ggml-metal.m 48 KB

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  1. #import "ggml-metal.h"
  2. #import "ggml.h"
  3. #import <Foundation/Foundation.h>
  4. #import <Metal/Metal.h>
  5. #import <MetalPerformanceShaders/MetalPerformanceShaders.h>
  6. #ifdef GGML_METAL_NDEBUG
  7. #define metal_printf(...)
  8. #else
  9. #define metal_printf(...) fprintf(stderr, __VA_ARGS__)
  10. #endif
  11. #define UNUSED(x) (void)(x)
  12. struct ggml_metal_buffer {
  13. const char * name;
  14. void * data;
  15. size_t size;
  16. id<MTLBuffer> metal;
  17. };
  18. struct ggml_metal_context {
  19. float * logits;
  20. id<MTLDevice> device;
  21. id<MTLCommandQueue> queue;
  22. id<MTLLibrary> library;
  23. int n_buffers;
  24. struct ggml_metal_buffer buffers[GGML_METAL_MAX_BUFFERS];
  25. // custom kernels
  26. #define GGML_METAL_DECL_KERNEL(name) \
  27. id<MTLFunction> function_##name; \
  28. id<MTLComputePipelineState> pipeline_##name
  29. GGML_METAL_DECL_KERNEL(add);
  30. GGML_METAL_DECL_KERNEL(mul);
  31. GGML_METAL_DECL_KERNEL(mul_row); // TODO: avoid this extra kernel, instead extend the "mul" kernel to support broadcast
  32. GGML_METAL_DECL_KERNEL(scale);
  33. GGML_METAL_DECL_KERNEL(silu);
  34. GGML_METAL_DECL_KERNEL(relu);
  35. GGML_METAL_DECL_KERNEL(gelu);
  36. GGML_METAL_DECL_KERNEL(soft_max);
  37. GGML_METAL_DECL_KERNEL(diag_mask_inf);
  38. GGML_METAL_DECL_KERNEL(get_rows_f16);
  39. GGML_METAL_DECL_KERNEL(get_rows_q4_0);
  40. GGML_METAL_DECL_KERNEL(get_rows_q4_1);
  41. GGML_METAL_DECL_KERNEL(get_rows_q2_k);
  42. GGML_METAL_DECL_KERNEL(get_rows_q3_k);
  43. GGML_METAL_DECL_KERNEL(get_rows_q4_k);
  44. GGML_METAL_DECL_KERNEL(get_rows_q5_k);
  45. GGML_METAL_DECL_KERNEL(get_rows_q6_k);
  46. GGML_METAL_DECL_KERNEL(rms_norm);
  47. GGML_METAL_DECL_KERNEL(norm);
  48. GGML_METAL_DECL_KERNEL(mul_mat_f16_f32);
  49. GGML_METAL_DECL_KERNEL(mul_mat_q4_0_f32);
  50. GGML_METAL_DECL_KERNEL(mul_mat_q4_1_f32);
  51. GGML_METAL_DECL_KERNEL(mul_mat_q2_k_f32);
  52. GGML_METAL_DECL_KERNEL(mul_mat_q3_k_f32);
  53. GGML_METAL_DECL_KERNEL(mul_mat_q4_k_f32);
  54. GGML_METAL_DECL_KERNEL(mul_mat_q5_k_f32);
  55. GGML_METAL_DECL_KERNEL(mul_mat_q6_k_f32);
  56. GGML_METAL_DECL_KERNEL(rope);
  57. GGML_METAL_DECL_KERNEL(alibi_f32);
  58. GGML_METAL_DECL_KERNEL(cpy_f32_f16);
  59. GGML_METAL_DECL_KERNEL(cpy_f32_f32);
  60. GGML_METAL_DECL_KERNEL(cpy_f16_f16);
  61. #undef GGML_METAL_DECL_KERNEL
  62. };
  63. // MSL code
  64. // TODO: move the contents here when ready
  65. // for now it is easier to work in a separate file
  66. static NSString * const msl_library_source = @"see metal.metal";
  67. // Here to assist with NSBundle Path Hack
  68. @interface GGMLMetalClass : NSObject
  69. @end
  70. @implementation GGMLMetalClass
  71. @end
  72. struct ggml_metal_context * ggml_metal_init(void) {
  73. fprintf(stderr, "%s: allocating\n", __func__);
  74. struct ggml_metal_context * ctx = malloc(sizeof(struct ggml_metal_context));
  75. ctx->device = MTLCreateSystemDefaultDevice();
  76. ctx->queue = [ctx->device newCommandQueue];
  77. ctx->n_buffers = 0;
  78. // determine if we can use MPS
  79. if (MPSSupportsMTLDevice(ctx->device)) {
  80. fprintf(stderr, "%s: using MPS\n", __func__);
  81. } else {
  82. fprintf(stderr, "%s: not using MPS\n", __func__);
  83. GGML_ASSERT(false && "MPS not supported");
  84. }
  85. #if 0
  86. // compile from source string and show compile log
  87. {
  88. NSError * error = nil;
  89. ctx->library = [ctx->device newLibraryWithSource:msl_library_source options:nil error:&error];
  90. if (error) {
  91. fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
  92. exit(1);
  93. }
  94. }
  95. #else
  96. UNUSED(msl_library_source);
  97. // read the source from "ggml-metal.metal" into a string and use newLibraryWithSource
  98. {
  99. NSError * error = nil;
  100. //NSString * path = [[NSBundle mainBundle] pathForResource:@"../../examples/metal/metal" ofType:@"metal"];
  101. NSBundle * bundle = [NSBundle bundleForClass:[GGMLMetalClass class]];
  102. NSString * path = [bundle pathForResource:@"ggml-metal" ofType:@"metal"];
  103. fprintf(stderr, "%s: loading '%s'\n", __func__, [path UTF8String]);
  104. NSString * src = [NSString stringWithContentsOfFile:path encoding:NSUTF8StringEncoding error:&error];
  105. if (error) {
  106. fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
  107. exit(1);
  108. }
  109. ctx->library = [ctx->device newLibraryWithSource:src options:nil error:&error];
  110. if (error) {
