ggml-metal.m 49 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. #ifdef GGML_QKK_64
  110. MTLCompileOptions* options = [MTLCompileOptions new];
  111. options.preprocessorMacros = @{ @"QK_K" : @(64) };
  112. ctx->library = [ctx->device newLibraryWithSource:src options:options error:&error];
  113. #else
  114. ctx->library = [ctx->device newLibraryWithSource:src options:nil error:&error];
  115. #endif
  116. if (error) {
  117. fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
  118. exit(1);
  119. }
  120. }
  121. #endif
  122. // load kernels
  123. {
  124. #define GGML_METAL_ADD_KERNEL(name) \
  125. ctx->function_##name = [ctx->library newFunctionWithName:@"kernel_"#name]; \
  126. ctx->pipeline_##name = [ctx->device newComputePipelineStateWithFunction:ctx->function_##name error:nil]; \
  127. fprintf(stderr, "%s: loaded %-32s %16p\n", __func__, "kernel_"#name, (void *) ctx->pipeline_##name);
  128. GGML_METAL_ADD_KERNEL(add);
  129. GGML_METAL_ADD_KERNEL(mul);
  130. GGML_METAL_ADD_KERNEL(mul_row);
  131. GGML_METAL_ADD_KERNEL(scale);
  132. GGML_METAL_ADD_KERNEL(silu);
  133. GGML_METAL_ADD_KERNEL(relu);
  134. GGML_METAL_ADD_KERNEL(gelu);
  135. GGML_METAL_ADD_KERNEL(soft_max);
  136. GGML_METAL_ADD_KERNEL(diag_mask_inf);
  137. GGML_METAL_ADD_KERNEL(get_rows_f16);
  138. GGML_METAL_ADD_KERNEL(get_rows_q4_0);
  139. GGML_METAL_ADD_KERNEL(get_rows_q4_1);
  140. GGML_METAL_ADD_KERNEL(get_rows_q2_K);
  141. GGML_METAL_ADD_KERNEL(get_rows_q3_K);
  142. GGML_METAL_ADD_KERNEL(get_rows_q4_K);
  143. GGML_METAL_ADD_KERNEL(get_rows_q5_K);
  144. GGML_METAL_ADD_KERNEL(get_rows_q6_K);
  145. GGML_METAL_ADD_KERNEL(rms_norm);
  146. GGML_METAL_ADD_KERNEL(norm);
  147. GGML_METAL_ADD_KERNEL(mul_mat_f16_f32);
  148. GGML_METAL_ADD_KERNEL(mul_mat_q4_0_f32);
  149. GGML_METAL_ADD_KERNEL(mul_mat_q4_1_f32);
  150. GGML_METAL_ADD_KERNEL(mul_mat_q2_K_f32);
  151. GGML_METAL_ADD_KERNEL(mul_mat_q3_K_f32);
  152. GGML_METAL_ADD_KERNEL(mul_mat_q4_K_f32);
  153. GGML_METAL_ADD_KERNEL(mul_mat_q5_K_f32);
  154. GGML_METAL_ADD_KERNEL(mul_mat_q6_K_f32);
  155. GGML_METAL_ADD_KERNEL(rope);
  156. GGML_METAL_ADD_KERNEL(alibi_f32);
  157. GGML_METAL_ADD_KERNEL(cpy_f32_f16);
  158. GGML_METAL_ADD_KERNEL(cpy_f32_f32);
  159. GGML_METAL_ADD_KERNEL(cpy_f16_f16);
  160. #undef GGML_METAL_ADD_KERNEL
  161. }
  162. fprintf(stderr, "%s: recommendedMaxWorkingSetSize = %8.2f MB\n", __func__, ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
  163. fprintf(stderr, "%s: hasUnifiedMemory = %s\n", __func__, ctx->device.hasUnifiedMemory ? "true" : "false");
  164. if (ctx->device.maxTransferRate != 0) {
  165. fprintf(stderr, "%s: maxTransferRate = %8.2f MB/s\n", __func__, ctx->device.maxTransferRate / 1024.0 / 1024.0);
  166. } else {
  167. fprintf(stderr, "%s: maxTransferRate = built-in GPU\n", __func__);
  168. }
  169. return ctx;
  170. }
  171. void ggml_metal_free(struct ggml_metal_context * ctx) {
  172. fprintf(stderr, "%s: deallocating\n", __func__);
  173. free(ctx);
  174. }
  175. // finds the Metal buffer that contains the tensor data on the GPU device
  176. // the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the
  177. // Metal buffer based on the host memory pointer
  178. //
  179. static id<MTLBuffer> ggml_metal_get_buffer(struct ggml_metal_context * ctx, struct ggml_tensor * t, size_t * offs) {
  180. //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);
  181. const int64_t tsize = ggml_nbytes(t);
  182. // find the view that contains the tensor fully
  183. for (int i = 0; i < ctx->n_buffers; ++i) {
  184. const int64_t ioffs = (int64_t) t->data - (int64_t) ctx->buffers[i].data;
