diff options
Diffstat (limited to 'ggml-backend.c')
| -rw-r--r-- | ggml-backend.c | 685 |
1 files changed, 456 insertions, 229 deletions
diff --git a/ggml-backend.c b/ggml-backend.c index 53e741cb..4c2d8b0b 100644 --- a/ggml-backend.c +++ b/ggml-backend.c @@ -15,6 +15,10 @@ // backend buffer type +const char * ggml_backend_buft_name(ggml_backend_buffer_type_t buft) { + return buft->iface.get_name(buft); +} + ggml_backend_buffer_t ggml_backend_buft_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { return buft->iface.alloc_buffer(buft, size); } @@ -58,11 +62,16 @@ ggml_backend_buffer_t ggml_backend_buffer_init( /* .buft = */ buft, /* .context = */ context, /* .size = */ size, + /* .usage = */ GGML_BACKEND_BUFFER_USAGE_ANY }; return buffer; } +const char * ggml_backend_buffer_name(ggml_backend_buffer_t buffer) { + return buffer->iface.get_name(buffer); +} + void ggml_backend_buffer_free(ggml_backend_buffer_t buffer) { if (buffer == NULL) { return; @@ -94,11 +103,11 @@ void ggml_backend_buffer_init_tensor(ggml_backend_buffer_t buffer, struct ggml_t } size_t ggml_backend_buffer_get_alignment (ggml_backend_buffer_t buffer) { - return ggml_backend_buft_get_alignment(ggml_backend_buffer_type(buffer)); + return ggml_backend_buft_get_alignment(ggml_backend_buffer_get_type(buffer)); } size_t ggml_backend_buffer_get_alloc_size(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) { - return ggml_backend_buft_get_alloc_size(ggml_backend_buffer_type(buffer), tensor); + return ggml_backend_buft_get_alloc_size(ggml_backend_buffer_get_type(buffer), tensor); } void ggml_backend_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { @@ -106,13 +115,31 @@ void ggml_backend_buffer_clear(ggml_backend_buffer_t buffer, uint8_t value) { } bool ggml_backend_buffer_is_host(ggml_backend_buffer_t buffer) { - return ggml_backend_buft_is_host(ggml_backend_buffer_type(buffer)); + return ggml_backend_buft_is_host(ggml_backend_buffer_get_type(buffer)); } -ggml_backend_buffer_type_t ggml_backend_buffer_type(ggml_backend_buffer_t buffer) { +void ggml_backend_buffer_set_usage(ggml_backend_buffer_t buffer, enum ggml_backend_buffer_usage usage) { + buffer->usage = usage; +} + +ggml_backend_buffer_type_t ggml_backend_buffer_get_type(ggml_backend_buffer_t buffer) { return buffer->buft; } +void ggml_backend_buffer_reset(ggml_backend_buffer_t buffer) { + if (buffer->iface.reset) { + buffer->iface.reset(buffer); + } +} + +bool ggml_backend_buffer_copy_tensor(const struct ggml_tensor * src, struct ggml_tensor * dst) { + ggml_backend_buffer_t dst_buf = dst->view_src ? dst->view_src->buffer : dst->buffer; + if (dst_buf->iface.cpy_tensor) { + return src->buffer->iface.cpy_tensor(dst_buf, src, dst); + } + return false; +} + // backend const char * ggml_backend_name(ggml_backend_t backend) { @@ -146,30 +173,42 @@ void ggml_backend_tensor_set_async(ggml_backend_t backend, struct ggml_tensor * GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds"); - backend->iface.set_tensor_async(backend, tensor, data, offset, size); + if (backend->iface.set_tensor_async == NULL) { + ggml_backend_tensor_set(tensor, data, offset, size); + } else { + backend->iface.set_tensor_async(backend, tensor, data, offset, size); + } } void ggml_backend_tensor_get_async(ggml_backend_t backend, const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor read out of bounds"); - backend->iface.get_tensor_async(backend, tensor, data, offset, size); + if (backend->iface.get_tensor_async == NULL) { + ggml_backend_tensor_get(tensor, data, offset, size); + } else { + backend->iface.get_tensor_async(backend, tensor, data, offset, size); + } } void ggml_backend_tensor_set(struct ggml_tensor * tensor, const void * data, size_t offset, size_t size) { + ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer; + GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); - GGML_ASSERT(tensor->buffer != NULL && "tensor buffer not set"); + GGML_ASSERT(buf != NULL && "tensor buffer not set"); GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor write out of bounds"); - tensor->buffer->iface.set_tensor(tensor->buffer, tensor, data, offset, size); + tensor->buffer->iface.set_tensor(buf, tensor, data, offset, size); } void ggml_backend_tensor_get(const struct ggml_tensor * tensor, void * data, size_t offset, size_t size) { + ggml_backend_buffer_t buf = tensor->view_src ? tensor->view_src->buffer : tensor->buffer; + GGML_ASSERT(tensor->data != NULL && "tensor not allocated"); GGML_ASSERT(tensor->buffer != NULL && "tensor buffer not set"); GGML_ASSERT(offset + size <= ggml_nbytes(tensor) && "tensor read out of bounds"); - tensor->buffer->iface.get_tensor(tensor->buffer, tensor, data, offset, size); + tensor->buffer->iface.get_tensor(buf, tensor, data, offset, size); } void ggml_backend_synchronize(ggml_backend_t backend) { @@ -190,19 +229,10 @@ void ggml_backend_graph_plan_free(ggml_backend_t backend, ggml_backend_graph_pla void ggml_backend_graph_plan_compute(ggml_backend_t backend, ggml_backend_graph_plan_t plan) { backend->iface.graph_plan_compute(backend, plan); - - // TODO: optional sync - ggml_backend_synchronize(backend); } bool ggml_backend_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) { - if (!backend->iface.graph_compute(backend, cgraph)) { - return false; - } - - // TODO: optional sync - ggml_backend_synchronize(backend); - return true; + return backend->iface.graph_compute(backend, cgraph); } bool ggml_backend_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) { @@ -227,28 +257,20 @@ static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml } void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst) { - //printf("src: %s ne: [%d %d %d %d] nb: [%d %d %d %d]\n", src->name, (int)src->ne[0], (int)src->ne[1], (int)src->ne[2], (int)src->ne[3], (int)src->nb[0], (int)src->nb[1], (int)src->nb[2], (int)src->nb[3]); - //printf("dst: %s ne: [%d %d %d %d] nb: [%d %d %d %d]\n", dst->name, (int)dst->ne[0], (int)dst->ne[1], (int)dst->ne[2], (int)dst->ne[3], (int)dst->nb[0], (int)dst->nb[1], (int)dst->nb[2], (int)dst->nb[3]); GGML_ASSERT(ggml_are_same_layout(src, dst) && "cannot copy tensors with different layouts"); - // fprintf(stderr, "cpy tensor %s from %s to %s (%lu bytes)\n", src->name, ggml_backend_name(src->backend), ggml_backend_name(dst->backend), ggml_nbytes(src)); - if (src == dst) { return; } - // TODO: allow backends to support copy to/from same backend - - if (dst->buffer->iface.cpy_tensor_from != NULL) { - dst->buffer->iface.cpy_tensor_from(dst->buffer, src, dst); - } else if (src->buffer->iface.cpy_tensor_to != NULL) { - src->buffer->iface.cpy_tensor_to(src->buffer, src, dst); - } else { - // shouldn't be hit when copying from/to CPU - #ifndef NDEBUG - fprintf(stderr, "ggml_backend_tensor_copy: neither cpy_tensor_from nor cpy_tensor_to " - "are implemented for %s and %s, falling back to get/set\n", src->name, dst->name); - #endif + if (ggml_backend_buffer_is_host(src->buffer)) { + ggml_backend_tensor_set(dst, src->data, 0, ggml_nbytes(src)); + } else if (ggml_backend_buffer_is_host(dst->buffer)) { + ggml_backend_tensor_get(src, dst->data, 0, ggml_nbytes(src)); + } else if (!ggml_backend_buffer_copy_tensor(src, dst)) { +#ifndef NDEBUG + fprintf(stderr, "%s: warning: slow copy from %s to %s\n", __func__, ggml_backend_buffer_name(src->buffer), ggml_backend_buffer_name(dst->buffer)); +#endif size_t nbytes = ggml_nbytes(src); void * data = malloc(nbytes); ggml_backend_tensor_get(src, data, 0, nbytes); @@ -257,6 +279,31 @@ void ggml_backend_tensor_copy(struct ggml_tensor * src, struct ggml_tensor * dst } } +void ggml_backend_tensor_copy_async(ggml_backend_t backend, struct ggml_tensor * src, struct ggml_tensor * dst) { + GGML_ASSERT(ggml_are_same_layout(src, dst) && "cannot copy tensors with different layouts"); + + if (src == dst) { + return; + } + + if (ggml_backend_buft_supports_backend(src->buffer->buft, backend) && ggml_backend_buft_supports_backend(dst->buffer->buft, backend)) { + if (backend->iface.cpy_tensor_async != NULL) { + if (backend->iface.cpy_tensor_async(backend, src, dst)) { + return; + } + } + } + + size_t nbytes = ggml_nbytes(src); + if (ggml_backend_buffer_is_host(src->buffer)) { + ggml_backend_tensor_set_async(backend, dst, src->data, 0, nbytes); + } + else { + ggml_backend_tensor_copy(src, dst); + } +} + + // backend registry #define GGML_MAX_BACKENDS_REG 16 @@ -392,6 +439,12 @@ ggml_backend_buffer_t ggml_backend_reg_alloc_buffer(size_t i, size_t size) { // backend CPU +static const char * ggml_backend_cpu_buffer_name(ggml_backend_buffer_t buffer) { + return "CPU"; + + GGML_UNUSED(buffer); +} + static void * ggml_backend_cpu_buffer_get_base(ggml_backend_buffer_t buffer) { return (void *)buffer->context; } @@ -412,14 +465,12 @@ static void ggml_backend_cpu_buffer_get_tensor(ggml_backend_buffer_t buffer, con GGML_UNUSED(buffer); } -static void ggml_backend_cpu_buffer_cpy_tensor_from(ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst) { - ggml_backend_tensor_get(src, dst->data, 0, ggml_nbytes(src)); - - GGML_UNUSED(buffer); -} - -static void ggml_backend_cpu_buffer_cpy_tensor_to(ggml_backend_buffer_t buffer, struct ggml_tensor * src, struct ggml_tensor * dst) { - ggml_backend_tensor_set(dst, src->data, 0, ggml_nbytes(src)); +static bool ggml_backend_cpu_buffer_cpy_tensor(ggml_backend_buffer_t buffer, const struct ggml_tensor * src, struct ggml_tensor * dst) { + if (ggml_backend_buffer_is_host(src->buffer)) { + memcpy(dst->data, src->data, ggml_nbytes(src)); + return true; + } + return false; GGML_UNUSED(buffer); } @@ -429,30 +480,38 @@ static void ggml_backend_cpu_buffer_clear(ggml_backend_buffer_t buffer, uint8_t } static struct ggml_backend_buffer_i cpu_backend_buffer_i = { + /* .get_name = */ ggml_backend_cpu_buffer_name, /* .free_buffer = */ ggml_backend_cpu_buffer_free_buffer, /* .get_base = */ ggml_backend_cpu_buffer_get_base, /* .init_tensor = */ NULL, // no initialization required /* .set_tensor = */ ggml_backend_cpu_buffer_set_tensor, /* .get_tensor = */ ggml_backend_cpu_buffer_get_tensor, - /* .cpy_tensor_from = */ ggml_backend_cpu_buffer_cpy_tensor_from, - /* .cpy_tensor_to = */ ggml_backend_cpu_buffer_cpy_tensor_to, + /* .cpy_tensor = */ ggml_backend_cpu_buffer_cpy_tensor, /* .clear = */ ggml_backend_cpu_buffer_clear, + /* .reset = */ NULL, }; // for buffers from ptr, free is not called static struct ggml_backend_buffer_i cpu_backend_buffer_i_from_ptr = { + /* .get_name = */ ggml_backend_cpu_buffer_name, /* .free_buffer = */ NULL, // ptr is not owned by the buffer, so it does not need to be freed /* .get_base = */ ggml_backend_cpu_buffer_get_base, /* .init_tensor = */ NULL, // no initialization required /* .set_tensor = */ ggml_backend_cpu_buffer_set_tensor, /* .get_tensor = */ ggml_backend_cpu_buffer_get_tensor, - /* .cpy_tensor_from = */ ggml_backend_cpu_buffer_cpy_tensor_from, - /* .cpy_tensor_to = */ ggml_backend_cpu_buffer_cpy_tensor_to, + /* .cpy_tensor = */ ggml_backend_cpu_buffer_cpy_tensor, /* .clear = */ ggml_backend_cpu_buffer_clear, + /* .reset = */ NULL, }; static const size_t TENSOR_ALIGNMENT = 64; // should be enough for AVX 512 +static const char * ggml_backend_cpu_buffer_type_get_name(ggml_backend_buffer_type_t