  111. fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
  112. exit(1);
  113. }
  114. }
  115. #endif
  116. // load kernels
  117. {
  118. #define GGML_METAL_ADD_KERNEL(name) \
  119. ctx->function_##name = [ctx->library newFunctionWithName:@"kernel_"#name]; \
  120. ctx->pipeline_##name = [ctx->device newComputePipelineStateWithFunction:ctx->function_##name error:nil]; \
  121. fprintf(stderr, "%s: loaded %-32s %16p\n", __func__, "kernel_"#name, (void *) ctx->pipeline_##name);
  122. GGML_METAL_ADD_KERNEL(add);
  123. GGML_METAL_ADD_KERNEL(mul);
  124. GGML_METAL_ADD_KERNEL(mul_row);
  125. GGML_METAL_ADD_KERNEL(scale);
  126. GGML_METAL_ADD_KERNEL(silu);
  127. GGML_METAL_ADD_KERNEL(relu);
  128. GGML_METAL_ADD_KERNEL(gelu);
  129. GGML_METAL_ADD_KERNEL(soft_max);
  130. GGML_METAL_ADD_KERNEL(diag_mask_inf);
  131. GGML_METAL_ADD_KERNEL(get_rows_f16);
  132. GGML_METAL_ADD_KERNEL(get_rows_q4_0);
  133. GGML_METAL_ADD_KERNEL(get_rows_q4_1);
  134. GGML_METAL_ADD_KERNEL(get_rows_q2_k);
  135. GGML_METAL_ADD_KERNEL(get_rows_q3_k);
  136. GGML_METAL_ADD_KERNEL(get_rows_q4_k);
  137. GGML_METAL_ADD_KERNEL(get_rows_q5_k);
  138. GGML_METAL_ADD_KERNEL(get_rows_q6_k);
  139. GGML_METAL_ADD_KERNEL(rms_norm);
  140. GGML_METAL_ADD_KERNEL(norm);
  141. GGML_METAL_ADD_KERNEL(mul_mat_f16_f32);
  142. GGML_METAL_ADD_KERNEL(mul_mat_q4_0_f32);
  143. GGML_METAL_ADD_KERNEL(mul_mat_q4_1_f32);
  144. GGML_METAL_ADD_KERNEL(mul_mat_q2_k_f32);
  145. GGML_METAL_ADD_KERNEL(mul_mat_q3_k_f32);
  146. GGML_METAL_ADD_KERNEL(mul_mat_q4_k_f32);
  147. GGML_METAL_ADD_KERNEL(mul_mat_q5_k_f32);
  148. GGML_METAL_ADD_KERNEL(mul_mat_q6_k_f32);
  149. GGML_METAL_ADD_KERNEL(rope);
  150. GGML_METAL_ADD_KERNEL(alibi_f32);
  151. GGML_METAL_ADD_KERNEL(cpy_f32_f16);
  152. GGML_METAL_ADD_KERNEL(cpy_f32_f32);
  153. GGML_METAL_ADD_KERNEL(cpy_f16_f16);
  154. #undef GGML_METAL_ADD_KERNEL
  155. }
  156. fprintf(stderr, "%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
  157. fprintf(stderr, "%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false");
  158. if (ctx->device.maxTransferRate != 0) {
  159. fprintf(stderr, "%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1024.0 / 1024.0);
  160. } else {
  161. fprintf(stderr, "%s: maxTransferRate = built-in GPU\n", __func__);
  162. }
  163. return ctx;
  164. }
  165. void ggml_metal_free(struct ggml_metal_context * ctx) {
  166. fprintf(stderr, "%s: deallocating\n", __func__);
  167. free(ctx);
  168. }
  169. // finds the Metal buffer that contains the tensor data on the GPU device
  170. // the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the
  171. // Metal buffer based on the host memory pointer
  172. //
  173. static id<MTLBuffer> ggml_metal_get_buffer(struct ggml_metal_context * ctx, struct ggml_tensor * t, size_t * offs) {
  174. //fprintf(stderr, "%s: data tensor '%16s', offs_data = %8ld, offs_eval = %8ld, offs_cach = %8ld\n", __func__, t->name, offs_data, offs_eval, offs_cach);
  175. const int64_t tsize = ggml_nbytes(t);
  176. // find the view that contains the tensor fully
  177. for (int i = 0; i < ctx->n_buffers; ++i) {
  178. const int64_t ioffs = (int64_t) t->data - (int64_t) ctx->buffers[i].data;
  179. if (ioffs >= 0 && ioffs + tsize <= (int64_t) ctx->buffers[i].size) {
  180. *offs = (size_t) ioffs;
  181. //fprintf(stderr, "%s: '%s' tensor '%16s', offs = %8ld\n", __func__, ctx->buffers[i].name, t->name, *offs);
  182. return ctx->buffers[i].metal;
  183. }
  184. }
  185. fprintf(stderr, "%s: error: buffer is nil\n", __func__);
  186. return nil;
  187. }
  188. bool ggml_metal_add_buffer(
  189. struct ggml_metal_context * ctx,
  190. const char * name,
  191. void * data,
  192. size_t size,
  193. size_t max_size) {
  194. if (ctx->n_buffers >= GGML_METAL_MAX_BUFFERS) {
  195. fprintf(stderr, "%s: too many buffers\n", __func__);
  196. return false;
  197. }
  198. if (data) {
  199. // verify that the buffer does not overlap with any of the existing buffers
  200. for (int i = 0; i < ctx->n_buffers; ++i) {
  201. const int64_t ioffs = (int64_t) data - (int64_t) ctx->buffers[i].data;
  202. if (ioffs >= 0 && ioffs < (int64_t) ctx->buffers[i].size) {
  203. fprintf(stderr, "%s: error: buffer '%s' overlaps with '%s'\n", __func__, name, ctx->buffers[i].name);
  204. return false;
  205. }
  206. }
  207. const size_t size_page = getpagesize();
  208. size_t size_aligned = size;
  209. if ((size_aligned % size_page) != 0) {
  210. size_aligned += (size_page - (size_aligned % size_page));
  211. }