  185. if (ioffs >= 0 && ioffs + tsize <= (int64_t) ctx->buffers[i].size) {
  186. *offs = (size_t) ioffs;
  187. //fprintf(stderr, "%s: '%s' tensor '%16s', offs = %8ld\n", __func__, ctx->buffers[i].name, t->name, *offs);
  188. return ctx->buffers[i].metal;
  189. }
  190. }
  191. fprintf(stderr, "%s: error: buffer is nil\n", __func__);
  192. return nil;
  193. }
  194. bool ggml_metal_add_buffer(
  195. struct ggml_metal_context * ctx,
  196. const char * name,
  197. void * data,
  198. size_t size,
  199. size_t max_size) {
  200. if (ctx->n_buffers >= GGML_METAL_MAX_BUFFERS) {
  201. fprintf(stderr, "%s: too many buffers\n", __func__);
  202. return false;
  203. }
  204. if (data) {
  205. // verify that the buffer does not overlap with any of the existing buffers
  206. for (int i = 0; i < ctx->n_buffers; ++i) {
  207. const int64_t ioffs = (int64_t) data - (int64_t) ctx->buffers[i].data;
  208. if (ioffs >= 0 && ioffs < (int64_t) ctx->buffers[i].size) {
  209. fprintf(stderr, "%s: error: buffer '%s' overlaps with '%s'\n", __func__, name, ctx->buffers[i].name);
  210. return false;
  211. }
  212. }
  213. const size_t size_page = getpagesize();
  214. size_t size_aligned = size;
  215. if ((size_aligned % size_page) != 0) {
  216. size_aligned += (size_page - (size_aligned % size_page));
  217. }
  218. // the buffer fits into the max buffer size allowed by the device
  219. if (size_aligned <= ctx->device.maxBufferLength) {
  220. ctx->buffers[ctx->n_buffers].name = name;
  221. ctx->buffers[ctx->n_buffers].data = data;
  222. ctx->buffers[ctx->n_buffers].size = size;
  223. ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:data length:size_aligned options:MTLResourceStorageModeShared deallocator:nil];
  224. if (ctx->buffers[ctx->n_buffers].metal == nil) {
  225. fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_aligned / 1024.0 / 1024.0);
  226. return false;
  227. }
  228. fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB", __func__, name, size_aligned / 1024.0 / 1024.0);
  229. ++ctx->n_buffers;
  230. } else {
  231. // this overlap between the views will guarantee that the tensor with the maximum size will fully fit into
  232. // one of the views
  233. const size_t size_ovlp = ((max_size + size_page - 1) / size_page + 1) * size_page; // round-up 2 pages just in case
  234. const size_t size_step = ctx->device.maxBufferLength - size_ovlp;
  235. const size_t size_view = ctx->device.maxBufferLength;
  236. for (size_t i = 0; i < size; i += size_step) {
  237. const size_t size_step_aligned = (i + size_view <= size) ? size_view : (size_aligned - i);
  238. ctx->buffers[ctx->n_buffers].name = name;
  239. ctx->buffers[ctx->n_buffers].data = (void *) ((uint8_t *) data + i);
  240. ctx->buffers[ctx->n_buffers].size = size_step_aligned;
  241. ctx->buffers[ctx->n_buffers].metal = [ctx->device newBufferWithBytesNoCopy:(void *) ((uint8_t *) data + i) length:size_step_aligned options:MTLResourceStorageModeShared deallocator:nil];
  242. if (ctx->buffers[ctx->n_buffers].metal == nil) {
  243. fprintf(stderr, "%s: failed to allocate '%-16s' buffer, size = %8.2f MB\n", __func__, name, size_step_aligned / 1024.0 / 1024.0);
  244. return false;
  245. }
  246. fprintf(stderr, "%s: allocated '%-16s' buffer, size = %8.2f MB, offs = %12ld", __func__, name, size_step_aligned / 1024.0 / 1024.0, i);
  247. if (i + size_step < size) {
  248. fprintf(stderr, "\n");
  249. }
  250. ++ctx->n_buffers;
  251. }
  252. }
  253. fprintf(stderr, ", (%8.2f / %8.2f)",
  254. ctx->device.currentAllocatedSize / 1024.0 / 1024.0,
  255. ctx->device.recommendedMaxWorkingSetSize / 1024.0 / 1024.0);
  256. if (ctx->device.currentAllocatedSize > ctx->device.recommendedMaxWorkingSetSize) {
