diff options
author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2024-07-27 07:55:01 +0200 |
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committer | GitHub <noreply@github.com> | 2024-07-27 07:55:01 +0200 |
commit | 154e0d75fccf1784fe9ff6fd76a630b66563da3d (patch) | |
tree | 81ce6dbb5b1900c1aa78a879f0593c694cab9d27 /ggml/src/ggml-alloc.c | |
parent | 0684c3e9c70d49323b4fc517128cbe222cab7f96 (diff) |
Merge mainline llama.cpp (#3)
* Merging mainline - WIP
* Merging mainline - WIP
AVX2 and CUDA appear to work.
CUDA performance seems slightly (~1-2%) lower as it is so often
the case with llama.cpp/ggml after some "improvements" have been made.
* Merging mainline - fix Metal
* Remove check
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'ggml/src/ggml-alloc.c')
-rw-r--r-- | ggml/src/ggml-alloc.c | 1042 |
1 files changed, 1042 insertions, 0 deletions
diff --git a/ggml/src/ggml-alloc.c b/ggml/src/ggml-alloc.c new file mode 100644 index 00000000..e176b883 --- /dev/null +++ b/ggml/src/ggml-alloc.c @@ -0,0 +1,1042 @@ +#include "ggml-alloc.h" +#include "ggml-backend-impl.h" +#include "ggml.h" +#include "ggml-impl.h" +#include <assert.h> +#include <limits.h> +#include <stdarg.h> +#include <stdio.h> +#include <stdlib.h> +#include <string.h> + +#define MAX(a, b) ((a) > (b) ? (a) : (b)) +#define MAX_FREE_BLOCKS 256 + +//#define GGML_ALLOCATOR_DEBUG + +//#define AT_PRINTF(...) fprintf(stderr, __VA_ARGS__) +#define AT_PRINTF(...) + + +static bool ggml_is_view(const struct ggml_tensor * t) { + return t->view_src != NULL; +} + +static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml_tensor * b) { + if (a->type != b->type) { + return false; + } + for (int i = 0; i < GGML_MAX_DIMS; i++) { + if (a->ne[i] != b->ne[i]) { + return false; + } + if (a->nb[i] != b->nb[i]) { + return false; + } + } + return true; +} + +static bool ggml_op_can_inplace(enum ggml_op op) { + switch (op) { + case GGML_OP_SCALE: + case GGML_OP_DIAG_MASK_ZERO: + case GGML_OP_DIAG_MASK_INF: + case GGML_OP_ADD: + case GGML_OP_ADD1: + case GGML_OP_SUB: + case GGML_OP_MUL: + case GGML_OP_DIV: + case GGML_OP_SQR: + case GGML_OP_SQRT: + case GGML_OP_LOG: + case GGML_OP_UNARY: + case GGML_OP_ROPE: + case GGML_OP_RMS_NORM: + case GGML_OP_SOFT_MAX: + return true; + + default: + return false; + } +} + +static size_t aligned_offset(const void * buffer, size_t offset, size_t alignment) { + assert(alignment && !(alignment & (alignment - 1))); // power of 2 + size_t align = (alignment - (((uintptr_t)buffer + offset) % alignment)) % alignment; + return offset + align; +} + +// tallocr + +struct ggml_tallocr ggml_tallocr_new(ggml_backend_buffer_t buffer) { + void * base = ggml_backend_buffer_get_base(buffer); + size_t align = ggml_backend_buffer_get_alignment(buffer); + + assert(align && !