  212. // the buffer fits into the max buffer size allowed by the device
  213. if (size_aligned <= ctx->device.maxBufferLength) {
  214. ctx->buffers[ctx->n_buffers].name = name;
  215. ctx->buffers[ctx->n_buffers].data = data;
  216. ctx->buffers[ctx->n_buffers].size = size;
  217. ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:data length:size_aligned options:MTLResourceStorageModeShared deallocator:nil];
  218. if (ctx->buffers[ctx->n_buffers].metal == nil) {
  219. fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_aligned / 1024.0 / 1024.0);
  220. return false;
  221. }
  222. fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB", __func__, name, size_aligned / 1024.0 / 1024.0);
  223. ++ctx->n_buffers;
  224. } else {
  225. // this overlap between the views will guarantee that the tensor with the maximum size will fully fit into
  226. // one of the views
  227. const size_t size_ovlp = ((max_size + size_page - 1) / size_page + 1) * size_page; // round-up 2 pages just in case
  228. const size_t size_step = ctx->device.maxBufferLength - size_ovlp;
  229. const size_t size_view = ctx->device.maxBufferLength;
  230. for (size_t i = 0; i < size; i += size_step) {
  231. const size_t size_step_aligned = (i + size_view <= size) ? size_view : (size_aligned - i);
  232. ctx->buffers[ctx->n_buffers].name = name;
  233. ctx->buffers[ctx->n_buffers].data = (void *) ((uint8_t *) data + i);
  234. ctx->buffers[ctx->n_buffers].size = size_step_aligned;
  235. ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:(void *) ((uint8_t *) data + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil];
  236. if (ctx->buffers[ctx->n_buffers].metal == nil) {
  237. fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_step_aligned / 1024.0 / 1024.0);
  238. return false;
  239. }
  240. fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB, offs = %12ld", __func__, name, size_step_aligned / 1024.0 / 1024.0, i);
  241. if (i + size_step < size) {
  242. fprintf(stderr, "\n");
  243. }
  244. ++ctx->n_buffers;
  245. }
  246. }
  247. fprintf(stderr, ", (%8.2f / %8.2f)",
  248. ctx->device.currentAllocatedSize / 1024.0 / 1024.0,
  249. ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
  250. if (ctx->device.currentAllocatedSize > ctx->device.recommendedMaxWorkingSetSize) {
  251. fprintf(stderr, ", warning: current allocated size is greater than the recommended max working set size\n");
  252. } else {
  253. fprintf(stderr, "\n");
  254. }
  255. }
  256. return true;
  257. }
  258. void ggml_metal_set_tensor(
  259. struct ggml_metal_context * ctx,
  260. struct ggml_tensor * t) {
  261. metal_printf("%s: set input for tensor '%s'\n", __func__, t->name);
  262. size_t offs;
  263. id<MTLBuffer> id_dst = ggml_metal_get_buffer(ctx, t, &offs);
  264. memcpy((void *) ((uint8_t *) id_dst.contents + offs), t->data, ggml_nbytes(t));
  265. }
  266. void ggml_metal_get_tensor(
  267. struct ggml_metal_context * ctx,
  268. struct ggml_tensor * t) {
  269. metal_printf("%s: extract results for tensor '%s'\n", __func__, t->name);
  270. size_t offs;
  271. id<MTLBuffer> id_src = ggml_metal_get_buffer(ctx, t, &offs);
  272. memcpy(t->data, (void *) ((uint8_t *) id_src.contents + offs), ggml_nbytes(t));
  273. }
  274. void ggml_metal_graph_compute(
  275. struct ggml_metal_context * ctx,
  276. struct ggml_cgraph * gf) {
  277. metal_printf("%s: evaluating graph\n", __func__);
  278. // create multiple command buffers and enqueue them
  279. // then, we encode the graph into the command buffers in parallel
  280. const int n_cb = gf->n_threads;
  281. NSMutableArray * command_buffers = [NSMutableArray arrayWithCapacity:n_cb];
  282. for (int i = 0; i < n_cb; ++i) {
  283. command_buffers[i] = [ctx->queue commandBuffer];
  284. // enqueue the command buffers in order to specify their execution order
  285. [command_buffers[i] enqueue];
  286. }
  287. // TODO: is this the best way to start threads?
  288. dispatch_queue_t queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);
  289. for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) {
  290. const int n_nodes_per_cb = (gf->n_nodes + n_cb - 1) / n_cb;
  291. dispatch_async(queue, ^{
  292. size_t offs_src0 = 0;
  293. size_t offs_src1 = 0;
  294. size_t offs_dst = 0;
  295. id<MTLCommandBuffer> command_buffer = command_buffers[cb_idx];
  296. id<MTLComputeCommandEncoder> encoder = nil;
  297. const int node_start = (cb_idx + 0) * n_nodes_per_cb;
  298. const int node_end = (cb_idx == n_cb - 1) ? gf->n_nodes : (cb_idx + 1) * n_nodes_per_cb;