buft) { + return "CPU"; + + GGML_UNUSED(buft); +} + static ggml_backend_buffer_t ggml_backend_cpu_buffer_type_alloc_buffer(ggml_backend_buffer_type_t buft, size_t size) { size += TENSOR_ALIGNMENT; // malloc may return an address that is not aligned void * data = malloc(size); // TODO: maybe use GGML_ALIGNED_MALLOC? @@ -483,6 +542,7 @@ static bool ggml_backend_cpu_buffer_type_is_host(ggml_backend_buffer_type_t buft ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void) { static struct ggml_backend_buffer_type ggml_backend_cpu_buffer_type = { /* .iface = */ { + /* .get_name = */ ggml_backend_cpu_buffer_type_get_name, /* .alloc_buffer = */ ggml_backend_cpu_buffer_type_alloc_buffer, /* .get_alignment = */ ggml_backend_cpu_buffer_type_get_alignment, /* .get_alloc_size = */ NULL, // defaults to ggml_nbytes @@ -501,6 +561,18 @@ ggml_backend_buffer_type_t ggml_backend_cpu_buffer_type(void) { #include <hbwmalloc.h> +static const char * ggml_backend_cpu_hbm_buffer_type_get_name(ggml_backend_buffer_type_t buft) { + return "CPU_HBM"; + + GGML_UNUSED(buft); +} + +static const char * ggml_backend_cpu_hbm_buffer_get_name(ggml_backend_buffer_t buf) { + return "CPU_HBM"; + + GGML_UNUSED(buf); +} + static void ggml_backend_cpu_hbm_buffer_free_buffer(ggml_backend_buffer_t buffer) { hbw_free(buffer->context); } @@ -514,17 +586,18 @@ static ggml_backend_buffer_t ggml_backend_cpu_hbm_buffer_type_alloc_buffer(ggml_ return NULL; } - // FIXME: this is a hack to avoid having to implement a new buffer type ggml_backend_buffer_t buffer = ggml_backend_cpu_buffer_from_ptr(ptr, size); buffer->buft = buft; + buffer->iface.get_name = ggml_backend_cpu_hbm_buffer_get_name; buffer->iface.free_buffer = ggml_backend_cpu_hbm_buffer_free_buffer; return buffer; } -ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type() { +ggml_backend_buffer_type_t ggml_backend_cpu_hbm_buffer_type(void) { static struct ggml_backend_buffer_type ggml_backend_cpu_buffer_type_hbm = { /* .iface = */ { + /* .get_name = */ ggml_backend_cpu_hbm_buffer_type_get_name, /* .alloc_buffer = */ ggml_backend_cpu_hbm_buffer_type_alloc_buffer, /* .get_alignment = */ ggml_backend_cpu_buffer_type_get_alignment, /* .get_alloc_size = */ NULL, // defaults to ggml_nbytes @@ -568,7 +641,7 @@ struct ggml_backend_plan_cpu { struct ggml_cgraph cgraph; }; -static ggml_backend_graph_plan_t ggml_backend_cpu_graph_plan_create(ggml_backend_t backend, struct ggml_cgraph * cgraph) { +static ggml_backend_graph_plan_t ggml_backend_cpu_graph_plan_create(ggml_backend_t backend, const struct ggml_cgraph * cgraph) { struct ggml_backend_cpu_context * cpu_ctx = (struct ggml_backend_cpu_context *)backend->context; struct ggml_backend_plan_cpu * cpu_plan = malloc(sizeof(struct ggml_backend_plan_cpu)); @@ -634,8 +707,7 @@ static struct ggml_backend_i cpu_backend_i = { /* .get_default_buffer_type = */ ggml_backend_cpu_get_default_buffer_type, /* .set_tensor_async = */ NULL, /* .get_tensor_async = */ NULL, - /* .cpy_tensor_from_async = */ NULL, - /* .cpy_tensor_to_async = */ NULL, + /* .cpy_tensor_async = */ NULL, /* .synchronize = */ NULL, /* .graph_plan_create = */ ggml_backend_cpu_graph_plan_create, /* .graph_plan_free = */ ggml_backend_cpu_graph_plan_free, @@ -661,7 +733,7 @@ ggml_backend_t ggml_backend_cpu_init(void) { } bool ggml_backend_is_cpu(ggml_backend_t backend) { - return backend->iface.get_name == ggml_backend_cpu_name; + return backend && backend->iface.get_name == ggml_backend_cpu_name; } void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads) { @@ -685,7 +757,7 @@ static ggml_backend_t ggml_backend_reg_cpu_init(const char * params, void * user // scheduler -#define GGML_MAX_BACKENDS 4 +#define GGML_MAX_BACKENDS 16 #define GGML_MAX_SPLITS 256 #define GGML_MAX_SPLIT_INPUTS 16 @@ -695,21 +767,29 @@ struct ggml_backend_sched_split { int i_end; struct ggml_tensor * inputs[GGML_MAX_SPLIT_INPUTS]; int n_inputs; + // graph view of this split struct ggml_cgraph graph; }; struct ggml_backend_sched { + bool is_reset; // true if the scheduler has been reset since the last graph split + int n_backends; ggml_backend_t backends[GGML_MAX_BACKENDS]; + ggml_backend_buffer_type_t bufts[GGML_MAX_BACKENDS]; ggml_tallocr_t tallocs[GGML_MAX_BACKENDS]; ggml_gallocr_t galloc; + // hash keys of the nodes in the graph struct ggml_hash_set hash_set; - ggml_tallocr_t * node_talloc; // [hash_set.size] - struct ggml_tensor * (* node_copies)[GGML_MAX_BACKENDS]; // [hash_set.size][GGML_MAX_BACKENDS] + // hash values (arrays of [hash_set.size]) + ggml_tallocr_t * node_talloc; // tallocr assigned to each node (indirectly this is the backend) + struct ggml_tensor * (* node_copies)[GGML_MAX_BACKENDS]; // copies of each node for each destination backend + // copy of the graph with modified inputs struct ggml_cgraph * graph; + struct ggml_backend_sched_split splits[GGML_MAX_SPLITS]; int n_splits; @@ -750,14 +830,22 @@ static int sched_allocr_prio(ggml_backend_sched_t sched, ggml_tallocr_t allocr) return INT_MAX; } -static ggml_backend_t get_buffer_backend(ggml_backend_sched_t sched, ggml_backend_buffer_t buffer) { +static ggml_tallocr_t sched_allocr_from_buffer(ggml_backend_sched_t sched, ggml_backend_buffer_t buffer) { if (buffer == NULL) { return NULL; } + + // check if this is already allocate in a allocr buffer (from user manual allocations) + for (int i = 0; i < sched->n_backends; i++) { + if (ggml_tallocr_get_buffer(sched->tallocs[i]) == buffer) { + return sched->tallocs[i]; + } + } + // find highest prio backend that supports the buffer type for (int i = 0; i < sched->n_backends; i++) { if (ggml_backend_buft_supports_backend(buffer->buft, sched->backends[i])) { - return sched->backends[i]; + return sched->tallocs[i]; } } GGML_ASSERT(false && "tensor buffer type not supported by any backend"); @@ -767,7 +855,6 @@ static ggml_backend_t get_allocr_backend(ggml_backend_sched_t sched, ggml_talloc if (allocr == NULL) { return NULL; } - // find highest prio backend that supports the buffer type for (int i = 0; i < sched->n_backends; i++) { if (sched->tallocs[i] == allocr) { return sched->backends[i]; @@ -777,7 +864,7 @@ static ggml_backend_t get_allocr_backend(ggml_backend_sched_t sched, ggml_talloc } #if 0 -static char causes[GGML_DEFAULT_GRAPH_SIZE*8 + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS][128]; // debug, remove +static char causes[GGML_DEFAULT_GRAPH_SIZE*16 + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS][128]; // debug only #define SET_CAUSE(node, ...) sprintf(causes[hash_id(node)], __VA_ARGS__) #define GET_CAUSE(node) causes[hash_id(node)] #else @@ -786,45 +873,37 @@ static char causes[GGML_DEFAULT_GRAPH_SIZE*8 + GGML_MAX_SPLITS*GGML_MAX_SPLIT_IN #endif // returns the backend that should be used for the node based on the current locations -static ggml_backend_t sched_backend_from_cur(ggml_backend_sched_t sched, struct ggml_tensor * node) { - // if the dst tensor is already allocated in a buffer, we must assume that it is critical to keep it there - // ie. kv cache updates - // note that this doesn't allow fallback to CPU. need to add output tensors to the splits to copy the data back to the original backend. +static ggml_tallocr_t sched_allocr_from_cur(ggml_backend_sched_t sched, struct ggml_tensor * node) { + // assign pre-allocated nodes to their backend // dst - ggml_backend_t cur_backend = get_buffer_backend(sched, node->buffer); - if (cur_backend != NULL) { + ggml_tallocr_t cur_allocr = sched_allocr_from_buffer(sched, node->buffer); + if (cur_allocr != NULL) { SET_CAUSE(node, "1.dst"); - return cur_backend; + return cur_allocr; } - // view_src - if (node->view_src != NULL && get_buffer_backend(sched, node->view_src->buffer) != NULL) { - SET_CAUSE(node, "1.vsrc"); - return get_buffer_backend(sched, node->view_src->buffer); + if (node->view_src != NULL) { + cur_allocr = sched_allocr_from_buffer(sched, node->view_src->buffer); + if (cur_allocr != NULL) { + SET_CAUSE(node, "1.vsrc"); + return cur_allocr; + } } - - // src - int cur_prio = INT_MAX; - size_t cur_size = 0; - + // assign nodes that use weights to the backend of the weights for (int i = 0; i < GGML_MAX_SRC; i++) { const struct ggml_tensor * src = node->src[i]; if (src == NULL) { break; } - ggml_backend_t src_backend = get_buffer_backend(sched, src->buffer); - if (src_backend != NULL) { - int src_prio = sched_backend_prio(sched, src_backend); - size_t src_size = ggml_nbytes(src); - if (src_prio < cur_prio && src_size >= cur_size) { - cur_prio = src_prio; - cur_size = src_size; - cur_backend = src_backend; - SET_CAUSE(node, "1.src%d", i); - } + if (src->buffer != NULL && src->buffer->usage == GGML_BACKEND_BUFFER_USAGE_WEIGHTS) { + ggml_tallocr_t src_allocr = sched_allocr_from_buffer(sched, src->buffer); + // operations with weights are always run on the same backend as the weights + SET_CAUSE(node, "1.wgt%d", i); + return src_allocr; } } - return cur_backend; + + return NULL; } static char * fmt_size(size_t size) { @@ -857,7 +936,7 @@ static void sched_print_assignments(ggml_backend_sched_t sched, struct ggml_cgra } ggml_tallocr_t node_allocr = node_allocr(node); ggml_backend_t node_backend = node_allocr ? get_allocr_backend(sched, node_allocr) : NULL; // FIXME: - fprintf(stderr, "node #%3d (%10.10s): %20.20s (%4.4s) [%4.4s %8.8s]:", i, ggml_op_name(node->op), node->name, + fprintf(stderr, "node #%3d (%10.10s): %20.20s (%5.5s) [%5.5s %8.8s]:", i, ggml_op_name(node->op), node->name, fmt_size(ggml_nbytes(node)), node_allocr ? ggml_backend_name(node_backend) : "NULL", GET_CAUSE(node)); for (int j = 0; j < GGML_MAX_SRC; j++) { struct ggml_tensor * src = node->src[j]; @@ -866,7 +945,7 @@ static void sched_print_assignments(ggml_backend_sched_t sched, struct ggml_cgra } ggml_tallocr_t src_allocr = node_allocr(src); ggml_backend_t src_backend = src_allocr ? get_allocr_backend(sched, src_allocr) : NULL; - fprintf(stderr, " %20.20s (%4.4s) [%4.4s %8.8s]", src->name, + fprintf(stderr, " %20.20s (%5.5s) [%5.5s %8.8s]", src->name, fmt_size(ggml_nbytes(src)), src_backend ? ggml_backend_name(src_backend) : "NULL", GET_CAUSE(src)); } fprintf(stderr, "\n"); @@ -882,15 +961,17 @@ static struct ggml_tensor * ggml_dup_tensor_layout(struct ggml_context * ctx, co return dup; } + +//#define DEBUG_PASS1 +//#define DEBUG_PASS2 +//#define DEBUG_PASS3 +//#define DEBUG_PASS4 + // assigns backends to ops and splits the graph into subgraphs that can be computed on the same backend -// TODO: merge passes static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - // reset state - size_t hash_size = sched->hash_set.size; - memset(sched->hash_set.keys, 0, sizeof(sched->hash_set.keys[0]) * hash_size); - memset(sched->node_talloc, 0, sizeof(sched->node_talloc[0]) * hash_size); - memset(sched->node_copies, 0, sizeof(sched->node_copies[0]) * hash_size); + // reset splits sched->n_splits = 0; + sched->is_reset = false; struct ggml_init_params params = { /* .mem_size = */ sizeof(sched->context_buffer), @@ -898,26 +979,22 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g /* .no_alloc = */ true }; - if (sched->ctx != NULL) { - ggml_free(sched->ctx); - } + ggml_free(sched->ctx); sched->ctx = ggml_init(params); + if (sched->ctx == NULL) { + fprintf(stderr, "%s: failed to initialize context\n", __func__); + GGML_ASSERT(false); + } - // pass 1: assign backends to ops with allocated inputs + // pass 1: assign backends to ops with pre-allocated inputs for (int i = 0; i < graph->n_leafs; i++) { struct ggml_tensor * leaf = graph->leafs[i]; if (node_allocr(leaf) != NULL) { // do not overwrite user assignments continue; } - ggml_backend_t leaf_backend = get_buffer_backend(sched, leaf->buffer); - if (leaf_backend == NULL && leaf->view_src != NULL) { - leaf_backend = get_buffer_backend(sched, leaf->view_src->buffer); - } - if (leaf_backend != NULL) { - node_allocr(leaf) = ggml_backend_sched_get_tallocr(sched, leaf_backend); - } + node_allocr(leaf) = sched_allocr_from_cur(sched, leaf); } for (int i = 0; i < graph->n_nodes; i++) { @@ -926,50 +1003,102 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g // do not overwrite user assignments continue; } - ggml_backend_t node_backend = sched_backend_from_cur(sched, node); - if (node_backend != NULL) { - node_allocr(node) = ggml_backend_sched_get_tallocr(sched, node_backend); + node_allocr(node) = sched_allocr_from_cur(sched, node); + // src + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (src == NULL) { + break; + } + if (node_allocr(src) == NULL) { + node_allocr(src) = sched_allocr_from_cur(sched, src); + } } } - //printf("PASS 1 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#ifdef DEBUG_PASS1 + fprintf(stderr, "PASS 1 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#endif - // pass 2: assign backends to ops from current assignments - // TODO: - // - reuse sched_backend_from_cur - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - ggml_tallocr_t node_allocr = node_allocr(node); - if (node_allocr == NULL) { - int cur_prio = INT_MAX; - size_t cur_size = 0; - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - break; + // pass 2: expand current backend assignments + // assign the same backend to adjacent nodes + // expand gpu backends (i.e. non last prio) up and down, ignoring cpu (the lowest priority backend) + // thus, cpu will never be used unless weights are on cpu, or there are no gpu ops between cpu ops + + // pass 2.1 expand gpu up + { + ggml_tallocr_t cur_allocr = NULL; + for (int i = graph->n_nodes - 1; i >= 0; i--) { + struct ggml_tensor * node = graph->nodes[i]; + if (ggml_is_view_op(node->op)) { + continue; + } + ggml_tallocr_t node_allocr = node_allocr(node); + if (node_allocr != NULL) { + if (sched_allocr_prio(sched, node_allocr) == sched->n_backends - 1) { + // skip cpu (lowest prio backend) + cur_allocr = NULL; + } else { + cur_allocr = node_allocr; } - ggml_tallocr_t src_allocr = node_allocr(src); - if (src_allocr != NULL) { - int src_prio = sched_allocr_prio(sched, src_allocr); - size_t src_size = ggml_nbytes(src); - if (src_prio < cur_prio && src_size >= cur_size) { - cur_prio = src_prio; - cur_size = src_size; - node_allocr = src_allocr; - SET_CAUSE(node, "2.src%d", j); - } + } else { + node_allocr(node) = cur_allocr; + SET_CAUSE(node, "2.1"); + } + } + } + + // pass 2.2 expand gpu down + { + ggml_tallocr_t cur_allocr = NULL; + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + if (ggml_is_view_op(node->op)) { + continue; + } + ggml_tallocr_t node_allocr = node_allocr(node); + if (node_allocr != NULL) { + if (sched_allocr_prio(sched, node_allocr) == sched->n_backends - 1) { + // skip cpu (lowest prio backend) + cur_allocr = NULL; + } else { + cur_allocr = node_allocr; } + } else { + node_allocr(node) = cur_allocr; + SET_CAUSE(node, "2.2"); } + } + } + + // pass 2.3 expand rest up + { + ggml_tallocr_t cur_allocr = NULL; + for (int i = graph->n_nodes - 1; i >= 0; i--) { + struct ggml_tensor * node = graph->nodes[i]; + if (ggml_is_view_op(node->op)) { + continue; + } + ggml_tallocr_t node_allocr = node_allocr(node); if (node_allocr != NULL) { - node_allocr(node) = node_allocr; + cur_allocr = node_allocr; + } else { + node_allocr(node) = cur_allocr; + SET_CAUSE(node, "2.3"); } } } - //printf("PASS 2 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#ifdef DEBUG_PASS2 + fprintf(stderr, "PASS 2 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#endif - // pass 3: assign backends to remaining src from dst (should only be leafs) + // pass 3: assign backends to remaining src from dst and view_src for (int i = 0; i < graph->n_nodes; i++) { struct ggml_tensor * node = graph->nodes[i]; - ggml_tallocr_t node_allocr = node_allocr(node); + ggml_tallocr_t cur_allocr = node_allocr(node); + if (node->view_src != NULL && cur_allocr == NULL) { + cur_allocr = node_allocr(node) = node_allocr(node->view_src); + SET_CAUSE(node, "3.vsrc"); + } for (int j = 0; j < GGML_MAX_SRC; j++) { struct ggml_tensor * src = node->src[j]; if (src == NULL) { @@ -977,81 +1106,105 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g } ggml_tallocr_t src_allocr = node_allocr(src); if (src_allocr == NULL) { - node_allocr(src) = node_allocr; + if (src->view_src != NULL) { + // views are always on the same backend as the source + node_allocr(src) = node_allocr(src->view_src); + SET_CAUSE(src, "3.vsrc"); + } else { + node_allocr(src) = cur_allocr; + SET_CAUSE(src, "3.cur"); + } } } } - //printf("PASS 3 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#ifdef DEBUG_PASS3 + fprintf(stderr, "PASS 3 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#endif // pass 4: split graph, find tensors that need to be copied - // TODO: - // - when switching from a less preferred backend to a more preferred backend, check if it is possible to move the switch to an earlier point for the same cost - // find first backend - int