  257. fprintf(stderr, ", warning: current allocated size is greater than the recommended max working set size\n");
  258. } else {
  259. fprintf(stderr, "\n");
  260. }
  261. }
  262. return true;
  263. }
  264. void ggml_metal_set_tensor(
  265. struct ggml_metal_context * ctx,
  266. struct ggml_tensor * t) {
  267. metal_printf("%s: set input for tensor '%s'\n", __func__, t->name);
  268. size_t offs;
  269. id<MTLBuffer> id_dst = ggml_metal_get_buffer(ctx, t, &offs);
  270. memcpy((void *) ((uint8_t *) id_dst.contents + offs), t->data, ggml_nbytes(t));
  271. }
  272. void ggml_metal_get_tensor(
  273. struct ggml_metal_context * ctx,
  274. struct ggml_tensor * t) {
  275. metal_printf("%s: extract results for tensor '%s'\n", __func__, t->name);
  276. size_t offs;
  277. id<MTLBuffer> id_src = ggml_metal_get_buffer(ctx, t, &offs);
  278. memcpy(t->data, (void *) ((uint8_t *) id_src.contents + offs), ggml_nbytes(t));
  279. }
  280. void ggml_metal_graph_compute(
  281. struct ggml_metal_context * ctx,
  282. struct ggml_cgraph * gf) {
  283. metal_printf("%s: evaluating graph\n", __func__);
  284. // create multiple command buffers and enqueue them
  285. // then, we encode the graph into the command buffers in parallel
  286. const int n_cb = gf->n_threads;
  287. NSMutableArray * command_buffers = [NSMutableArray arrayWithCapacity:n_cb];
  288. for (int i = 0; i < n_cb; ++i) {
  289. command_buffers[i] = [ctx->queue commandBuffer];
  290. // enqueue the command buffers in order to specify their execution order
  291. [command_buffers[i] enqueue];
  292. }
  293. // TODO: is this the best way to start threads?
  294. dispatch_queue_t queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);
  295. for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) {
  296. const int n_nodes_per_cb = (gf->n_nodes + n_cb - 1) / n_cb;
  297. dispatch_async(queue, ^{
  298. size_t offs_src0 = 0;
  299. size_t offs_src1 = 0;
  300. size_t offs_dst = 0;
  301. id<MTLCommandBuffer> command_buffer = command_buffers[cb_idx];
  302. id<MTLComputeCommandEncoder> encoder = nil;
  303. const int node_start = (cb_idx + 0) * n_nodes_per_cb;
  304. const int node_end = (cb_idx == n_cb - 1) ? gf->n_nodes : (cb_idx + 1) * n_nodes_per_cb;
  305. for (int i = node_start; i < node_end; ++i) {
  306. metal_printf("%s: encoding node %3d, op = %8s\n", __func__, i, ggml_op_name(gf->nodes[i]->op));
  307. struct ggml_tensor * src0 = gf->nodes[i]->src0;
  308. struct ggml_tensor * src1 = gf->nodes[i]->src1;
  309. struct ggml_tensor * dst = gf->nodes[i];
  310. const int64_t ne00 = src0 ? src0->ne[0] : 0;
  311. const int64_t ne01 = src0 ? src0->ne[1] : 0;
  312. const int64_t ne02 = src0 ? src0->ne[2] : 0;
  313. const int64_t ne03 = src0 ? src0->ne[3] : 0;
  314. const uint64_t nb00 = src0 ? src0->nb[0] : 0;
  315. const uint64_t nb01 = src0 ? src0->nb[1] : 0;
  316. const uint64_t nb02 = src0 ? src0->nb[2] : 0;
  317. const uint64_t nb03 = src0 ? src0->nb[3] : 0;
  318. const int64_t ne10 = src1 ? src1->ne[0] : 0;
  319. const int64_t ne11 = src1 ? src1->ne[1] : 0;
  320. const int64_t ne12 = src1 ? src1->ne[2] : 0;
  321. const int64_t ne13 = src1 ? src1->ne[3] : 0; UNUSED(ne13);
  322. const uint64_t nb10 = src1 ? src1->nb[0] : 0;
  323. const uint64_t nb11 = src1 ? src1->nb[1] : 0;
  324. const uint64_t nb12 = src1 ? src1->nb[2] : 0;
  325. const uint64_t nb13 = src1 ? src1->nb[3] : 0; UNUSED(nb13);
  326. const int64_t ne0 = dst ? dst->ne[0] : 0;
  327. const int64_t ne1 = dst ? dst->ne[1] : 0;
  328. const int64_t ne2 = dst ? dst->ne[2] : 0;
  329. const int64_t ne3 = dst ? dst->ne[3] : 0;