  299. for (int i = node_start; i < node_end; ++i) {
  300. metal_printf("%s: encoding node %3d, op = %8s\n", __func__, i, ggml_op_name(gf->nodes[i]->op));
  301. struct ggml_tensor * src0 = gf->nodes[i]->src0;
  302. struct ggml_tensor * src1 = gf->nodes[i]->src1;
  303. struct ggml_tensor * dst = gf->nodes[i];
  304. const int64_t ne00 = src0 ? src0->ne[0] : 0;
  305. const int64_t ne01 = src0 ? src0->ne[1] : 0;
  306. const int64_t ne02 = src0 ? src0->ne[2] : 0;
  307. const int64_t ne03 = src0 ? src0->ne[3] : 0;
  308. const uint64_t nb00 = src0 ? src0->nb[0] : 0;
  309. const uint64_t nb01 = src0 ? src0->nb[1] : 0;
  310. const uint64_t nb02 = src0 ? src0->nb[2] : 0;
  311. const uint64_t nb03 = src0 ? src0->nb[3] : 0;
  312. const int64_t ne10 = src1 ? src1->ne[0] : 0;
  313. const int64_t ne11 = src1 ? src1->ne[1] : 0;
  314. const int64_t ne12 = src1 ? src1->ne[2] : 0;
  315. const int64_t ne13 = src1 ? src1->ne[3] : 0; UNUSED(ne13);
  316. const uint64_t nb10 = src1 ? src1->nb[0] : 0;
  317. const uint64_t nb11 = src1 ? src1->nb[1] : 0;
  318. const uint64_t nb12 = src1 ? src1->nb[2] : 0;
  319. const uint64_t nb13 = src1 ? src1->nb[3] : 0; UNUSED(nb13);
  320. const int64_t ne0 = dst ? dst->ne[0] : 0;
  321. const int64_t ne1 = dst ? dst->ne[1] : 0;
  322. const int64_t ne2 = dst ? dst->ne[2] : 0;
  323. const int64_t ne3 = dst ? dst->ne[3] : 0;
  324. const uint64_t nb0 = dst ? dst->nb[0] : 0;
  325. const uint64_t nb1 = dst ? dst->nb[1] : 0;
  326. const uint64_t nb2 = dst ? dst->nb[2] : 0;
  327. const uint64_t nb3 = dst ? dst->nb[3] : 0;
  328. const enum ggml_type src0t = src0 ? src0->type : GGML_TYPE_COUNT;
  329. const enum ggml_type src1t = src1 ? src1->type : GGML_TYPE_COUNT;
  330. const enum ggml_type dstt = dst ? dst->type : GGML_TYPE_COUNT;
  331. id<MTLBuffer> id_src0 = src0 ? ggml_metal_get_buffer(ctx, src0, &offs_src0) : nil;
  332. id<MTLBuffer> id_src1 = src1 ? ggml_metal_get_buffer(ctx, src1, &offs_src1) : nil;
  333. id<MTLBuffer> id_dst = dst ? ggml_metal_get_buffer(ctx, dst, &offs_dst) : nil;
  334. //metal_printf("%s: op - %s\n", __func__, ggml_op_name(dst->op));
  335. //if (src0) {
  336. // metal_printf("%s: src0 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src0t), ne00, ne01, ne02,
  337. // ggml_is_contiguous(src0), src0->name);
  338. //}
  339. //if (src1) {
  340. // metal_printf("%s: src1 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src1t), ne10, ne11, ne12,
  341. // ggml_is_contiguous(src1), src1->name);
  342. //}
  343. //if (dst) {
  344. // metal_printf("%s: dst - %4s [%5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(dstt), ne0, ne1, ne2,
  345. // dst->name);
  346. //}
  347. switch (dst->op) {
  348. case GGML_OP_RESHAPE:
  349. case GGML_OP_VIEW:
  350. case GGML_OP_TRANSPOSE:
  351. case GGML_OP_PERMUTE:
  352. {
  353. // noop
  354. } break;
  355. case GGML_OP_ADD:
  356. {
  357. if (encoder == nil) {
  358. encoder = [command_buffer computeCommandEncoder];
  359. }
  360. [encoder setComputePipelineState:ctx->pipeline_add];
  361. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  362. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  363. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  364. const int64_t n = ggml_nelements(dst);
  365. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  366. } break;
  367. case GGML_OP_MUL:
  368. {
  369. if (encoder == nil) {
  370. encoder = [command_buffer computeCommandEncoder];
  371. }
  372. if (ggml_nelements(src1) == ne10) {
  373. // src1 is a row
  374. [encoder setComputePipelineState:ctx->pipeline_mul_row];
  375. } else {
  376. [encoder setComputePipelineState:ctx->pipeline_mul];
  377. }
  378. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  379. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  380. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  381. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
  382. const int64_t n = ggml_nelements(dst);
  383. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  384. } break;
  385. case GGML_OP_SCALE:
  386. {
  387. if (encoder == nil) {
  388. encoder = [command_buffer computeCommandEncoder];
  389. }
  390. const float scale = *(const float *) src1->data;
  391. [encoder setComputePipelineState:ctx->pipeline_scale];
  392. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  393. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  394. [encoder setBytes:&scale length:sizeof(scale) atIndex:2];
