diff options
Diffstat (limited to 'ggml.c')
-rw-r--r-- | ggml.c | 45 |
1 files changed, 42 insertions, 3 deletions
@@ -248,6 +248,8 @@ inline static void * ggml_aligned_malloc(size_t size) { #include "ggml-cuda.h" #elif defined(GGML_USE_CLBLAST) #include "ggml-opencl.h" +#elif defined(GGML_USE_VULKAN) +#include "ggml-vulkan.h" #elif defined(GGML_USE_SYCL) #include "ggml-sycl.h" #endif @@ -2295,6 +2297,8 @@ struct ggml_context * ggml_init(struct ggml_init_params params) { ggml_init_cublas(); #elif defined(GGML_USE_CLBLAST) ggml_cl_init(); +#elif defined(GGML_USE_VULKAN) + ggml_vk_init(); #elif defined(GGML_USE_SYCL) ggml_init_sycl(); #endif @@ -8019,7 +8023,7 @@ static void ggml_compute_forward_mul_f32( const int ith = params->ith; const int nth = params->nth; -#ifdef GGML_USE_CLBLAST +#if defined(GGML_USE_CLBLAST) if (src1->backend == GGML_BACKEND_GPU) { // TODO: OpenCL kernel support full broadcast GGML_ASSERT(ggml_can_repeat_rows(src1, src0)); @@ -14703,6 +14707,18 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm } GGML_ASSERT(tensor->src[0] == NULL || tensor->src[0]->backend == GGML_BACKEND_CPU); GGML_ASSERT(tensor->src[1] == NULL || tensor->src[1]->backend == GGML_BACKEND_CPU); +#elif defined(GGML_USE_VULKAN) + const bool skip_cpu = ggml_vk_compute_forward(params, tensor); +#ifdef GGML_VULKAN_CHECK_RESULTS + if (skip_cpu) { + ggml_vk_check_results_1(params, tensor); + } +#endif + if (skip_cpu) { + return; + } + GGML_ASSERT(tensor->src[0] == NULL || tensor->src[0]->backend == GGML_BACKEND_CPU); + GGML_ASSERT(tensor->src[1] == NULL || tensor->src[1]->backend == GGML_BACKEND_CPU); #endif // GGML_USE_CUBLAS #ifdef GGML_USE_SYCL @@ -17105,6 +17121,17 @@ int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan) { } } +#ifdef GGML_USE_VULKAN + for (int i = 0; i < cgraph->n_nodes; i++) { + ggml_vk_preallocate_buffers_graph(cgraph->nodes[i]); + } + ggml_vk_preallocate_buffers(); + + for (int i = 0; i < cgraph->n_nodes; i++) { + ggml_vk_build_graph(cgraph->nodes[i], i == cgraph->n_nodes - 1); + } +#endif + const int n_threads = cplan->n_threads; struct ggml_compute_state_shared state_shared = { @@ -17156,6 +17183,10 @@ int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan) { } } +#ifdef GGML_USE_VULKAN + ggml_vk_graph_cleanup(); +#endif + // performance stats (graph) { int64_t perf_cycles_cur = ggml_perf_cycles() - perf_start_cycles; @@ -20290,7 +20321,7 @@ int ggml_cpu_has_wasm_simd(void) { } int ggml_cpu_has_blas(void) { -#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_CLBLAST) || defined(GGML_USE_SYCL) +#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CUBLAS) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CLBLAST) || defined(GGML_USE_SYCL) return 1; #else return 0; @@ -20313,6 +20344,14 @@ int ggml_cpu_has_clblast(void) { #endif } +int ggml_cpu_has_vulkan(void) { +#if defined(GGML_USE_VULKAN) + return 1; +#else + return 0; +#endif +} + int ggml_cpu_has_sycl(void) { #if defined(GGML_USE_SYCL) return 1; @@ -20322,7 +20361,7 @@ int ggml_cpu_has_sycl(void) { } int ggml_cpu_has_gpublas(void) { - return ggml_cpu_has_cublas() || ggml_cpu_has_clblast() || ggml_cpu_has_sycl(); + return ggml_cpu_has_cublas() || ggml_cpu_has_clblast() || ggml_cpu_has_vulkan() || ggml_cpu_has_sycl(); } int ggml_cpu_has_sse3(void) { |