| 1 | // Benchmark quantization specific functions on synthetic data |
| 2 | |
| 3 | #include "ggml.h" |
| 4 | #include "ggml-cpu.h" |
| 5 | |
| 6 | #undef NDEBUG |
| 7 | #include <algorithm> |
| 8 | #include <assert.h> |
| 9 | #include <functional> |
| 10 | #include <math.h> |
| 11 | #include <memory> |
| 12 | #include <stdio.h> |
| 13 | #include <string> |
| 14 | #include <vector> |
| 15 | |
| 16 | #if defined(_MSC_VER) |
| 17 | #pragma warning(disable: 4244 4267) // possible loss of data |
| 18 | #endif |
| 19 | |
| 20 | #define MAX_ALIGNMENT 64 |
| 21 | #define QK 32 |
| 22 | #define WARMUP 5 |
| 23 | #define ITERATIONS 10 |
| 24 | #define MAX_ITERATIONS 100000000 |
| 25 | |
| 26 | #define L1_SIZE 32*128 |
| 27 | #define L2_SIZE 32*2048 |
| 28 | #define L3_SIZE 32*20480 |
| 29 | #define MEM_SIZE 32*2048000 |
| 30 | |
| 31 | struct quantize_perf_params { |
| 32 | std::vector<std::string> include_types; |
| 33 | std::vector<size_t> test_sizes; |
| 34 | size_t alignment_offset = 0; |
| 35 | bool op_quantize_row_q_reference = false; |
| 36 | bool op_quantize_row_q = false; |
| 37 | bool op_dequantize_row_q = false; |
| 38 | bool op_quantize_row_q_dot = false; |
| 39 | bool op_vec_dot_q = false; |
| 40 | int64_t iterations = ITERATIONS; |
| 41 | }; |
| 42 | |
| 43 | #if defined(__x86_64__) || defined(__i386__) |
| 44 | |
| 45 | #include <x86intrin.h> |
| 46 | inline int64_t cpu_cycles() { |
| 47 | // Rough way to detect new-ish CPUs |
| 48 | #ifdef __POPCNT__ |
| 49 | unsigned int dummy; |
| 50 | return __rdtscp(&dummy); |
| 51 | #else |
| 52 | return __rdtsc(); |
| 53 | #endif |
| 54 | } |
| 55 | |
| 56 | #else |
| 57 | |
| 58 | #define cpu_cycles() 0 |
| 59 | |
| 60 | #endif |
| 61 | |
| 62 | |
| 63 | // Generate synthetic data |
| 64 | static void generate_data(float offset, size_t n, float * dst) { |
| 65 | for (size_t i = 0; i < n; i++) { |
| 66 | dst[i] = 0.1 + 2*cosf(x: i + offset); |
| 67 | } |
| 68 | } |
| 69 | |
| 70 | static float gigabytes_per_second(size_t bytes, int64_t usecs) { |
| 71 | return bytes / (float) usecs * 1000000 / (1024*1024*1024); |
| 72 | } |
| 73 | |
| 74 | static void * align_with_offset(void * ptr, int offset) { |
| 75 | size_t dummy_size = MAX_ALIGNMENT * 4; |
| 76 | return (char *) std::align(MAX_ALIGNMENT, MAX_ALIGNMENT, ptr&: ptr, space&: dummy_size) + offset; |
| 77 | } |
| 78 | |
| 79 | static void benchmark_function(size_t size, size_t q_size, int64_t iterations, const std::function<float(void)> & func) { |
| 80 | int64_t min_time_us = INT64_MAX; |
| 81 | int64_t total_time_us = 0; |
| 82 | int64_t min_time_cycles = INT64_MAX; |
| 83 | int64_t total_time_cycles = 0; |
| 84 | |
| 85 | for (int i = 0; i < WARMUP; i++) { |
| 86 | func(); |
| 87 | } |
| 88 | |
| 89 | for (int i = 0; i < iterations; i++) { |
| 90 | const int64_t start_time = ggml_time_us(); |
| 91 | const int64_t start_cycles = cpu_cycles(); |
| 92 | |
| 93 | func(); |
| 94 | |
| 95 | const int64_t end_cycles = cpu_cycles(); |