  395. const int64_t n = ggml_nelements(dst);
  396. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  397. } break;
  398. case GGML_OP_SILU:
  399. {
  400. if (encoder == nil) {
  401. encoder = [command_buffer computeCommandEncoder];
  402. }
  403. [encoder setComputePipelineState:ctx->pipeline_silu];
  404. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  405. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  406. const int64_t n = ggml_nelements(dst);
  407. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  408. } break;
  409. case GGML_OP_RELU:
  410. {
  411. if (encoder == nil) {
  412. encoder = [command_buffer computeCommandEncoder];
  413. }
  414. [encoder setComputePipelineState:ctx->pipeline_relu];
  415. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  416. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  417. const int64_t n = ggml_nelements(dst);
  418. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  419. } break;
  420. case GGML_OP_GELU:
  421. {
  422. if (encoder == nil) {
  423. encoder = [command_buffer computeCommandEncoder];
  424. }
  425. [encoder setComputePipelineState:ctx->pipeline_gelu];
  426. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  427. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  428. const int64_t n = ggml_nelements(dst);
  429. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  430. } break;
  431. case GGML_OP_SOFT_MAX:
  432. {
  433. if (encoder == nil) {
  434. encoder = [command_buffer computeCommandEncoder];
  435. }
  436. const int nth = 32;
  437. [encoder setComputePipelineState:ctx->pipeline_soft_max];
  438. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  439. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  440. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
  441. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:3];
  442. [encoder setBytes:&ne02 length:sizeof(ne02) atIndex:4];
  443. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  444. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  445. } break;
  446. case GGML_OP_DIAG_MASK_INF:
  447. {
  448. if (encoder == nil) {
  449. encoder = [command_buffer computeCommandEncoder];
  450. }
  451. const int n_past = ((int32_t *)(src1->data))[0];
  452. [encoder setComputePipelineState:ctx->pipeline_diag_mask_inf];
  453. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  454. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  455. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
  456. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:3];
  457. [encoder setBytes:&n_past length:sizeof(int) atIndex:4];
  458. [encoder dispatchThreadgroups:MTLSizeMake(ne00, ne01, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  459. } break;
  460. case GGML_OP_MUL_MAT:
  461. {
  462. // TODO: needs to be updated after PR: https://github.com/ggerganov/ggml/pull/224
  463. GGML_ASSERT(ne00 == ne10);
  464. GGML_ASSERT(ne02 == ne12);
  465. if (ggml_is_contiguous(src0) &&
  466. ggml_is_contiguous(src1) &&
  467. (src0t == GGML_TYPE_F32 || src0t == GGML_TYPE_F16) && ne11 > 1) {
  468. if (encoder != nil) {
  469. [encoder endEncoding];
  470. encoder = nil;
  471. }
  472. MPSDataType src0dt = src0t == GGML_TYPE_F32 ? MPSDataTypeFloat32 : MPSDataTypeFloat16;
  473. MPSDataType src1dt = src1t == GGML_TYPE_F32 ? MPSDataTypeFloat32 : MPSDataTypeFloat16;
  474. // for F32 x F32 we use MPS
  475. MPSMatrixDescriptor * desc0 = [MPSMatrixDescriptor
  476. matrixDescriptorWithRows:ne01 columns:ne00 rowBytes:src0->nb[1] dataType:src0dt];
  477. MPSMatrixDescriptor * desc1 = [MPSMatrixDescriptor
  478. matrixDescriptorWithRows:ne11 columns:ne10 rowBytes:src1->nb[1] dataType:src1dt];
  479. MPSMatrixDescriptor * desc = [MPSMatrixDescriptor
  480. matrixDescriptorWithRows:ne1 columns:ne0 rowBytes:dst->nb[1] dataType:MPSDataTypeFloat32];
  481. MPSMatrixMultiplication * mul = [[MPSMatrixMultiplication alloc]
  482. initWithDevice:ctx->device transposeLeft:false transposeRight:true
  483. resultRows:ne11 resultColumns:ne01 interiorColumns:ne00 alpha:1.0 beta:0.0];
  484. // we need to do ne02 multiplications
  485. // TODO: is there a way to do this in parallel - currently very slow ..
  486. // TODO: might be possible to offload part of the computation to ANE using Accelerate's CBLAS
  487. for (int64_t i02 = 0; i02 < ne02; ++i02) {
  488. size_t offs_src0_cur = offs_src0 + i02*nb02;
  489. size_t offs_src1_cur = offs_src1 + i02*nb12;
  490. size_t offs_dst_cur = offs_dst + i02*nb2;