  330. const uint64_t nb0 = dst ? dst->nb[0] : 0;
  331. const uint64_t nb1 = dst ? dst->nb[1] : 0;
  332. const uint64_t nb2 = dst ? dst->nb[2] : 0;
  333. const uint64_t nb3 = dst ? dst->nb[3] : 0;
  334. const enum ggml_type src0t = src0 ? src0->type : GGML_TYPE_COUNT;
  335. const enum ggml_type src1t = src1 ? src1->type : GGML_TYPE_COUNT;
  336. const enum ggml_type dstt = dst ? dst->type : GGML_TYPE_COUNT;
  337. id<MTLBuffer> id_src0 = src0 ? ggml_metal_get_buffer(ctx, src0, &offs_src0) : nil;
  338. id<MTLBuffer> id_src1 = src1 ? ggml_metal_get_buffer(ctx, src1, &offs_src1) : nil;
  339. id<MTLBuffer> id_dst = dst ? ggml_metal_get_buffer(ctx, dst, &offs_dst) : nil;
  340. //metal_printf("%s: op - %s\n", __func__, ggml_op_name(dst->op));
  341. //if (src0) {
  342. // metal_printf("%s: src0 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src0t), ne00, ne01, ne02,
  343. // ggml_is_contiguous(src0), src0->name);
  344. //}
  345. //if (src1) {
  346. // metal_printf("%s: src1 - %4s [%5lld, %5lld, %5lld], %d, %s\n", __func__, ggml_type_name(src1t), ne10, ne11, ne12,
  347. // ggml_is_contiguous(src1), src1->name);
  348. //}
  349. //if (dst) {
  350. // metal_printf("%s: dst - %4s [%5lld, %5lld, %5lld], 1, %s\n", __func__, ggml_type_name(dstt), ne0, ne1, ne2,
  351. // dst->name);
  352. //}
  353. switch (dst->op) {
  354. case GGML_OP_RESHAPE:
  355. case GGML_OP_VIEW:
  356. case GGML_OP_TRANSPOSE:
  357. case GGML_OP_PERMUTE:
  358. {
  359. // noop
  360. } break;
  361. case GGML_OP_ADD:
  362. {
  363. if (encoder == nil) {
  364. encoder = [command_buffer computeCommandEncoder];
  365. }
  366. [encoder setComputePipelineState:ctx->pipeline_add];
  367. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  368. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  369. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  370. const int64_t n = ggml_nelements(dst);
  371. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  372. } break;
  373. case GGML_OP_MUL:
  374. {
  375. if (encoder == nil) {
  376. encoder = [command_buffer computeCommandEncoder];
  377. }
  378. if (ggml_nelements(src1) == ne10) {
  379. // src1 is a row
  380. [encoder setComputePipelineState:ctx->pipeline_mul_row];
  381. } else {
  382. [encoder setComputePipelineState:ctx->pipeline_mul];
  383. }
  384. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  385. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  386. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  387. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
  388. const int64_t n = ggml_nelements(dst);
  389. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  390. } break;
  391. case GGML_OP_SCALE:
  392. {
  393. if (encoder == nil) {
  394. encoder = [command_buffer computeCommandEncoder];
  395. }
  396. const float scale = *(const float *) src1->data;
  397. [encoder setComputePipelineState:ctx->pipeline_scale];
  398. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  399. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  400. [encoder setBytes:&scale length:sizeof(scale) atIndex:2];
  401. const int64_t n = ggml_nelements(dst);
  402. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  403. } break;
  404. case GGML_OP_SILU:
  405. {
  406. if (encoder == nil) {
  407. encoder = [command_buffer computeCommandEncoder];
  408. }
  409. [encoder setComputePipelineState:ctx->pipeline_silu];
  410. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  411. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  412. const int64_t n = ggml_nelements(dst);
  413. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  414. } break;