| 96 | const int64_t end_time = ggml_time_us(); |
| 97 | |
| 98 | total_time_cycles += end_cycles - start_cycles; |
| 99 | min_time_cycles = std::min(a: min_time_cycles, b: end_cycles - start_cycles); |
| 100 | total_time_us += end_time - start_time; |
| 101 | min_time_us = std::min(a: min_time_us, b: end_time - start_time); |
| 102 | } |
| 103 | |
| 104 | printf(format: " min cycles/%d vals : %9.2f\n" , QK, QK * min_time_cycles / (float) size); |
| 105 | printf(format: " avg cycles/%d vals : %9.2f\n" , QK, QK * total_time_cycles / (float) (size * iterations)); |
| 106 | printf(format: " float32 throughput : %9.2f GB/s\n" , gigabytes_per_second(bytes: 4 * size * iterations, usecs: total_time_us)); |
| 107 | printf(format: " quantized throughput : %9.2f GB/s\n" , gigabytes_per_second(bytes: q_size * iterations, usecs: total_time_us)); |
| 108 | } |
| 109 | |
| 110 | static void usage(char * argv[]) { |
| 111 | printf(format: "Benchmark quantization specific functions on synthetic data\n" ); |
| 112 | printf(format: "\n" ); |
| 113 | printf(format: "usage: %s [options]\n" , argv[0]); |
| 114 | printf(format: "\n" ); |
| 115 | printf(format: "options: (default)\n" ); |
| 116 | printf(format: " -h, --help show this help message and exit\n" ); |
| 117 | printf(format: " --size SIZE set test size, divisible by 32 (L1_SIZE:%d)\n" , L1_SIZE); |
| 118 | printf(format: " -3 use size as L1, L2, L3 sizes (L1:%d L2:%d L3:%d)\n" , L1_SIZE, L2_SIZE, L3_SIZE); |
| 119 | printf(format: " -4 use size as L1, L2, L3, MEM sizes (L1:%d L2:%d L3:%d MEM:%d)\n" , L1_SIZE, L2_SIZE, L3_SIZE, MEM_SIZE); |
| 120 | printf(format: " --op OP set test operation as quantize_row_q_reference, quantize_row_q, dequantize_row_q,\n" ); |
| 121 | printf(format: " quantize_row_q_dot, vec_dot_q (all)\n" ); |
| 122 | printf(format: " --type TYPE set test type as" ); |
| 123 | for (int i = 0; i < GGML_TYPE_COUNT; i++) { |
| 124 | ggml_type type = (ggml_type) i; |
| 125 | const auto * qfns = ggml_get_type_traits(type); |
| 126 | const auto * qfns_cpu = ggml_get_type_traits_cpu(type); |
| 127 | if (ggml_type_name(type) != NULL) { |
| 128 | if (qfns_cpu->from_float && qfns->to_float) { |
| 129 | printf(format: " %s" , ggml_type_name(type)); |
| 130 | } |
| 131 | } |
| 132 | } |
| 133 | printf(format: " (all)\n" ); |
| 134 | printf(format: " --alignment-offset OFFSET\n" ); |
| 135 | printf(format: " set alignment offset as OFFSET (0)\n" ); |
| 136 | printf(format: " -i NUM, --iterations NUM\n" ); |
| 137 | printf(format: " set test iteration number (%d)\n" , ITERATIONS); |
| 138 | } |
| 139 | |
| 140 | int main(int argc, char * argv[]) { |
| 141 | quantize_perf_params params {}; |
| 142 | |
| 143 | // read command line |
| 144 | |
| 145 | bool invalid_param = false; |
| 146 | std::string arg; |
| 147 | for (int i = 1; i < argc; i++) { |
| 148 | arg = argv[i]; |
| 149 | |
| 150 | if (arg == "--size" ) { |
| 151 | if (++i >= argc) { |
| 152 | invalid_param = true; |