(align & (align - 1))); // power of 2 + + struct ggml_tallocr talloc = (struct ggml_tallocr) { + /*.buffer = */ buffer, + /*.base = */ base, + /*.alignment = */ align, + /*.offset = */ aligned_offset(base, 0, align), + }; + return talloc; +} + +void ggml_tallocr_alloc(struct ggml_tallocr * talloc, struct ggml_tensor * tensor) { + size_t size = ggml_backend_buffer_get_alloc_size(talloc->buffer, tensor); + size = GGML_PAD(size, talloc->alignment); + + if (talloc->offset + size > ggml_backend_buffer_get_size(talloc->buffer)) { + fprintf(stderr, "%s: not enough space in the buffer to allocate %s (needed %zu, available %zu)\n", + __func__, tensor->name, size, ggml_backend_buffer_get_size(talloc->buffer) - talloc->offset); + GGML_ASSERT(!"not enough space in the buffer"); + return; + } + + void * addr = (char *)ggml_backend_buffer_get_base(talloc->buffer) + talloc->offset; + talloc->offset += size; + + assert(((uintptr_t)addr % talloc->alignment) == 0); + + ggml_backend_tensor_alloc(talloc->buffer, tensor, addr); +} + +// dynamic tensor allocator + +struct free_block { + size_t offset; + size_t size; +}; + +struct ggml_dyn_tallocr { + size_t alignment; + int n_free_blocks; + struct free_block free_blocks[MAX_FREE_BLOCKS]; + size_t max_size; + +#ifdef GGML_ALLOCATOR_DEBUG + struct { + const struct ggml_tensor * tensor; + size_t offset; + } allocated_tensors[1024]; +#endif +}; + +#ifdef GGML_ALLOCATOR_DEBUG +static void add_allocated_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, const struct ggml_tensor * tensor) { + for (int i = 0; i < 1024; i++) { + if (alloc->allocated_tensors[i].tensor == NULL) { + alloc->allocated_tensors[i].tensor = tensor; + alloc->allocated_tensors[i].offset = offset; + return; + } + } + GGML_ASSERT(!"out of allocated_tensors"); +} +static void remove_allocated_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, const struct ggml_tensor * tensor) { + for (int i = 0; i < 1024; i++) { + if (alloc->allocated_tensors[i].offset == offset) { + alloc->allocated_tensors[i].tensor = NULL; + return; + } + } + fprintf(stderr, "tried to free tensor %s not found\n", tensor->name); + GGML_ASSERT(!"tensor not found"); +} +#endif + +static size_t ggml_dyn_tallocr_alloc(struct ggml_dyn_tallocr * alloc, size_t size, const struct ggml_tensor * tensor) { + size = aligned_offset(NULL, size, alloc->alignment); + + AT_PRINTF("%s: allocating %s (%zu bytes) - ", __func__, tensor->name, size); + + size_t max_avail = 0; + + // find the best fitting free block besides the last block + int best_fit_block = -1; + size_t best_fit_size = SIZE_MAX; + for (int i = 0; i < alloc->n_free_blocks - 1; i++) { + struct free_block * block = &alloc->free_blocks[i]; + max_avail = MAX(max_avail, block->size); + if (block->size >= size && block->size <= best_fit_size) { + best_fit_block = i; + best_fit_size = block->size; + } + } + + if (best_fit_block == -1) { + // the last block is our last resort + struct free_block * block = &alloc->free_blocks[alloc->n_free_blocks - 1]; + max_avail = MAX(max_avail, block->size); + if (block->size >= size) { + best_fit_block = alloc->n_free_blocks - 1; + } else { + // this should never happen + fprintf(stderr, "%s: not enough space in the buffer to allocate %zu bytes, largest block available %zu bytes\n", + __func__, size, max_avail); + GGML_ASSERT(!"not enough space in the buffer"); + GGML_UNREACHABLE(); + } + } + + struct free_block * block = &alloc->free_blocks[best_fit_block]; + size_t offset = block->offset; + block->offset = offset + size; + block->size -= size; + if (block->size == 0) { + // remove block if empty + alloc->n_free_blocks--; + for (int j = best_fit_block; j < alloc->n_free_blocks; j++) { + alloc->free_blocks[j] = alloc->free_blocks[j+1]; + } + } + + AT_PRINTF("block %d, offset %zu\n", best_fit_block, offset); + +#ifdef GGML_ALLOCATOR_DEBUG + add_allocated_tensor(alloc, offset, tensor); + size_t cur_max = offset + size; + if (cur_max > alloc->max_size) { + // sort allocated_tensors by offset + for (int i = 0; i < 1024; i++) { + for (int j = i + 1; j < 1024; j++) { + if (alloc->allocated_tensors[i].offset > alloc->allocated_tensors[j].offset) { + const struct ggml_tensor * tmp_tensor = alloc->allocated_tensors[i].tensor; + size_t tmp_offset = alloc->allocated_tensors[i].offset; + alloc->allocated_tensors[i].tensor = alloc->allocated_tensors[j].tensor; + alloc->allocated_tensors[i].offset = alloc->allocated_tensors[j].offset; + alloc->allocated_tensors[j].tensor = tmp_tensor; + alloc->allocated_tensors[j].offset = tmp_offset; + } + } + } + fprintf(stderr, "max_size = %.2f MB: tensors: ", cur_max / 1024.0 / 1024.0); + for (int i = 0; i < 1024; i++) { + if (alloc->allocated_tensors[i].tensor) { + fprintf(stderr, "%s [%zx-%zx] (%.2f MB) ", alloc->allocated_tensors[i].tensor->name, + alloc->allocated_tensors[i].offset, + alloc->allocated_tensors[i].offset + ggml_nbytes(alloc->allocated_tensors[i].tensor), + ggml_nbytes(alloc->allocated_tensors[i].tensor) / 1024.0 / 1024.0); + } + } + fprintf(stderr, "\n"); + } +#endif + + alloc->max_size = MAX(alloc->max_size, offset + size); + + return offset; + + GGML_UNUSED(tensor); +} + +// this is a very naive implementation, but for our case the number of free blocks should be very small +static void ggml_dyn_tallocr_free_tensor(struct ggml_dyn_tallocr * alloc, size_t offset, size_t size, const struct ggml_tensor * tensor) { + size = aligned_offset(NULL, size, alloc->alignment); + + AT_PRINTF("%s: freeing %s at %zu (%zu bytes) - n_free_blocks = %d\n", __func__, tensor->name, offset, size, alloc->n_free_blocks); + +#ifdef GGML_ALLOCATOR_DEBUG + remove_allocated_tensor(alloc, offset, tensor); +#endif + + // see if we can merge with an existing block + for (int i = 0; i < alloc->n_free_blocks; i++) { + struct free_block * block = &alloc->free_blocks[i]; + // check if ptr is at the end of the block + if (block->offset + block->size == offset) { + block->size += size; + // check if we can merge with the next block + if (i < alloc->n_free_blocks - 1 && block->offset + block->size == alloc->free_blocks[i+1].offset) { + block->size += alloc->free_blocks[i+1].size; + alloc->n_free_blocks--; + for (int j = i+1; j < alloc->n_free_blocks; j++) { + alloc->free_blocks[j] = alloc->free_blocks[j+1]; + } + } + return; + } + // check if ptr is at the beginning of the block + if (offset + size == block->offset) { + block->offset = offset; + block->size += size; + // check if we can merge with the previous block + if (i > 0 && alloc->free_blocks[i-1].offset + alloc->free_blocks[i-1].size == block->offset) { + alloc->free_blocks[i-1].size += block->size; + alloc->n_free_blocks--; + for (int j = i; j < alloc->n_free_blocks; j++) { + alloc->free_blocks[j] = alloc->free_blocks[j+1]; + } + } + return; + } + } + // otherwise, add a new block + GGML_ASSERT(alloc->n_free_blocks < MAX_FREE_BLOCKS && "out of free blocks"); + // insert the new block in the correct position to keep the array sorted by address (to make merging blocks faster) + int