File size: 12,701 Bytes
bf4d3fe | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 | #include <cublasLt.h>
#include <cuda_bf16.h>
#include <cuda_runtime.h>
#include <math.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
typedef struct {
int m;
int n;
int k;
int warmup;
int iters;
int skip_reference;
} pyc_hopper_cublaslt_bf16_config;
static int parse_int_arg(const char* text, int* out_value) {
char* end = NULL;
long parsed;
if (!text || !out_value) {
return -1;
}
parsed = strtol(text, &end, 10);
if (end == text || *end != '\0' || parsed < 0 || parsed > INT32_MAX) {
return -1;
}
*out_value = (int)parsed;
return 0;
}
static int env_flag(const char* name, int default_value) {
const char* raw = getenv(name);
if (!raw || raw[0] == '\0') {
return default_value;
}
if (
strcmp(raw, "1") == 0 || strcmp(raw, "true") == 0 || strcmp(raw, "TRUE") == 0
|| strcmp(raw, "yes") == 0 || strcmp(raw, "on") == 0) {
return 1;
}
if (
strcmp(raw, "0") == 0 || strcmp(raw, "false") == 0 || strcmp(raw, "FALSE") == 0
|| strcmp(raw, "no") == 0 || strcmp(raw, "off") == 0) {
return 0;
}
return default_value;
}
static int check_cuda(cudaError_t status, const char* what) {
if (status != cudaSuccess) {
fprintf(stderr, "%s failed: %s\n", what, cudaGetErrorString(status));
return -1;
}
return 0;
}
static int check_cublas(cublasStatus_t status, const char* what) {
if (status != CUBLAS_STATUS_SUCCESS) {
fprintf(stderr, "%s failed: cublas status %d\n", what, (int)status);
return -1;
}
return 0;
}
static void fill_matrix(__nv_bfloat16* data, int rows, int cols, float scale) {
int i;
for (i = 0; i < rows * cols; ++i) {
int pattern = (i * 23 + rows * 13 + cols * 5) % 31;
data[i] = __float2bfloat16(((float)pattern - 15.0f) * scale);
}
}
static void reference_gemm(
const __nv_bfloat16* a,
const __nv_bfloat16* b,
__nv_bfloat16* d,
int m,
int n,
int k) {
int row;
for (row = 0; row < m; ++row) {
int col;
for (col = 0; col < n; ++col) {
float acc = 0.0f;
int kk;
for (kk = 0; kk < k; ++kk) {
acc += __bfloat162float(a[row * k + kk]) * __bfloat162float(b[kk * n + col]);
}
d[row * n + col] = __float2bfloat16(acc);
}
}
}
static int parse_config(int argc, char** argv, pyc_hopper_cublaslt_bf16_config* cfg) {
if (!cfg) {
return -1;
}
cfg->m = 4096;
cfg->n = 4096;
cfg->k = 4096;
cfg->warmup = 3;
cfg->iters = 30;
cfg->skip_reference = env_flag("PYC_HOPPER_CUBLASLT_SKIP_REFERENCE", 1);
if (argc > 1 && parse_int_arg(argv[1], &cfg->m) != 0) return -1;
if (argc > 2 && parse_int_arg(argv[2], &cfg->n) != 0) return -1;
if (argc > 3 && parse_int_arg(argv[3], &cfg->k) != 0) return -1;
if (argc > 4 && parse_int_arg(argv[4], &cfg->warmup) != 0) return -1;
if (argc > 5 && parse_int_arg(argv[5], &cfg->iters) != 0) return -1;
if (argc > 6 && parse_int_arg(argv[6], &cfg->skip_reference) != 0) return -1;
return 0;
}
int main(int argc, char** argv) {
pyc_hopper_cublaslt_bf16_config cfg;
struct cudaDeviceProp props;
cublasLtHandle_t lt_handle = NULL;
cublasLtMatmulDesc_t op_desc = NULL;
cublasLtMatrixLayout_t a_layout = NULL;
cublasLtMatrixLayout_t b_layout = NULL;
cublasLtMatrixLayout_t c_layout = NULL;
cublasLtMatmulPreference_t pref = NULL;
cublasLtMatmulHeuristicResult_t heuristic;
int returned_results = 0;
cudaEvent_t start = NULL;
cudaEvent_t stop = NULL;
cudaStream_t stream = NULL;
__nv_bfloat16* host_a = NULL;
__nv_bfloat16* host_b = NULL;
__nv_bfloat16* host_d = NULL;
__nv_bfloat16* ref_d = NULL;
__nv_bfloat16* dev_a = NULL;
__nv_bfloat16* dev_b = NULL;
__nv_bfloat16* dev_d = NULL;
void* workspace = NULL;
size_t workspace_bytes = 64u * 1024u * 1024u;
size_t a_bytes;
size_t b_bytes;