| 153 | break; |
| 154 | } |
| 155 | size_t size = std::stoi(str: argv[i]); |
| 156 | if (size % 32 != 0) { |
| 157 | fprintf(stderr, format: "error: size %zu not divisible by 32\n" , size); |
| 158 | invalid_param = true; |
| 159 | break; |
| 160 | } |
| 161 | params.test_sizes.push_back(x: size); |
| 162 | } else if (arg == "-3" ) { |
| 163 | // quick select sizes that probably fit in CPU caches |
| 164 | params.test_sizes.push_back(L1_SIZE); |
| 165 | params.test_sizes.push_back(L2_SIZE); |
| 166 | params.test_sizes.push_back(L3_SIZE); |
| 167 | } else if (arg == "-4" ) { |
| 168 | // quick select cache sizes + memory |
| 169 | params.test_sizes.push_back(L1_SIZE); |
| 170 | params.test_sizes.push_back(L2_SIZE); |
| 171 | params.test_sizes.push_back(L3_SIZE); |
| 172 | params.test_sizes.push_back(MEM_SIZE); |
| 173 | } else if (arg == "--op" ) { |
| 174 | if (++i >= argc) { |
| 175 | invalid_param = true; |
| 176 | break; |
| 177 | } |
| 178 | std::string op {argv[i]}; |
| 179 | if (op == "quantize_row_q_reference" ) { |
| 180 | params.op_quantize_row_q_reference = true; |
| 181 | } else if (op == "quantize_row_q" ) { |
| 182 | params.op_quantize_row_q = true; |
| 183 | } else if (op == "dequantize_row_q" ) { |
| 184 | params.op_dequantize_row_q = true; |
| 185 | } else if (op == "quantize_row_q_dot" ) { |
| 186 | params.op_quantize_row_q_dot = true; |
| 187 | } else if (op == "vec_dot_q" ) { |
| 188 | params.op_vec_dot_q = true; |
| 189 | } else { |
| 190 | invalid_param = true; |
| 191 | break; |
| 192 | } |
| 193 | } else if (arg == "--type" ) { |
| 194 | if (++i >= argc) { |
| 195 | invalid_param = true; |
| 196 | break; |
| 197 | } |
| 198 | params.include_types.push_back(x: argv[i]); |
| 199 | } else if (arg == "--alignment-offset" ) { |
| 200 | if (++i >= argc) { |
| 201 | invalid_param = true; |
| 202 | break; |
| 203 | } |
| 204 | int alignment = std::stoi(str: argv[i]); |
| 205 | if (alignment < 0 || alignment > MAX_ALIGNMENT) { |
| 206 | fprintf(stderr, format: "error: alignment-offset must be less than %d\n" , MAX_ALIGNMENT); |
| 207 | invalid_param = true; |
| 208 | break; |
| 209 | } |
| 210 | params.alignment_offset = alignment; |
| 211 | } else if ((arg == "-i" ) || (arg == "--iterations" )) { |
| 212 | if (++i >= argc) { |
| 213 | invalid_param = true; |
| 214 | break; |
| 215 | } |
| 216 | int number = std::stoi(str: argv[i]); |
| 217 | if (number < 0 || number > MAX_ITERATIONS) { |
| 218 | fprintf(stderr, format: "error: iterations must be less than %d\n" , MAX_ITERATIONS); |
| 219 | invalid_param = true; |
| 220 | break; |
| 221 | } |
| 222 | params.iterations = number; |
| 223 | } else if ((arg == "-h" ) || (arg == "--help" )) { |
| 224 | usage(argv); |
| 225 | return 1; |
| 226 | } else { |
| 227 | fprintf(stderr, format: "error: unknown argument: %s\n" , arg.c_str()); |
| 228 | return 1; |
| 229 | } |
| 230 | } |
| 231 | if (invalid_param) { |