  415. case GGML_OP_RELU:
  416. {
  417. if (encoder == nil) {
  418. encoder = [command_buffer computeCommandEncoder];
  419. }
  420. [encoder setComputePipelineState:ctx->pipeline_relu];
  421. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  422. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  423. const int64_t n = ggml_nelements(dst);
  424. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  425. } break;
  426. case GGML_OP_GELU:
  427. {
  428. if (encoder == nil) {
  429. encoder = [command_buffer computeCommandEncoder];
  430. }
  431. [encoder setComputePipelineState:ctx->pipeline_gelu];
  432. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  433. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  434. const int64_t n = ggml_nelements(dst);
  435. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  436. } break;
  437. case GGML_OP_SOFT_MAX:
  438. {
  439. if (encoder == nil) {
  440. encoder = [command_buffer computeCommandEncoder];
  441. }
  442. const int nth = 32;
  443. [encoder setComputePipelineState:ctx->pipeline_soft_max];
  444. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  445. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  446. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
  447. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:3];
  448. [encoder setBytes:&ne02 length:sizeof(ne02) atIndex:4];
  449. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  450. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  451. } break;
  452. case GGML_OP_DIAG_MASK_INF:
  453. {
  454. if (encoder == nil) {
  455. encoder = [command_buffer computeCommandEncoder];
  456. }
  457. const int n_past = ((int32_t *)(src1->data))[0];
  458. [encoder setComputePipelineState:ctx->pipeline_diag_mask_inf];
  459. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  460. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  461. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:2];
  462. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:3];
  463. [encoder setBytes:&n_past length:sizeof(int) atIndex:4];
  464. [encoder dispatchThreadgroups:MTLSizeMake(ne00, ne01, ne02) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  465. } break;
  466. case GGML_OP_MUL_MAT:
  467. {
  468. // TODO: needs to be updated after PR: https://github.com/ggerganov/ggml/pull/224
  469. GGML_ASSERT(ne00 == ne10);
  470. GGML_ASSERT(ne02 == ne12);
  471. if (ggml_is_contiguous(src0) &&
  472. ggml_is_contiguous(src1) &&
  473. (src0t == GGML_TYPE_F32 || src0t == GGML_TYPE_F16) && ne11 > 1) {
  474. if (encoder != nil) {
  475. [encoder endEncoding];
  476. encoder = nil;
  477. }
  478. MPSDataType src0dt = src0t == GGML_TYPE_F32 ? MPSDataTypeFloat32 : MPSDataTypeFloat16;
  479. MPSDataType src1dt = src1t == GGML_TYPE_F32 ? MPSDataTypeFloat32 : MPSDataTypeFloat16;
  480. // for F32 x F32 we use MPS
  481. MPSMatrixDescriptor * desc0 = [MPSMatrixDescriptor
  482. matrixDescriptorWithRows:ne01 columns:ne00 rowBytes:src0->nb[1] dataType:src0dt];
  483. MPSMatrixDescriptor * desc1 = [MPSMatrixDescriptor
  484. matrixDescriptorWithRows:ne11 columns:ne10 rowBytes:src1->nb[1] dataType:src1dt];
  485. MPSMatrixDescriptor * desc = [MPSMatrixDescriptor
  486. matrixDescriptorWithRows:ne1 columns:ne0 rowBytes:dst->nb[1] dataType:MPSDataTypeFloat32];
  487. MPSMatrixMultiplication * mul = [[MPSMatrixMultiplication alloc]
  488. initWithDevice:ctx->device transposeLeft:false transposeRight:true
  489. resultRows:ne11 resultColumns:ne01 interiorColumns:ne00 alpha:1.0 beta:0.0];
  490. // we need to do ne02 multiplications
  491. // TODO: is there a way to do this in parallel - currently very slow ..
