B, const int ldb, const int B_multi_stride) override
int_t get_position(int_t d) const
Definition: ndrange.hpp:176
GemmConfig get_config() override
bool B_is_pretransposed() const override
GemmMethod method
Definition: arm_gemm.hpp:68
bool B_pretranspose_required() const override
unsigned int N
void end(TokenStream &in, bool &valid)
Definition: MLGOParser.cpp:290
void requantize_bias(void *in_buffer, const To *B, const int ldb, const int B_multi_stride) override
const StratType * strategy
ndrange_t get_window_size() const override
NDCoordinate builds upon a range, but specifies a starting position in addition to a size which it in...
Definition: ndrange.hpp:151
GemvPretransposed(const GemmArgs &args, const OutputStage &os={})
void compute_col_sums(const Requantize32 &qp, unsigned int width, unsigned int height, const T *input, unsigned int in_stride, int32_t *col_bias, unsigned int depth, unsigned int multi, unsigned int first_col)
void execute(const ndcoord_t &work_range, const ndcoord_t &, int) override
Main execute member fucntion.
std::string filter
Definition: arm_gemm.hpp:69
unsigned int _Ksize
Definition: arm_gemm.hpp:107
int_t get_position_end(int_t d) const
Definition: ndrange.hpp:190
size_t get_B_pretransposed_array_size() const override
const int32_t * bias
unsigned int K