cur_split = 0; - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; - if (node->view_src == NULL) { - sched->splits[0].tallocr = node_allocr(node); - break; + { + int cur_split = 0; + // find the backend of the first split, skipping view ops + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + if (!ggml_is_view_op(node->op)) { + sched->splits[0].tallocr = node_allocr(node); + break; + } } - } - sched->splits[0].i_start = 0; - sched->splits[0].n_inputs = 0; - memset(sched->splits[0].inputs, 0, sizeof(sched->splits[0].inputs)); //HACK - ggml_tallocr_t cur_allocr = sched->splits[0].tallocr; - size_t cur_backend_id = sched_allocr_prio(sched, cur_allocr); - for (int i = 0; i < graph->n_nodes; i++) { - struct ggml_tensor * node = graph->nodes[i]; + sched->splits[0].i_start = 0; + sched->splits[0].n_inputs = 0; + memset(sched->splits[0].inputs, 0, sizeof(sched->splits[0].inputs)); //HACK + ggml_tallocr_t cur_allocr = sched->splits[0].tallocr; + size_t cur_backend_id = sched_allocr_prio(sched, cur_allocr); + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + + if (ggml_is_view_op(node->op)) { + continue; + } - if (ggml_is_view_op(node->op)) { - continue; - } + ggml_tallocr_t node_allocr = node_allocr(node); + + if (node_allocr != cur_allocr) { + sched->splits[cur_split].i_end = i; + cur_split++; + GGML_ASSERT(cur_split < GGML_MAX_SPLITS); + sched->splits[cur_split].tallocr = node_allocr; + sched->splits[cur_split].i_start = i; + sched->splits[cur_split].n_inputs = 0; + cur_allocr = node_allocr; + cur_backend_id = sched_allocr_prio(sched, cur_allocr); + } - ggml_tallocr_t node_allocr = node_allocr(node); + // find inputs that are not on the same backend + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (src == NULL) { + break; + } + ggml_tallocr_t src_allocr = node_allocr(src); + GGML_ASSERT(src_allocr != NULL); // all inputs should be assigned by now + if (src_allocr != node_allocr) { + // check if the input is already in the split + bool found = false; + for (int k = 0; k < sched->splits[cur_split].n_inputs; k++) { + if (sched->splits[cur_split].inputs[k] == src) { + found = true; + break; + } + } - if (node_allocr != cur_allocr) { - sched->splits[cur_split].i_end = i; - cur_split++; - GGML_ASSERT(cur_split < GGML_MAX_SPLITS); - sched->splits[cur_split].tallocr = node_allocr; - sched->splits[cur_split].i_start = i; - sched->splits[cur_split].n_inputs = 0; - memset(sched->splits[cur_split].inputs, 0, sizeof(sched->splits[cur_split].inputs)); //HACK - cur_allocr = node_allocr; - cur_backend_id = sched_allocr_prio(sched, cur_allocr); - } + if (!found) { + int n_inputs = sched->splits[cur_split].n_inputs++; + //printf("split %d input %d: %s (%s)\n", cur_split, n_inputs, src->name, ggml_backend_name(get_allocr_backend(sched, src_allocr))); + GGML_ASSERT(n_inputs < GGML_MAX_SPLIT_INPUTS); + sched->splits[cur_split].inputs[n_inputs] = src; + } - // find inputs that are not on the same backend - for (int j = 0; j < GGML_MAX_SRC; j++) { - struct ggml_tensor * src = node->src[j]; - if (src == NULL) { - break; - } - ggml_tallocr_t src_allocr = node_allocr(src); - if (src_allocr != node_allocr) { - int n_inputs = sched->splits[cur_split].n_inputs++; - GGML_ASSERT(n_inputs < GGML_MAX_SPLIT_INPUTS); - sched->splits[cur_split].inputs[n_inputs] = (struct ggml_tensor *)src; - - // create copies - size_t id = hash_id(src); - if (sched->node_copies[id][cur_backend_id] == NULL) { - struct ggml_tensor * tensor_copy = ggml_dup_tensor_layout(sched->ctx, src); - sched->node_copies[id][cur_backend_id] = tensor_copy; - node_allocr(tensor_copy) = cur_allocr; - ggml_backend_t backend = get_allocr_backend(sched, cur_allocr); - ggml_format_name(tensor_copy, "%s#%s", ggml_backend_name(backend), src->name); + // create a copy of the input in the split's backend + size_t id = hash_id(src); + if (sched->node_copies[id][cur_backend_id] == NULL) { + ggml_backend_t backend = get_allocr_backend(sched, cur_allocr); + struct ggml_tensor * tensor_copy = ggml_dup_tensor_layout(sched->ctx, src); + ggml_format_name(tensor_copy, "%s#%s", ggml_backend_name(backend), src->name); + + sched->node_copies[id][cur_backend_id] = tensor_copy; + node_allocr(tensor_copy) = cur_allocr; + SET_CAUSE(tensor_copy, "4.cpy"); + } + node->src[j] = sched->node_copies[id][cur_backend_id]; } - node->src[j] = sched->node_copies[id][cur_backend_id]; } } + sched->splits[cur_split].i_end = graph->n_nodes; + sched->n_splits = cur_split + 1; } - sched->splits[cur_split].i_end = graph->n_nodes; - sched->n_splits = cur_split + 1; - - //fprintf(stderr, "PASS 4 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); fflush(stdout); +#ifdef DEBUG_PASS4 + fprintf(stderr, "PASS 4 ASSIGNMENTS\n"); sched_print_assignments(sched, graph); +#endif -#if 1 +#ifndef NDEBUG // sanity check: all sources should have the same backend as the node for (int i = 0; i < graph->n_nodes; i++) { struct ggml_tensor * node = graph->nodes[i]; @@ -1059,6 +1212,11 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g if (node_allocr == NULL) { fprintf(stderr, "!!!!!!! %s has no backend\n", node->name); } + if (node->view_src != NULL && node_allocr != node_allocr(node->view_src)) { + fprintf(stderr, "!!!!!!! %s has backend %s, view_src %s has backend %s\n", + node->name, node_allocr ? ggml_backend_name(get_allocr_backend(sched, node_allocr)) : "NULL", + node->view_src->name, node_allocr(node->view_src) ? ggml_backend_name(get_allocr_backend(sched, node_allocr(node->view_src))) : "NULL"); + } for (int j = 0; j < GGML_MAX_SRC; j++) { struct ggml_tensor * src = node->src[j]; if (src == NULL) { @@ -1070,8 +1228,14 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g node->name, node_allocr ? ggml_backend_name(get_allocr_backend(sched, node_allocr)) : "NULL", j, src->name, src_allocr ? ggml_backend_name(get_allocr_backend(sched, src_allocr)) : "NULL"); } + if (src->view_src != NULL && src_allocr != node_allocr(src->view_src)) { + fprintf(stderr, "!!!!!!! [src] %s has backend %s, view_src %s has backend %s\n", + src->name, src_allocr ? ggml_backend_name(get_allocr_backend(sched, src_allocr)) : "NULL", + src->view_src->name, node_allocr(src->view_src) ? ggml_backend_name(get_allocr_backend(sched, node_allocr(src->view_src))) : "NULL"); + } } } + fflush(stderr); #endif // create copies of the graph for each split @@ -1085,6 +1249,8 @@ static void sched_split_graph(ggml_backend_sched_t sched, struct ggml_cgraph * g for (int j = 0; j < split->n_inputs; j++) { struct ggml_tensor * input = split->inputs[j]; struct ggml_tensor * input_cpy = sched->node_copies[hash_id(input)][sched_allocr_prio(sched, split->tallocr)]; + // add a dependency to the input source so that it is not freed before the copy is done + GGML_ASSERT(input_cpy->src[0] == NULL || input_cpy->src[0] == input); input_cpy->src[0] = input; graph_copy->nodes[graph_copy->n_nodes++] = input_cpy; } @@ -1119,24 +1285,16 @@ static void sched_compute_splits(ggml_backend_sched_t sched) { uint64_t copy_start_us = ggml_time_us(); for (int j = 0; j < split->n_inputs; j++) { struct ggml_tensor * input = split->inputs[j]; - struct ggml_tensor * input_cpy = sched->node_copies[hash_id(input)][sched_backend_prio(sched, split_backend)]; - if (input->buffer == NULL) { - if (input->view_src == NULL) { - fprintf(stderr, "input %s has no buffer and no view_src\n", input->name); - exit(1); - } - // FIXME: may need to use the sched buffer instead - ggml_backend_view_init(input->view_src->buffer, input); - } - if (input_cpy->buffer == NULL) { - fprintf(stderr, "input_cpy %s has no buffer\n", input_cpy->name); - exit(1); - } - //GGML_ASSERT(input->buffer->backend != input_cpy->buffer->backend); - //GGML_ASSERT(input_cpy->buffer->backend == split_backend); - ggml_backend_tensor_copy(input, input_cpy); + struct ggml_tensor * input_cpy = sched->node_copies[hash_id(input)][split_backend_id]; + + GGML_ASSERT(input->buffer != NULL); + GGML_ASSERT(input_cpy->buffer != NULL); + + // TODO: avoid this copy if it was already copied in a previous split, and the input didn't change + // this is important to avoid copying constants such as KQ_mask and inp_pos multiple times + ggml_backend_tensor_copy_async(split_backend, input, input_cpy); } - // ggml_backend_synchronize(split_backend); + //ggml_backend_synchronize(split_backend); // necessary to measure copy time int64_t copy_end_us = ggml_time_us(); copy_us[split_backend_id] += copy_end_us - copy_start_us; @@ -1148,7 +1306,7 @@ static void sched_compute_splits(ggml_backend_sched_t sched) { uint64_t compute_start_us = ggml_time_us(); ggml_backend_graph_compute(split_backend, &split->graph); - // ggml_backend_synchronize(split_backend); + //ggml_backend_synchronize(split_backend); // necessary to measure compute time uint64_t compute_end_us = ggml_time_us(); compute_us[split_backend_id] += compute_end_us - compute_start_us; } @@ -1168,26 +1326,41 @@ static void sched_reset(ggml_backend_sched_t sched) { for (int i = 0; i < sched->n_backends; i++) { ggml_tallocr_reset(sched->tallocs[i]); } + // reset state for the next run + size_t hash_size = sched->hash_set.size; + memset(sched->hash_set.keys, 0, sizeof(sched->hash_set.keys[0]) * hash_size); + memset(sched->node_talloc, 0, sizeof(sched->node_talloc[0]) * hash_size); + memset(sched->node_copies, 0, sizeof(sched->node_copies[0]) * hash_size); + + sched->is_reset = true; } -ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, int n_backends) { +ggml_backend_sched_t ggml_backend_sched_new(ggml_backend_t * backends, ggml_backend_buffer_type_t * bufts, int n_backends, size_t graph_size) { + GGML_ASSERT(n_backends > 0); GGML_ASSERT(n_backends <= GGML_MAX_BACKENDS); - struct ggml_backend_sched * sched = malloc(sizeof(struct ggml_backend_sched)); - memset(sched, 0, sizeof(struct ggml_backend_sched)); + struct ggml_backend_sched * sched = calloc(sizeof(struct ggml_backend_sched), 1); + + // initialize hash table + sched->hash_set = ggml_hash_set_new(graph_size + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS); + sched->node_talloc = calloc(sizeof(sched->node_talloc[0]) * sched->hash_set.size, 1); + sched->node_copies = calloc(sizeof(sched->node_copies[0]) * sched->hash_set.size, 1); sched->n_backends = n_backends; for (int i = 0; i < n_backends; i++) { sched->backends[i] = backends[i]; + sched->bufts[i] = bufts ? bufts[i] : ggml_backend_get_default_buffer_type(backends[i]); } sched->galloc = ggml_gallocr_new(); // init measure allocs for each backend for (int i = 0; i < n_backends; i++) { - sched->tallocs[i] = ggml_tallocr_new_measure_from_backend(backends[i]); + sched->tallocs[i] = ggml_tallocr_new_measure_from_buft(sched->bufts[i]); } + sched_reset(sched); + return sched; } @@ -1199,6 +1372,7 @@ void ggml_backend_sched_free(ggml_backend_sched_t sched) { ggml_tallocr_free(sched->tallocs[i]); } ggml_gallocr_free(sched->galloc); + ggml_free(sched->ctx); free(sched->hash_set.keys); free(sched->node_talloc); free(sched->node_copies); @@ -1206,12 +1380,7 @@ void ggml_backend_sched_free(ggml_backend_sched_t sched) { } void ggml_backend_sched_init_measure(ggml_backend_sched_t sched, struct ggml_cgraph * measure_graph) { - // initialize hash tables - size_t hash_size = measure_graph->visited_hash_table.size + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS; - sched->hash_set.size = hash_size; - sched->hash_set.keys = malloc(sizeof(sched->hash_set.keys[0]) * hash_size); - sched->node_talloc = malloc(sizeof(sched->node_talloc[0]) * hash_size); - sched->node_copies = malloc(sizeof(sched->node_copies[0]) * hash_size); + GGML_ASSERT(ggml_tallocr_is_measure(sched->tallocs[0])); // can only be initialized once sched_split_graph(sched, measure_graph); sched_alloc_splits(sched); @@ -1220,28 +1389,41 @@ void ggml_backend_sched_init_measure(ggml_backend_sched_t sched, struct ggml_cgr for (int i = 0; i < sched->n_backends; i++) { size_t size = ggml_tallocr_max_size(sched->tallocs[i]); ggml_tallocr_free(sched->tallocs[i]); - sched->tallocs[i] = ggml_tallocr_new_from_backend(sched->backends[i], size); + sched->tallocs[i] = ggml_tallocr_new_from_buft(sched->bufts[i], size); } sched_reset(sched); } void ggml_backend_sched_graph_compute(ggml_backend_sched_t sched, struct ggml_cgraph * graph) { - GGML_ASSERT(sched->hash_set.size >= graph->visited_hash_table.size + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS); + GGML_ASSERT((int)sched->hash_set.size >= graph->n_nodes + GGML_MAX_SPLITS*GGML_MAX_SPLIT_INPUTS); + + if (!sched->is_reset) { + sched_reset(sched); + } sched_split_graph(sched, graph); sched_alloc_splits(sched); sched_compute_splits(sched); +} + +void ggml_backend_sched_reset(ggml_backend_sched_t sched) { sched_reset(sched); } +int ggml_backend_sched_get_n_splits(ggml_backend_sched_t sched) { + return sched->n_splits; +} + ggml_tallocr_t ggml_backend_sched_get_tallocr(ggml_backend_sched_t sched, ggml_backend_t backend) { int backend_index = sched_backend_prio(sched, backend); + GGML_ASSERT(backend_index >= 0 && backend_index < sched->n_backends); return sched->tallocs[backend_index]; } ggml_backend_buffer_t ggml_backend_sched_get_buffer(ggml_backend_sched_t sched, ggml_backend_t backend) { int backend_index = sched_backend_prio(sched, backend); + GGML_ASSERT(backend_index >= 0 && backend_index < sched->n_backends); return ggml_tallocr_get_buffer(sched->tallocs[backend_index]); } @@ -1251,10 +1433,19 @@ void ggml_backend_sched_set_node_backend(ggml_backend_sched_t sched, struct ggml node_allocr(node) = sched->tallocs[backend_index]; } +ggml_backend_t ggml_backend_sched_get_node_backend(ggml_backend_sched_t sched, struct ggml_tensor * node) { + ggml_tallocr_t allocr = node_allocr(node); + if (allocr == NULL) { + return NULL; + } + return get_allocr_backend(sched, allocr); +} + // utils + void ggml_backend_view_init(ggml_backend_buffer_t buffer, struct ggml_tensor * tensor) { GGML_ASSERT(tensor->buffer == NULL); - //GGML_ASSERT(tensor->data == NULL); // views of pre-allocted tensors may have the data set, but still need to be initialized + //GGML_ASSERT(tensor->data == NULL); // views of pre-allocated tensors may have the data set in ggml_new_tensor, but still need to be initialized by the backend GGML_ASSERT(tensor->view_src != NULL); GGML_ASSERT(tensor->view_src->buffer != NULL); GGML_ASSERT(tensor->view_src->data != NULL); @@ -1320,6 +1511,7 @@ static void graph_init_tensor(struct ggml_hash_set hash_set, struct ggml_tensor struct ggml_tensor * dst = node_copies[id]; if (dst->view_src != NULL) { + graph_init_tensor(hash_set, node_copies, node_init, src->view_src); ggml_backend_view_init(dst->view_src->buffer, dst); } else { @@ -1353,6 +1545,21 @@ struct ggml_backend_graph_copy ggml_backend_graph_copy(ggml_backend_t backend, s struct ggml_context * ctx_allocated = ggml_init(params); struct ggml_context * ctx_unallocated = ggml_init(params); + if (ctx_allocated == NULL || ctx_unallocated == NULL) { + fprintf(stderr, "failed to allocate context for graph copy\n"); + free(hash_set.keys); + free(node_copies); + free(node_init); + ggml_free(ctx_allocated); + ggml_free(ctx_unallocated); + return (struct ggml_backend_graph_copy) { + /* .buffer = */ NULL, + /* .ctx_allocated = */ NULL, + /* .ctx_unallocated = */ NULL, + /* .graph = */ NULL, + }; + } + // dup nodes for (int i = 0; i < graph->n_nodes; i++) { struct ggml_tensor * node = graph->nodes[i]; @@ -1361,6 +1568,20 @@ struct ggml_backend_graph_copy ggml_backend_graph_copy(ggml_backend_t backend, s // allocate nodes ggml_backend_buffer_t buffer = ggml_backend_alloc_ctx_tensors(ctx_allocated, backend); + if (buffer == NULL) { + fprintf(stderr, "failed to allocate buffer for graph copy\n"); + free(hash_set.keys); + free(node_copies); + free(node_init); + ggml_free(ctx_allocated); + ggml_free(ctx_unallocated); + return (struct ggml_backend_graph_copy) { + /* .buffer = */ NULL, + /* .ctx_allocated = */ NULL, + /* .ctx_unallocated = */ NULL, + /* .graph = */ NULL, + }; + } //printf("copy buffer size: %zu MB\n", ggml_backend_buffer_get_size(buffer) / 1024 / 1024); @@ -1397,8 +1618,12 @@ void ggml_backend_graph_copy_free(struct ggml_backend_graph_copy copy) { ggml_free(copy.ctx_unallocated); } -void ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t backend2, struct ggml_cgraph * graph, ggml_backend_eval_callback callback, void * user_data) { +bool ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t backend2, struct ggml_cgraph * graph, ggml_backend_eval_callback callback, void * user_data) { struct ggml_backend_graph_copy copy = ggml_backend_graph_copy(backend2, graph); + if (copy.buffer == NULL) { + return false; + } + struct ggml_cgraph * g1 = graph; struct ggml_cgraph * g2 = copy.graph; @@ -1428,4 +1653,6 @@ void ggml_backend_compare_graph_backend(ggml_backend_t backend1, ggml_backend_t } ggml_backend_graph_copy_free(copy); + + return true; } |