size_t d_bytes;
float alpha = 1.0f;
float beta = 0.0f;
float elapsed_ms = 0.0f;
double best_ms = 0.0;
double max_abs_diff = 0.0;
int iter;
if (parse_config(argc, argv, &cfg) != 0) {
fprintf(stderr, "usage: %s [m] [n] [k] [warmup] [iters] [skip_reference]\n", argv[0]);
return 2;
}
if (check_cuda(cudaGetDeviceProperties(&props, 0), "cudaGetDeviceProperties") != 0) {
return 1;
}
if (props.major < 9) {
fprintf(stderr, "Hopper cuBLASLt BF16 prototype requires sm_90-class hardware\n");
return 1;
}
a_bytes = (size_t)cfg.m * (size_t)cfg.k * sizeof(__nv_bfloat16);
b_bytes = (size_t)cfg.k * (size_t)cfg.n * sizeof(__nv_bfloat16);
d_bytes = (size_t)cfg.m * (size_t)cfg.n * sizeof(__nv_bfloat16);
host_a = (__nv_bfloat16*)malloc(a_bytes);
host_b = (__nv_bfloat16*)malloc(b_bytes);
if (!host_a || !host_b) {
fprintf(stderr, "host allocation failed\n");
return 1;
}
if (!cfg.skip_reference) {
host_d = (__nv_bfloat16*)malloc(d_bytes);
ref_d = (__nv_bfloat16*)malloc(d_bytes);
if (!host_d || !ref_d) {
fprintf(stderr, "host validation allocation failed\n");
return 1;
}
}
fill_matrix(host_a, cfg.m, cfg.k, 0.03125f);
fill_matrix(host_b, cfg.k, cfg.n, 0.0625f);
if (!cfg.skip_reference) {
reference_gemm(host_a, host_b, ref_d, cfg.m, cfg.n, cfg.k);
}
if (check_cuda(cudaMalloc((void**)&dev_a, a_bytes), "cudaMalloc(a)") != 0) return 1;
if (check_cuda(cudaMalloc((void**)&dev_b, b_bytes), "cudaMalloc(b)") != 0) return 1;
if (check_cuda(cudaMalloc((void**)&dev_d, d_bytes), "cudaMalloc(d)") != 0) return 1;
if (check_cuda(cudaMalloc(&workspace, workspace_bytes), "cudaMalloc(workspace)") != 0) return 1;
if (check_cuda(cudaMemcpy(dev_a, host_a, a_bytes, cudaMemcpyHostToDevice), "cudaMemcpy(a)") != 0) return 1;
if (check_cuda(cudaMemcpy(dev_b, host_b, b_bytes, cudaMemcpyHostToDevice), "cudaMemcpy(b)") != 0) return 1;
if (check_cuda(cudaMemset(dev_d, 0, d_bytes), "cudaMemset(d)") != 0) return 1;
if (check_cuda(cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking), "cudaStreamCreateWithFlags") != 0) return 1;
if (check_cublas(cublasLtCreate(<_handle), "cublasLtCreate") != 0) return 1;
if (check_cublas(cublasLtMatmulDescCreate(&op_desc, CUBLAS_COMPUTE_32F, CUDA_R_32F), "cublasLtMatmulDescCreate") != 0) return 1;
{
cublasOperation_t transa = CUBLAS_OP_N;
cublasOperation_t transb = CUBLAS_OP_N;
if (check_cublas(cublasLtMatmulDescSetAttribute(op_desc, CUBLASLT_MATMUL_DESC_TRANSA, &transa, sizeof(transa)), "cublasLtMatmulDescSetAttribute(TRANSA)") != 0) return 1;
if (check_cublas(cublasLtMatmulDescSetAttribute(op_desc, CUBLASLT_MATMUL_DESC_TRANSB, &transb, sizeof(transb)), "cublasLtMatmulDescSetAttribute(TRANSB)") != 0) return 1;
}
if (check_cublas(cublasLtMatrixLayoutCreate(&a_layout, CUDA_R_16BF, cfg.m, cfg.k, cfg.k), "cublasLtMatrixLayoutCreate(A)") != 0) return 1;
if (check_cublas(cublasLtMatrixLayoutCreate(&b_layout, CUDA_R_16BF, cfg.k, cfg.n, cfg.n), "cublasLtMatrixLayoutCreate(B)") != 0) return 1;
if (check_cublas(cublasLtMatrixLayoutCreate(&c_layout, CUDA_R_16BF, cfg.m, cfg.n, cfg.n), "cublasLtMatrixLayoutCreate(D)") != 0) return 1;
{
cublasLtOrder_t order = CUBLASLT_ORDER_ROW;
if (check_cublas(cublasLtMatrixLayoutSetAttribute(a_layout, CUBLASLT_MATRIX_LAYOUT_ORDER, &order, sizeof(order)), "cublasLtMatrixLayoutSetAttribute(A order)") != 0) return 1;
if (check_cublas(cublasLtMatrixLayoutSetAttribute(b_layout, CUBLASLT_MATRIX_LAYOUT_ORDER, &order, sizeof(order)), "cublasLtMatrixLayoutSetAttribute(B order)") != 0) return 1;
if (check_cublas(cublasLtMatrixLayoutSetAttribute(c_layout, CUBLASLT_MATRIX_LAYOUT_ORDER, &order, sizeof(order)), "cublasLtMatrixLayoutSetAttribute(D order)") != 0) return 1;