insert_pos = 0; + while (insert_pos < alloc->n_free_blocks && alloc->free_blocks[insert_pos].offset < offset) { + insert_pos++; + } + // shift all blocks from insert_pos onward to make room for the new block + for (int i = alloc->n_free_blocks; i > insert_pos; i--) { + alloc->free_blocks[i] = alloc->free_blocks[i-1]; + } + // insert the new block + alloc->free_blocks[insert_pos].offset = offset; + alloc->free_blocks[insert_pos].size = size; + alloc->n_free_blocks++; + + GGML_UNUSED(tensor); +} + +static void ggml_dyn_tallocr_reset(struct ggml_dyn_tallocr * alloc) { + alloc->n_free_blocks = 1; + alloc->free_blocks[0].offset = 0; + alloc->free_blocks[0].size = SIZE_MAX/2; // restrict maximum size of a measure allocator to half size_t max to avoid overflows + alloc->max_size = 0; +} + +static struct ggml_dyn_tallocr * ggml_dyn_tallocr_new(size_t alignment) { + struct ggml_dyn_tallocr * alloc = (struct ggml_dyn_tallocr *)malloc(sizeof(struct ggml_dyn_tallocr)); + + *alloc = (struct ggml_dyn_tallocr) { + /*.alignment = */ alignment, + /*.n_free_blocks = */ 0, + /*.free_blocks = */ {{0}}, + /*.max_size = */ 0, +#ifdef GGML_ALLOCATOR_DEBUG + /*.allocated_tensors = */ {{0}}, +#endif + }; + + ggml_dyn_tallocr_reset(alloc); + + return alloc; +} + +static void ggml_dyn_tallocr_free(struct ggml_dyn_tallocr * alloc) { + free(alloc); +} + +static size_t ggml_dyn_tallocr_max_size(struct ggml_dyn_tallocr * alloc) { + return alloc->max_size; +} + + +///////////////////////////////////// + +// graph allocator + +struct hash_node { + int n_children; + int n_views; + int buffer_id; + size_t offset; // offset within the buffer + bool allocated; +}; + +struct tensor_alloc { + int buffer_id; + size_t offset; + size_t size_max; // 0 = pre-allocated, unused, or view +}; + +struct leaf_alloc { + int buffer_id; + struct tensor_alloc leaf; +}; + +struct node_alloc { + struct tensor_alloc dst; + struct tensor_alloc src[GGML_MAX_SRC]; +}; + +struct ggml_gallocr { + ggml_backend_buffer_type_t * bufts; // [n_buffers] + ggml_backend_buffer_t * buffers; // [n_buffers] + struct ggml_dyn_tallocr ** buf_tallocs; // [n_buffers] + int n_buffers; + + struct ggml_hash_set hash_set; + struct hash_node * hash_values; // [hash_set.size] + + struct node_alloc * node_allocs; // [n_nodes] + int n_nodes; + + struct leaf_alloc * leaf_allocs; // [n_leafs] + int n_leafs; +}; + +ggml_gallocr_t ggml_gallocr_new_n(ggml_backend_buffer_type_t * bufts, int n_bufs) { + ggml_gallocr_t galloc = (ggml_gallocr_t)calloc(1, sizeof(struct ggml_gallocr)); + GGML_ASSERT(galloc != NULL); + + galloc->bufts = calloc(n_bufs, sizeof(ggml_backend_buffer_type_t)); + GGML_ASSERT(galloc->bufts != NULL); + + galloc->buffers = calloc(n_bufs, sizeof(ggml_backend_buffer_t)); + GGML_ASSERT(galloc->buffers != NULL); + + galloc->buf_tallocs = calloc(n_bufs, sizeof(struct ggml_dyn_tallocr *)); + GGML_ASSERT(galloc->buf_tallocs != NULL); + + for (int i = 0; i < n_bufs; i++) { + galloc->bufts[i] = bufts[i]; + galloc->buffers[i] = NULL; + + // check if the same buffer type is used multiple times and reuse the same allocator + for (int j = 0; j < i; j++) { + if (bufts[i] == bufts[j]) { + galloc->buf_tallocs[i] = galloc->buf_tallocs[j]; + break; + } + } + + if (galloc->buf_tallocs[i] == NULL) { + size_t