forked from vllm-project/vllm
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathmatrix_view.cuh
295 lines (257 loc) · 9.66 KB
/
matrix_view.cuh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
/*
Adapted from https://github.com/turboderp/exllamav2 and
https://github.com/turboderp/exllama
*/
#ifndef _matrix_view_cuh
#define _matrix_view_cuh
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include "qdq_util.cuh"
namespace vllm {
namespace gptq {
class MatrixView_half {
public:
const half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half(const half* data, const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ half item(int row, int column) const {
return data[row * width + column];
}
__device__ __forceinline__ half2 item_half2(int row, int column) const {
return ((half2*)data)[(row * width + column) / 2];
}
__device__ __forceinline__ half2 item_half2half2(int row, int column) const {
return __half2half2(data[row * width + column]);
}
__device__ __forceinline__ const half* item_ptr(int row, int column) const {
return &data[row * width + column];
}
__device__ __forceinline__ void item4(half (&items)[4], int row,
int column) const {
half2* ptr = (half2*)item_ptr(row, column);
half2 i01 = ptr[0];
half2 i23 = ptr[1];
items[0] = __low2half(i01);
items[1] = __high2half(i01);
items[2] = __low2half(i23);
items[3] = __high2half(i23);
}
__device__ __forceinline__ void item4_f(float (&items)[4], int row,
int column) const {
half2* ptr = (half2*)item_ptr(row, column);
half2 i01 = ptr[0];
half2 i23 = ptr[1];
items[0] = __half2float(__low2half(i01));
items[1] = __half2float(__high2half(i01));
items[2] = __half2float(__low2half(i23));
items[3] = __half2float(__high2half(i23));
}
__device__ __forceinline__ void item4_h2(half2 (&items)[4], int row,
int column) const {
half2* ptr = (half2*)item_ptr(row, column);
half2 i01 = ptr[0];
half2 i23 = ptr[1];
items[0] = __half2half2(__low2half(i01));
items[1] = __half2half2(__high2half(i01));
items[2] = __half2half2(__low2half(i23));
items[3] = __half2half2(__high2half(i23));
}
};
class MatrixView_half_rw {
public:
half* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_half_rw(half* data, const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ half item(int row, int column) const {
return data[row * width + column];
}
__device__ __forceinline__ half2 item_half2(int row, int column) const {
return ((half2*)data)[(row * width + column) / 2];
}
__device__ __forceinline__ half* item_ptr(int row, int column) {
return &data[row * width + column];
}
__device__ __forceinline__ void set(int row, int column, half value) {
data[row * width + column] = value;
}
__device__ __forceinline__ void set_half2(int row, int column, half2 value) {
((half2*)data)[(row * width + column) / 2] = value;
}
__device__ __forceinline__ void set4(int row, int column, half v0, half v1,
half v2, half v3) {
half2 v01 = __halves2half2(v0, v1);
half2 v23 = __halves2half2(v2, v3);
half2* ptr = (half2*)item_ptr(row, column);
ptr[0] = v01;
ptr[1] = v23;
}
};
class MatrixView_q4_row {
public:
const uint32_t* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_q4_row(const uint32_t* data,
const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ int item(int row, int column) const {
int shift = (column & 0x07) * 4;
return (data[row * width / 8 + column / 8] >> shift) & 0x0f;
}
__device__ __forceinline__ void item2(int (&items)[2], int row,
int column) const {
int shift = (column & 0x07) * 4;
uint32_t d = data[row * width / 8 + column / 8] >> shift;
items[0] = d & 0x0f;
items[1] = (d >> 4) & 0x0f;
}
__device__ __forceinline__ void item4(int (&items)[4], int row,
int column) const {
int shift = (column & 0x07) * 4;
uint32_t d = data[row * width / 8 + column / 8] >> shift;
items[0] = d & 0x0f;
items[1] = (d >> 4) & 0x0f;
items[2] = (d >> 8) & 0x0f;
items[3] = (d >> 12) & 0x0f;
}
};
class MatrixView_q4_column {
public:
const uint32_t* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_q4_column(const uint32_t* data,
const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ int item(int row, int column) const {
int shift = (row & 0x07) * 4;
return (data[row / 8 * width + column] >> shift) & 0x0f;
}
__device__ __forceinline__ uint32_t item_uint32_t(int row, int column) {
return data[row / 8 * width + column];
}
__device__ __forceinline__ const uint32_t* item_uint32_ptr(int row,
int column) {
return &data[row / 8 * width + column];
}
};
class MatrixView_q2_row {
public:
const uint32_t* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_q2_row(const uint32_t* data,
const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ int item(int row, int column) const {
int shift = (column & 0x0f) * 2;
return (data[row * width / 16 + column / 16] >> shift) & 0x03;
}
__device__ __forceinline__ void item2(int (&items)[2], int row,
int column) const {
int shift = (column & 0x0f) * 2;
uint32_t d = data[row * width / 16 + column / 16] >> shift;
items[0] = d & 0x03;
items[1] = (d >> 2) & 0x03;
}
__device__ __forceinline__ void item4(int (&items)[4], int row,
int column) const {
int shift = (column & 0x0f) * 2;
uint32_t d = data[row * width / 16 + column / 16] >> shift;
items[0] = d & 0x03;
items[1] = (d >> 2) & 0x03;
items[2] = (d >> 4) & 0x03;
items[3] = (d >> 6) & 0x03;
}
};
class MatrixView_q3_row {
public:
const uint32_t* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_q3_row(const uint32_t* data,
const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ int item(int row, int column) const {
int z_w = column * 3 / 32;
int z_mod = column & 0x1f;
if (z_mod == 10) {
return (data[row * width * 3 / 32 + z_w] >> 30) |
((data[row * width * 3 / 32 + (z_w + 1)] << 2) & 0x4);
} else if (z_mod == 21) {
return (data[row * width * 3 / 32 + z_w] >> 31) |
((data[row * width * 3 / 32 + (z_w + 1)] << 1) & 0x6);
} else if (z_mod < 10) {
return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3)) & 0x07;
} else if (z_mod < 21) {
return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3 - 32)) & 0x07;
} else {
return (data[row * width * 3 / 32 + z_w] >> (z_mod * 3 - 64)) & 0x07;
}
}
__device__ __forceinline__ void item4(int (&items)[4], int row,
int column) const {
int shift = (column & 0x1f);
uint32_t d;
if (shift <= 4) {
d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3);
} else if (shift == 8) {
d = (data[row * width / 32 * 3 + column * 3 / 32] >> 24) |
((data[row * width / 32 * 3 + column * 3 / 32 + 1] & 0x0f) << 8);
} else if (shift <= 16) {
d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3 - 32);
} else if (shift == 20) {
d = (data[row * width / 32 * 3 + column * 3 / 32] >> 28) |
((data[row * width / 32 * 3 + column * 3 / 32 + 1] & 0xff) << 4);
} else {
d = data[row * width / 32 * 3 + column * 3 / 32] >> (shift * 3 - 64);
}
items[0] = d & 0x07;
items[1] = (d >> 3) & 0x07;
items[2] = (d >> 6) & 0x07;
items[3] = (d >> 9) & 0x07;
}
};
class MatrixView_q8_row {
public:
const uint32_t* data;
const int height;
const int width;
__device__ __forceinline__ MatrixView_q8_row(const uint32_t* data,
const int height,
const int width)
: data(data), height(height), width(width) {}
__device__ __forceinline__ int item(int row, int column) const {
int shift = (column & 0x03) * 8;
return (data[row * width / 4 + column / 4] >> shift) & 0xff;
}
__device__ __forceinline__ void item2(int (&items)[2], int row,
int column) const {
int shift = (column & 0x03) * 8;
uint32_t d = data[row * width / 4 + column / 4] >> shift;
items[0] = d & 0xff;
items[1] = (d >> 8) & 0xff;
}
__device__ __forceinline__ void item4(int (&items)[4], int row,
int column) const {
int shift = (column & 0x03) * 2;
uint32_t d = data[row * width / 4 + column / 4] >> shift;
items[0] = d & 0xff;
items[1] = (d >> 8) & 0xff;
items[2] = (d >> 16) & 0xff;
items[3] = (d >> 24) & 0xff;
}
};
} // namespace gptq
} // namespace vllm
#endif