  492. // TODO: might be possible to offload part of the computation to ANE using Accelerate's CBLAS
  493. for (int64_t i02 = 0; i02 < ne02; ++i02) {
  494. size_t offs_src0_cur = offs_src0 + i02*nb02;
  495. size_t offs_src1_cur = offs_src1 + i02*nb12;
  496. size_t offs_dst_cur = offs_dst + i02*nb2;
  497. MPSMatrix * mat_src0 = [[MPSMatrix alloc] initWithBuffer:id_src0 offset:offs_src0_cur descriptor:desc0];
  498. MPSMatrix * mat_src1 = [[MPSMatrix alloc] initWithBuffer:id_src1 offset:offs_src1_cur descriptor:desc1];
  499. MPSMatrix * mat_dst = [[MPSMatrix alloc] initWithBuffer:id_dst offset:offs_dst_cur descriptor:desc ];
  500. [mul encodeToCommandBuffer:command_buffer leftMatrix:mat_src1 rightMatrix:mat_src0 resultMatrix:mat_dst];
  501. }
  502. } else {
  503. if (encoder == nil) {
  504. encoder = [command_buffer computeCommandEncoder];
  505. }
  506. int nth0 = 32;
  507. int nth1 = 1;
  508. // use custom matrix x vector kernel
  509. switch (src0t) {
  510. case GGML_TYPE_F16:
  511. {
  512. GGML_ASSERT(ne02 == ne12);
  513. nth0 = 64;
  514. nth1 = 1;
  515. [encoder setComputePipelineState:ctx->pipeline_mul_mat_f16_f32];
  516. } break;
  517. case GGML_TYPE_Q4_0:
  518. {
  519. GGML_ASSERT(ne02 == 1);
  520. GGML_ASSERT(ne12 == 1);
  521. nth0 = 8;
  522. nth1 = 8;
  523. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_0_f32];
  524. } break;
  525. case GGML_TYPE_Q4_1:
  526. {
  527. GGML_ASSERT(ne02 == 1);
  528. GGML_ASSERT(ne12 == 1);
  529. nth0 = 8;
  530. nth1 = 8;
  531. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_1_f32];
  532. } break;
  533. case GGML_TYPE_Q2_K:
  534. {
  535. GGML_ASSERT(ne02 == 1);
  536. GGML_ASSERT(ne12 == 1);
  537. nth0 = 4;
  538. nth1 = 16;
  539. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_K_f32];
  540. } break;
  541. case GGML_TYPE_Q3_K:
  542. {
  543. GGML_ASSERT(ne02 == 1);
  544. GGML_ASSERT(ne12 == 1);
  545. nth0 = 4;
  546. nth1 = 16;
  547. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q3_K_f32];
  548. } break;
  549. case GGML_TYPE_Q4_K:
  550. {
  551. GGML_ASSERT(ne02 == 1);
  552. GGML_ASSERT(ne12 == 1);
  553. nth0 = 4;
  554. nth1 = 16;
  555. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_K_f32];
  556. } break;
  557. case GGML_TYPE_Q5_K:
  558. {
  559. GGML_ASSERT(ne02 == 1);
  560. GGML_ASSERT(ne12 == 1);
  561. nth0 = 4;
  562. nth1 = 16;
  563. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q5_K_f32];
  564. } break;
  565. case GGML_TYPE_Q6_K:
  566. {
  567. GGML_ASSERT(ne02 == 1);
  568. GGML_ASSERT(ne12 == 1);
  569. nth0 = 4;
  570. nth1 = 16;
  571. [encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_K_f32];
  572. } break;
  573. default:
  574. {
  575. fprintf(stderr, "Asserting on type %d\n",(int)src0t);
  576. GGML_ASSERT(false && "not implemented");
  577. }
  578. };
  579. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  580. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  581. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  582. [encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
  583. [encoder setBytes:&ne01 length:sizeof(ne01) atIndex:4];
  584. [encoder setBytes:&nb00 length:sizeof(nb00) atIndex:5];
  585. [encoder setBytes:&nb01 length:sizeof(nb01) atIndex:6];
  586. [encoder setBytes:&nb02 length:sizeof(nb02) atIndex:7];
  587. [encoder setBytes:&ne10 length:sizeof(ne10) atIndex:8];
  588. [encoder setBytes:&ne11 length:sizeof(ne11) atIndex:9];
  589. [encoder setBytes:&nb10 length:sizeof(nb10) atIndex:10];
  590. [encoder setBytes:&nb11 length:sizeof(nb11) atIndex:11];
  591. [encoder setBytes:&nb12 length:sizeof(nb12) atIndex:12];
  592. [encoder setBytes:&ne0 length:sizeof(ne0) atIndex:13];
  593. [encoder setBytes:&ne1 length:sizeof(ne1) atIndex:14];
  594. if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1) {
  595. [encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
  596. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  597. }
  598. else if (src0t == GGML_TYPE_Q2_K ||
  599. src0t == GGML_TYPE_Q3_K ||
  600. src0t == GGML_TYPE_Q4_K ||
  601. src0t == GGML_TYPE_Q5_K ||
  602. src0t == GGML_TYPE_Q6_K) {
  603. [encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
  604. [encoder dispatchThreadgroups:MTLSizeMake(ne01, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  605. } else {
  606. [encoder setThreadgroupMemoryLength:nth0*sizeof(float) atIndex:0];
  607. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, ne12) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
  608. }
  609. }
  610. } break;
  611. case GGML_OP_GET_ROWS:
  612. {
  613. if (encoder == nil) {
  614. encoder = [command_buffer computeCommandEncoder];
  615. }