| 232 | fprintf(stderr, format: "error: invalid parameter for argument: %s\n" , arg.c_str()); |
| 233 | return 1; |
| 234 | } |
| 235 | |
| 236 | if (params.test_sizes.empty()) { |
| 237 | params.test_sizes.push_back(L1_SIZE); |
| 238 | } |
| 239 | if (!(params.op_quantize_row_q_reference || params.op_quantize_row_q || params.op_dequantize_row_q || params.op_quantize_row_q_dot || params.op_vec_dot_q)) { |
| 240 | params.op_quantize_row_q_reference = params.op_quantize_row_q = params.op_dequantize_row_q = params.op_quantize_row_q_dot = params.op_vec_dot_q = true; |
| 241 | } |
| 242 | |
| 243 | std::sort(first: params.test_sizes.begin(), last: params.test_sizes.end()); |
| 244 | size_t largest = params.test_sizes.back(); |
| 245 | |
| 246 | std::vector<uint8_t> test_data1_v(largest*4 + MAX_ALIGNMENT*2); |
| 247 | std::vector<uint8_t> test_data2_v(largest*4 + MAX_ALIGNMENT*2); |
| 248 | std::vector<uint8_t> test_q1_v (largest*4 + MAX_ALIGNMENT*2); |
| 249 | std::vector<uint8_t> test_q2_v (largest*4 + MAX_ALIGNMENT*2); |
| 250 | std::vector<uint8_t> test_out_v (largest*4 + MAX_ALIGNMENT*2); |
| 251 | |
| 252 | float * test_data1 = (float *) align_with_offset(ptr: test_data1_v.data(), offset: params.alignment_offset); |
| 253 | float * test_data2 = (float *) align_with_offset(ptr: test_data2_v.data(), offset: params.alignment_offset); |
| 254 | float * test_q1 = (float *) align_with_offset(ptr: test_q1_v.data(), offset: params.alignment_offset); |
| 255 | float * test_q2 = (float *) align_with_offset(ptr: test_q2_v.data(), offset: params.alignment_offset); |
| 256 | float * test_out = (float *) align_with_offset(ptr: test_out_v.data(), offset: params.alignment_offset); |
| 257 | |
| 258 | generate_data(offset: 0, n: largest, dst: test_data1); |
| 259 | generate_data(offset: 1, n: largest, dst: test_data2); |
| 260 | |
| 261 | int64_t iterations = params.iterations; |
| 262 | |
| 263 | ggml_cpu_init(); |
| 264 | |
| 265 | for (int i = 0; i < GGML_TYPE_COUNT; i++) { |
| 266 | ggml_type type = (ggml_type) i; |
| 267 | const auto * qfns = ggml_get_type_traits(type); |
| 268 | const auto * qfns_cpu = ggml_get_type_traits_cpu(type); |
| 269 | if (!params.include_types.empty() && ggml_type_name(type) && std::find(first: params.include_types.begin(), last: params.include_types.end(), val: ggml_type_name(type)) == params.include_types.end()) { |
| 270 | continue; |
| 271 | } |
| 272 | |
| 273 | if (qfns_cpu->from_float && qfns->to_float) { |
| 274 | printf(format: "%s\n" , ggml_type_name(type)); |
| 275 | |
| 276 | ggml_quantize_init(type); |
| 277 | |
| 278 | if (params.op_quantize_row_q_reference) { |
| 279 | printf(format: " quantize_row_q_reference\n" ); |
| 280 | for (size_t size : params.test_sizes) { |
| 281 | printf(format: " %zu values (%.2f MB)\n" , size, 4*size/(float)(1024*1024)); |
| 282 | auto quantize_fn = [&](void) -> float { |
| 283 | qfns->from_float_ref(test_data1, test_q1, size); |
| 284 | return test_q1[0]; |
| 285 | }; |