  491. MPSMatrix * mat_src0 = [[MPSMatrix alloc] initWithBuffer:id_src0 offset:offs_src0_cur descriptor:desc0];
  492. MPSMatrix * mat_src1 = [[MPSMatrix alloc] initWithBuffer:id_src1 offset:offs_src1_cur descriptor:desc1];
  493. MPSMatrix * mat_dst = [[MPSMatrix alloc] initWithBuffer:id_dst offset:offs_dst_cur descriptor:desc ];
  494. [mul encodeToCommandBuffer:command_buffer leftMatrix:mat_src1 rightMatrix:mat_src0 resultMatrix:mat_dst];
  495. }
  496. } else {
  497. if (encoder == nil) {
  498. encoder = [command_buffer computeCommandEncoder];
  499. }
  500. int nth0 = 32;
  501. int nth1 = 1;
  502. // use custom matrix x vector kernel
  503. switch (src0t) {
  504. case GGML_TYPE_F16:
  505. {
  506. GGML_ASSERT(ne02 == ne12);
  507. nth0 = 64;
  508. nth1 = 1;
  509. [encoder setComputePipelineState:ctx->pipeline_mul_mat_f16_f32];
  510. } break;
  511. case GGML_TYPE_Q4_0:
  512. {
  513. GGML_ASSERT(ne02 == 1);
  514. GGML_ASSERT(ne12 == 1);
  515. nth0 = 8;
  516. nth1 = 8;
  517. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_0_f32];
  518. } break;
  519. case GGML_TYPE_Q4_1:
  520. {
  521. GGML_ASSERT(ne02 == 1);
  522. GGML_ASSERT(ne12 == 1);
  523. nth0 = 8;
  524. nth1 = 8;
  525. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_1_f32];
  526. } break;
  527. case GGML_TYPE_Q2_K:
  528. {
  529. GGML_ASSERT(ne02 == 1);
  530. GGML_ASSERT(ne12 == 1);
  531. nth0 = 4;
  532. nth1 = 16;
  533. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_k_f32];
  534. } break;
  535. case GGML_TYPE_Q3_K:
  536. {
  537. GGML_ASSERT(ne02 == 1);
  538. GGML_ASSERT(ne12 == 1);
  539. nth0 = 4;
  540. nth1 = 16;
  541. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q3_k_f32];
  542. } break;
  543. case GGML_TYPE_Q4_K:
  544. {
  545. GGML_ASSERT(ne02 == 1);
  546. GGML_ASSERT(ne12 == 1);
  547. nth0 = 4;
  548. nth1 = 16;
  549. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_k_f32];
  550. } break;
  551. case GGML_TYPE_Q5_K:
  552. {
  553. GGML_ASSERT(ne02 == 1);
  554. GGML_ASSERT(ne12 == 1);
  555. nth0 = 4;
  556. nth1 = 16;
  557. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q5_k_f32];
  558. } break;
  559. case GGML_TYPE_Q6_K:
  560. {
  561. GGML_ASSERT(ne02 == 1);
  562. GGML_ASSERT(ne12 == 1);
  563. nth0 = 4;
  564. nth1 = 16;
  565. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_k_f32];
  566. } break;
  567. default:
  568. {
  569. fprintf(stderr, "Asserting on type %d\n",(int)src0t);
  570. GGML_ASSERT(false && "not implemented");
  571. }
  572. };
  573. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  574. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  575. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  576. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
  577. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:4];
  578. [encoder setBytes:&nb00 length:sizeof(nb00) atIndex:5];
  579. [encoder setBytes:&nb01 length:sizeof(nb01) atIndex:6];
  580. [encoder setBytes:&nb02 length:sizeof(nb02) atIndex:7];
  581. [encoder setBytes:&ne10 length:sizeof(ne10) atIndex:8];
  582. [encoder setBytes:&ne11 length:sizeof(ne11) atIndex:9];
  583. [encoder setBytes:&nb10 length:sizeof(nb10) atIndex:10];
  584. [encoder setBytes:&nb11 length:sizeof(nb11) atIndex:11];
  585. [encoder setBytes:&nb12 length:sizeof(nb12) atIndex:12];
  586. [encoder setBytes:&ne0 length:sizeof(ne0) atIndex:13];
  587. [encoder setBytes:&ne1 length:sizeof(ne1) atIndex:14];
  588. if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1) {
  589. [encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
  590. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  591. }
  592. else if (src0t == GGML_TYPE_Q2_K ||
  593. src0t == GGML_TYPE_Q3_K ||
  594. src0t == GGML_TYPE_Q4_K ||
  595. src0t == GGML_TYPE_Q5_K ||
  596. src0t == GGML_TYPE_Q6_K) {
  597. [encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
  598. [encoder dispatchThreadgroups:MTLSizeMake(ne01, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  599. } else {
  600. [encoder setThreadgroupMemoryLength:nth0*sizeof(float) atIndex:0];
  601. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, ne12) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  602. }
  603. }
  604. } break;
  605. case GGML_OP_GET_ROWS:
  606. {
  607. if (encoder == nil) {
  608. encoder = [command_buffer computeCommandEncoder];
  609. }
  610. switch (src0->type) {
  611. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_get_rows_f16]; break;
  612. case GGML_TYPE_Q4_0: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_0]; break;