  616. switch (src0->type) {
  617. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_get_rows_f16]; break;
  618. case GGML_TYPE_Q4_0: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_0]; break;
  619. case GGML_TYPE_Q4_1: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_1]; break;
  620. case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_K]; break;
  621. case GGML_TYPE_Q3_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q3_K]; break;
  622. case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_K]; break;
  623. case GGML_TYPE_Q5_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q5_K]; break;
  624. case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_K]; break;
  625. default: GGML_ASSERT(false && "not implemented");
  626. }
  627. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  628. [encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
  629. [encoder setBuffer:id_dst offset:offs_dst atIndex:2];
  630. [encoder setBytes:&(src0->ne[0]) length:sizeof( int64_t) atIndex:3];
  631. [encoder setBytes:&(src0->nb[1]) length:sizeof(uint64_t) atIndex:4];
  632. [encoder setBytes:&(dst->nb[1]) length:sizeof(uint64_t) atIndex:5];
  633. const int64_t n = ggml_nelements(src1);
  634. [encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  635. } break;
  636. case GGML_OP_RMS_NORM:
  637. {
  638. if (encoder == nil) {
  639. encoder = [command_buffer computeCommandEncoder];
  640. }
  641. const float eps = 1e-6f;
  642. const int nth = 256;
  643. [encoder setComputePipelineState:ctx->pipeline_rms_norm];
  644. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  645. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  646. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  647. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3];
  648. [encoder setBytes:&eps length:sizeof( float) atIndex:4];
  649. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  650. const int64_t nrows = ggml_nrows(src0);
  651. [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  652. } break;
  653. case GGML_OP_NORM:
  654. {
  655. if (encoder == nil) {
  656. encoder = [command_buffer computeCommandEncoder];
  657. }
  658. const float eps = 1e-5f;
  659. const int nth = 256;
  660. [encoder setComputePipelineState:ctx->pipeline_norm];
  661. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  662. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  663. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  664. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3];
  665. [encoder setBytes:&eps length:sizeof( float) atIndex:4];
  666. [encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
  667. const int64_t nrows = ggml_nrows(src0);
  668. [encoder dispatchThreadgroups:MTLSizeMake(nrows, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  669. } break;
  670. case GGML_OP_ALIBI:
  671. {
  672. if (encoder == nil) {
  673. encoder = [command_buffer computeCommandEncoder];
  674. }
  675. GGML_ASSERT((src0t == GGML_TYPE_F32));
  676. const int n_past = ((int32_t *) src1->data)[0]; UNUSED(n_past);
  677. const int n_head = ((int32_t *) src1->data)[1];
  678. const float max_bias = ((float *) src1->data)[2];
  679. if (__builtin_popcount(n_head) != 1) {
  680. GGML_ASSERT(false && "only power-of-two n_head implemented");
  681. }
  682. const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
  683. const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor);
  684. [encoder setComputePipelineState:ctx->pipeline_alibi_f32];
  685. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  686. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  687. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  688. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  689. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  690. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  691. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  692. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  693. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  694. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  695. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  696. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  697. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  698. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  699. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  700. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  701. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  702. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  703. [encoder setBytes:&m0 length:sizeof( float) atIndex:18];
  704. const int nth = 32;