}
if (check_cublas(cublasLtMatmulPreferenceCreate(&pref), "cublasLtMatmulPreferenceCreate") != 0) return 1;
if (check_cublas(cublasLtMatmulPreferenceSetAttribute(pref, CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES, &workspace_bytes, sizeof(workspace_bytes)), "cublasLtMatmulPreferenceSetAttribute") != 0) return 1;
if (check_cublas(cublasLtMatmulAlgoGetHeuristic(lt_handle, op_desc, a_layout, b_layout, c_layout, c_layout, pref, 1, &heuristic, &returned_results), "cublasLtMatmulAlgoGetHeuristic") != 0) return 1;
if (returned_results <= 0) {
fprintf(stderr, "cublasLtMatmulAlgoGetHeuristic returned no algorithms\n");
return 1;
}
if (check_cuda(cudaEventCreate(&start), "cudaEventCreate(start)") != 0) return 1;
if (check_cuda(cudaEventCreate(&stop), "cudaEventCreate(stop)") != 0) return 1;
for (iter = 0; iter < cfg.warmup; ++iter) {
if (check_cublas(
cublasLtMatmul(
lt_handle,
op_desc,
&alpha,
dev_a,
a_layout,
dev_b,
b_layout,
&beta,
dev_d,
c_layout,
dev_d,
c_layout,
&heuristic.algo,
workspace,
workspace_bytes,
stream),
"cublasLtMatmul(warmup)")
!= 0) return 1;
}
if (check_cuda(cudaStreamSynchronize(stream), "cudaStreamSynchronize(warmup)") != 0) return 1;
for (iter = 0; iter < cfg.iters; ++iter) {
if (check_cuda(cudaEventRecord(start, stream), "cudaEventRecord(start)") != 0) return 1;
if (check_cublas(
cublasLtMatmul(
lt_handle,
op_desc,
&alpha,
dev_a,
a_layout,
dev_b,
b_layout,
&beta,
dev_d,
c_layout,
dev_d,
c_layout,
&heuristic.algo,
workspace,
workspace_bytes,
stream),
"cublasLtMatmul(bench)")
!= 0) return 1;
if (check_cuda(cudaEventRecord(stop, stream), "cudaEventRecord(stop)") != 0) return 1;
if (check_cuda(cudaEventSynchronize(stop), "cudaEventSynchronize(stop)") != 0) return 1;
if (check_cuda(cudaEventElapsedTime(&elapsed_ms, start, stop), "cudaEventElapsedTime") != 0) return 1;
if (iter == 0 || elapsed_ms < (float)best_ms) {
best_ms = elapsed_ms;
}
}
if (!cfg.skip_reference) {
int idx;
if (check_cuda(cudaMemcpy(host_d, dev_d, d_bytes, cudaMemcpyDeviceToHost), "cudaMemcpy(d)") != 0) return 1;
for (idx = 0; idx < cfg.m * cfg.n; ++idx) {
double diff = fabs((double)__bfloat162float(host_d[idx]) - (double)__bfloat162float(ref_d[idx]));
if (diff > max_abs_diff) {
max_abs_diff = diff;
}
}
}
printf("kernel=hopper_cublaslt_bf16\n");
printf("arch=sm%d%d\n", props.major, props.minor);
printf("shape=%dx%dx%d\n", cfg.m, cfg.n, cfg.k);
printf("workspace_bytes=%zu\n", workspace_bytes);
printf("heuristic_workspace_bytes=%zu\n", heuristic.workspaceSize);
printf("skip_reference=%d\n", cfg.skip_reference);
printf("best_ms=%.3f\n", best_ms);
if (!cfg.skip_reference) {
printf("max_abs_diff=%.6f\n", max_abs_diff);
}
if (best_ms > 0.0) {
double flops = 2.0 * (double)cfg.m * (double)cfg.n * (double)cfg.k;
double gflops = flops / (best_ms * 1.0e6);
printf("gflops=%.3f\n", gflops);
printf("tflops=%.3f\n", gflops / 1000.0);
}
if (start) cudaEventDestroy(start);
if (stop) cudaEventDestroy(stop);
if (stream) cudaStreamDestroy(stream);
if (pref) cublasLtMatmulPreferenceDestroy(pref);
if (c_layout) cublasLtMatrixLayoutDestroy(c_layout);
if (b_layout) cublasLtMatrixLayoutDestroy(b_layout);
if (a_layout) cublasLtMatrixLayoutDestroy(a_layout);
if (op_desc) cublasLtMatmulDescDestroy(op_desc);
if (lt_handle) cublasLtDestroy(lt_handle);
if (workspace) cudaFree(workspace);
if (dev_d) cudaFree(dev_d);
if (dev_b) cudaFree(dev_b);
if (dev_a) cudaFree(dev_a);
free(ref_d);
free(host_d);
free(host_b);
free(host_a);
return (cfg.skip_reference || max_abs_diff <= 0.25) ? 0 : 1;
}
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