| 286 | size_t quantized_size = ggml_row_size(type, ne: size); |
| 287 | benchmark_function(size, q_size: quantized_size, iterations, func: quantize_fn); |
| 288 | } |
| 289 | printf(format: "\n" ); |
| 290 | } |
| 291 | |
| 292 | if (params.op_quantize_row_q) { |
| 293 | printf(format: " quantize_row_q\n" ); |
| 294 | for (size_t size : params.test_sizes) { |
| 295 | printf(format: " %zu values (%.2f MB)\n" , size, 4*size/(float)(1024*1024)); |
| 296 | auto quantize_fn = [&](void) -> float { |
| 297 | qfns_cpu->from_float(test_data1, test_q1, size); |
| 298 | return test_q1[0]; |
| 299 | }; |
| 300 | size_t quantized_size = ggml_row_size(type, ne: size); |
| 301 | benchmark_function(size, q_size: quantized_size, iterations, func: quantize_fn); |
| 302 | } |
| 303 | printf(format: "\n" ); |
| 304 | } |
| 305 | |
| 306 | if (params.op_dequantize_row_q) { |
| 307 | printf(format: " dequantize_row_q\n" ); |
| 308 | qfns_cpu->from_float(test_data1, test_q1, largest); |
| 309 | for (size_t size : params.test_sizes) { |
| 310 | printf(format: " %zu values (%.2f MB)\n" , size, 4*size/(float)(1024*1024)); |
| 311 | auto quantize_fn = [&](void) -> float { |
| 312 | qfns->to_float(test_q1, test_out, size); |
| 313 | return test_out[0]; |
| 314 | }; |
| 315 | size_t quantized_size = ggml_row_size(type, ne: size); |
| 316 | benchmark_function(size, q_size: quantized_size, iterations, func: quantize_fn); |
| 317 | } |
| 318 | printf(format: "\n" ); |
| 319 | } |
| 320 | |
| 321 | if (params.op_quantize_row_q_dot) { |
| 322 | printf(format: " quantize_row_q_dot\n" ); |
| 323 | for (size_t size : params.test_sizes) { |
| 324 | printf(format: " %zu values (%.2f MB)\n" , size, 4*size/(float)(1024*1024)); |
| 325 | auto quantize_fn = [&](void) -> float { |
| 326 | const auto * vdot = ggml_get_type_traits_cpu(type: qfns_cpu->vec_dot_type); |
| 327 | vdot->from_float(test_data1, test_q1, size); |
| 328 | return test_q1[0]; |
| 329 | }; |
| 330 | size_t quantized_size = ggml_row_size(type, ne: size); |
| 331 | benchmark_function(size, q_size: quantized_size, iterations, func: quantize_fn); |
| 332 | } |
| 333 | printf(format: "\n" ); |
| 334 | } |
| 335 | |
| 336 | if (params.op_vec_dot_q) { |
| 337 | printf(format: " vec_dot_q\n" ); |
| 338 | qfns_cpu->from_float(test_data1, test_q1, largest); |
| 339 | qfns_cpu->from_float(test_data2, test_q2, largest); |
| 340 | for (size_t size : params.test_sizes) { |
| 341 | printf(format: " %zu values (%.2f MB)\n" , size, 4*size/(float)(1024*1024)); |
| 342 | auto quantize_fn = [&](void) -> float { |
| 343 | float result; |
| 344 | qfns_cpu->vec_dot(size, &result, 0, test_q1, 0, test_q2, 0, 1); |
| 345 | return result; |
| 346 | }; |
| 347 | size_t quantized_size = ggml_row_size(type, ne: size); |
| 348 | benchmark_function(size, q_size: quantized_size, iterations, func: quantize_fn); |
| 349 | } |
| 350 | printf(format: "\n" ); |
| 351 | } |
| 352 | } |
| 353 | } |
| 354 | |
| 355 | return 0; |
| 356 | } |
| 357 | |