  705. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  706. } break;
  707. case GGML_OP_ROPE:
  708. {
  709. if (encoder == nil) {
  710. encoder = [command_buffer computeCommandEncoder];
  711. }
  712. const int n_dims = ((int32_t *) src1->data)[1];
  713. const int mode = ((int32_t *) src1->data)[2];
  714. const int n_past = ((int32_t *)(src1->data))[0];
  715. [encoder setComputePipelineState:ctx->pipeline_rope];
  716. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  717. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  718. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  719. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  720. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  721. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  722. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  723. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  724. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  725. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  726. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  727. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  728. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  729. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  730. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  731. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  732. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  733. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  734. [encoder setBytes:&n_past length:sizeof( int) atIndex:18];
  735. [encoder setBytes:&n_dims length:sizeof( int) atIndex:19];
  736. [encoder setBytes:&mode length:sizeof( int) atIndex:20];
  737. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
  738. } break;
  739. case GGML_OP_CPY:
  740. {
  741. if (encoder == nil) {
  742. encoder = [command_buffer computeCommandEncoder];
  743. }
  744. const int nth = 32;
  745. switch (src0t) {
  746. case GGML_TYPE_F32:
  747. {
  748. switch (dstt) {
  749. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_cpy_f32_f16]; break;
  750. case GGML_TYPE_F32: [encoder setComputePipelineState:ctx->pipeline_cpy_f32_f32]; break;
  751. default: GGML_ASSERT(false && "not implemented");
  752. };
  753. } break;
  754. case GGML_TYPE_F16:
  755. {
  756. switch (dstt) {
  757. case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_cpy_f16_f16]; break;
  758. case GGML_TYPE_F32: GGML_ASSERT(false && "cpy_f16_f32 not implemented"); break;
  759. default: GGML_ASSERT(false && "not implemented");
  760. };
  761. } break;
  762. default: GGML_ASSERT(false && "not implemented");
  763. }
  764. [encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
  765. [encoder setBuffer:id_dst offset:offs_dst atIndex:1];
  766. [encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
  767. [encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
  768. [encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
  769. [encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
  770. [encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
  771. [encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
  772. [encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
  773. [encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
  774. [encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
  775. [encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
  776. [encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
  777. [encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
  778. [encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
  779. [encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
  780. [encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
  781. [encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
  782. [encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
  783. } break;
  784. default:
  785. fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
  786. GGML_ASSERT(false);
  787. }
  788. }
  789. if (encoder != nil) {
  790. [encoder endEncoding];
  791. encoder = nil;
  792. }
  793. [command_buffer commit];
  794. });
  795. }
  796. // wait for all threads to finish
  797. dispatch_barrier_sync(queue, ^{});
  798. [command_buffers[n_cb - 1] waitUntilCompleted];
  799. // check status of command buffers
  800. // needed to detect if the device ran out-of-memory for example (#1881)
  801. for (int i = 0; i < n_cb; i++) {
  802. MTLCommandBufferStatus status = (MTLCommandBufferStatus) [command_buffers[i] status];
  803. if (status != MTLCommandBufferStatusCompleted) {
  804. fprintf(stderr, "%s: command buffer %d failed with status %lu\n", __func__, i, status);
  805. GGML_ASSERT(false);
  806. }
  807. }
  808. }