  613. case GGML_TYPE_Q4_1: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_1]; break;
  614. case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_k]; break;
  615. case GGML_TYPE_Q3_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q3_k]; break;
  616. case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_k]; break;
  617. case GGML_TYPE_Q5_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q5_k]; break;
  618. case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_k]; break;
  619. default: GGML_ASSERT(false && "not implemented");
  620. }
  621. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  622. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  623. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  624. [encoder setBytes:&(src0->ne[0]) length:sizeof( int64_t) atIndex:3];
  625. [encoder setBytes:&(src0->nb[1]) length:sizeof(uint64_t) atIndex:4];
  626. [encoder setBytes:&(dst->nb[1]) length:sizeof(uint64_t) atIndex:5];
  627. const int64_t n = ggml_nelements(src1);
  628. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  629. } break;
  630. case GGML_OP_RMS_NORM:
  631. {
  632. if (encoder == nil) {
  633. encoder = [command_buffer computeCommandEncoder];
  634. }
  635. const float eps = 1e-6f;
  636. const int nth = 256;
  637. [encoder setComputePipelineState:ctx->pipeline_rms_norm];
  638. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  639. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  640. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  641. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3];
  642. [encoder setBytes:&eps length:sizeof( float) atIndex:4];
  643. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  644. const int64_t nrows = ggml_nrows(src0);
  645. [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  646. } break;
  647. case GGML_OP_NORM:
  648. {
  649. if (encoder == nil) {
  650. encoder = [command_buffer computeCommandEncoder];
  651. }
  652. const float eps = 1e-5f;
  653. const int nth = 256;
  654. [encoder setComputePipelineState:ctx->pipeline_norm];
  655. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  656. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  657. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  658. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3];
  659. [encoder setBytes:&eps length:sizeof( float) atIndex:4];
  660. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  661. const int64_t nrows = ggml_nrows(src0);
  662. [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  663. } break;
  664. case GGML_OP_ALIBI:
  665. {
  666. if (encoder == nil) {
  667. encoder = [command_buffer computeCommandEncoder];
  668. }
  669. GGML_ASSERT((src0t == GGML_TYPE_F32));
  670. const int n_past = ((int32_t *) src1->data)[0]; UNUSED(n_past);
  671. const int n_head = ((int32_t *) src1->data)[1];
  672. const float max_bias = ((float *) src1->data)[2];
  673. if (__builtin_popcount(n_head) != 1) {
  674. GGML_ASSERT(false && "only power-of-two n_head implemented");
  675. }
  676. const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
  677. const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor);
  678. [encoder setComputePipelineState:ctx->pipeline_alibi_f32];
  679. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  680. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  681. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  682. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  683. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  684. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  685. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  686. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  687. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  688. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  689. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  690. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  691. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  692. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  693. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  694. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  695. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  696. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  697. [encoder setBytes:&m0 length:sizeof( float) atIndex:18];
  698. const int nth = 32;
  699. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  700. } break;
  701. case GGML_OP_ROPE:
  702. {
  703. if (encoder == nil) {
  704. encoder = [command_buffer computeCommandEncoder];
  705. }
  706. const int n_dims = ((int32_t *) src1->data)[1];
  707. const int mode = ((int32_t *) src1->data)[2];
  708. const int n_past = ((int32_t *)(src1->data))[0];
  709. [encoder setComputePipelineState:ctx->pipeline_rope];
  710. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  711. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  712. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  713. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  714. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  715. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  716. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  717. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  718. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  719. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  720. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  721. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  722. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  723. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  724. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  725. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  726. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  727. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  728. [encoder setBytes:&n_past length:sizeof( int) atIndex:18];
  729. [encoder setBytes:&n_dims length:sizeof( int) atIndex:19];
  730. [encoder setBytes:&mode length:sizeof( int) atIndex:20];
  731. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  732. } break;
  733. case GGML_OP_CPY:
  734. {
  735. if (encoder == nil) {
  736. encoder = [command_buffer computeCommandEncoder];
  737. }
  738. const int nth = 32;
  739. switch (src0t) {
  740. case GGML_TYPE_F32:
  741. {
  742. switch (dstt) {
  743. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_cpy_f32_f16]; break;
  744. case GGML_TYPE_F32: [encoder setComputePipelineState:ctx->pipeline_cpy_f32_f32]; break;
  745. default: GGML_ASSERT(false && "not implemented");
  746. };
  747. } break;
  748. case GGML_TYPE_F16:
  749. {
  750. switch (dstt) {
  751. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_cpy_f16_f16]; break;
  752. case GGML_TYPE_F32: GGML_ASSERT(false && "cpy_f16_f32 not implemented"); break;
  753. default: GGML_ASSERT(false && "not implemented");
  754. };
  755. } break;
  756. default: GGML_ASSERT(false && "not implemented");
  757. }
  758. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  759. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  760. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  761. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  762. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  763. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  764. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  765. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  766. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  767. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  768. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  769. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  770. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  771. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  772. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  773. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  774. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  775. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  776. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  777. } break;
  778. default:
  779. fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
  780. GGML_ASSERT(false);
  781. }
  782. }
  783. if (encoder != nil) {
  784. [encoder endEncoding];
  785. encoder = nil;
  786. }
  787. [command_buffer commit];
  788. });
  789. }
  790. // wait for all threads to finish
  791. dispatch_barrier_sync(queue, ^{});
  792. [command_buffers[n_cb - 1] waitUntilCompleted];
  793. // check status of command buffers
  794. // needed to detect if the device ran out-of-memory for example (#1881)
  795. for (int i = 0; i < n_cb; i++) {
  796. MTLCommandBufferStatus status = (MTLCommandBufferStatus) [command_buffers[i] status];
  797. if (status != MTLCommandBufferStatusCompleted) {
  798. fprintf(stderr, "%s: command buffer %d failed with status %lu\n", __func__, i, status);
  799. GGML_ASSERT(false);
  800. }
  801. }
  802. }