alignment = ggml_backend_buft_get_alignment(bufts[i]); + galloc->buf_tallocs[i] = ggml_dyn_tallocr_new(alignment); + } + } + galloc->n_buffers = n_bufs; + + return galloc; +} + +ggml_gallocr_t ggml_gallocr_new(ggml_backend_buffer_type_t buft) { + return ggml_gallocr_new_n(&buft, 1); +} + +void ggml_gallocr_free(ggml_gallocr_t galloc) { + if (galloc == NULL) { + return; + } + + for (int i = 0; i < galloc->n_buffers; i++) { + if (galloc->buffers != NULL) { + // skip if already freed + bool freed = false; + for (int j = 0; j < i; j++) { + if (galloc->buffers[j] == galloc->buffers[i]) { + freed = true; + break; + } + } + if (!freed) { + ggml_backend_buffer_free(galloc->buffers[i]); + } + } + if (galloc->buf_tallocs != NULL) { + // skip if already freed + bool freed = false; + for (int j = 0; j < i; j++) { + if (galloc->buf_tallocs[j] == galloc->buf_tallocs[i]) { + freed = true; + break; + } + } + if (!freed) { + ggml_dyn_tallocr_free(galloc->buf_tallocs[i]); + } + } + } + + free(galloc->hash_set.keys); + free(galloc->hash_values); + free(galloc->bufts); + free(galloc->buffers); + free(galloc->buf_tallocs); + free(galloc->node_allocs); + free(galloc->leaf_allocs); + free(galloc); +} + +typedef struct ggml_gallocr * ggml_gallocr_t; + +static struct hash_node * ggml_gallocr_hash_get(ggml_gallocr_t galloc, struct ggml_tensor * t) { + size_t i = ggml_hash_find_or_insert(galloc->hash_set, t); + return &galloc->hash_values[i]; +} + +static bool ggml_gallocr_is_own(ggml_gallocr_t galloc, struct ggml_tensor * t) { + return ggml_gallocr_hash_get(galloc, t)->allocated; +} + +static void ggml_gallocr_set_node_offset(ggml_gallocr_t galloc, struct ggml_tensor * node, int buffer_id, size_t offset) { + struct hash_node * hn = ggml_gallocr_hash_get(galloc, node); + hn->buffer_id = buffer_id; + hn->offset = offset; + hn->allocated = true; +} + +static bool ggml_gallocr_is_allocated(ggml_gallocr_t galloc, struct ggml_tensor * t) { + return t->data != NULL || ggml_gallocr_hash_get(galloc, t)->allocated; +} + +static void ggml_gallocr_allocate_node(ggml_gallocr_t galloc, struct ggml_tensor * node, int buffer_id) { + struct hash_node * hn = ggml_gallocr_hash_get(galloc, node); + + if (!ggml_gallocr_is_allocated(galloc, node) && !ggml_is_view(node)) { + hn->allocated = true; + assert(hn->offset == 0); + + // try to reuse a parent's buffer (inplace) + if (ggml_op_can_inplace(node->op)) { + for (int i = 0; i < GGML_MAX_SRC; i++) { + struct ggml_tensor * parent = node->src[i]; + if (parent == NULL) { + continue; + } + + // if the node's data is external, then we cannot re-use it + if (!ggml_gallocr_is_own(galloc, parent)) { + AT_PRINTF("not reusing parent %s for %s as %p is external\n", parent->name, node->name, parent->data); + continue; + } + + // outputs cannot be reused + if (parent->flags & GGML_TENSOR_FLAG_OUTPUT || (parent->view_src != NULL && parent->view_src->flags & GGML_TENSOR_FLAG_OUTPUT)) { + AT_PRINTF("not reusing parent %s for %s as it is an output\n", parent->name, node->name); + continue; + } + + if (!ggml_are_same_layout(node, parent)) { + AT_PRINTF("not reusing parent %s for %s as layouts are different\n", parent->name, node->name); + continue; + } + + struct hash_node * p_hn = ggml_gallocr_hash_get(galloc, parent); + if (p_hn->n_children == 1 && p_hn->n_views == 0) { + if (ggml_is_view(parent)) { + struct ggml_tensor * view_src = parent->view_src; + struct hash_node * view_src_hn = ggml_gallocr_hash_get(galloc, view_src); + if (view_src_hn->n_views == 1 && view_src_hn->n_children == 0 && view_src->data == parent->data) { + AT_PRINTF("reusing view parent %s (%s) for %s\n", parent->name, view_src->name, node->name); + assert(view_src_hn->offset == p_hn->offset); + hn->buffer_id = p_hn->buffer_id; + hn->offset = p_hn->offset; + p_hn->allocated = false; // avoid freeing the parent + view_src_hn->allocated = false; + return; + } + } else { + AT_PRINTF("reusing parent %s for %s\n", parent->name, node->name); + hn->buffer_id = p_hn->buffer_id; + hn->offset = p_hn->offset; + p_hn->allocated = false; // avoid freeing the parent + return; + } + } + } + } + // allocate tensor from the buffer + struct ggml_dyn_tallocr * alloc = galloc->buf_tallocs[buffer_id]; + ggml_backend_buffer_type_t buft = galloc->bufts[buffer_id]; + size_t size = ggml_backend_buft_get_alloc_size(buft, node); + size_t offset = ggml_dyn_tallocr_alloc(alloc, size, node); + hn->buffer_id = buffer_id; + hn->offset = offset; + return; + } +} + +static void ggml_gallocr_free_node(ggml_gallocr_t galloc, struct ggml_tensor * node) { + // graph outputs are never freed + if (node->flags & GGML_TENSOR_FLAG_OUTPUT) { + AT_PRINTF("not freeing output %s\n", node->name); + return; + } + + struct hash_node * hn = ggml_gallocr_hash_get(galloc, node); + size_t offset = hn->offset; + int buffer_id = hn->buffer_id; + struct ggml_dyn_tallocr * alloc = galloc->buf_tallocs[buffer_id]; + ggml_backend_buffer_type_t buft = galloc->bufts[buffer_id]; + size_t size = ggml_backend_buft_get_alloc_size(buft, node); + ggml_dyn_tallocr_free_tensor(alloc, offset, size, node); + hn->allocated = false; +} + +static int get_node_buffer_id(const int * node_buffer_ids, int i) { + return node_buffer_ids ? node_buffer_ids[i] : 0; +} + +static void ggml_gallocr_alloc_graph_impl(ggml_gallocr_t galloc, struct ggml_cgraph * graph, const int * node_buffer_ids, const int * leaf_buffer_ids) { + // clear hash tables + memset(galloc->hash_set.keys, 0, galloc->hash_set.size * sizeof(struct ggml_tensor *)); + memset(galloc->hash_values, 0, galloc->hash_set.size * sizeof(struct hash_node)); + + // allocate leafs + // these may be tensors that the application is not using in the graph, but may still want to allocate for other purposes + for (int i = 0; i < graph->n_leafs; i++) { + struct ggml_tensor * leaf = graph->leafs[i]; + ggml_gallocr_allocate_node(galloc, leaf, get_node_buffer_id(leaf_buffer_ids, i)); + } + + // count number of children and views + // allocate other graph inputs and leafs first to avoid overwriting them + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + + // TODO: better way to add external dependencies + // GGML_OP_NONE does not appear normally in the graph nodes, but is used by ggml-backend to add dependencies to + // control when some tensors are allocated and freed. in this case, the dependencies are in `src`, but the node + // itself is never used and should not be considered a dependency + if (ggml_is_view(node) && node->op != GGML_OP_NONE) { + struct ggml_tensor * view_src = node->view_src; + ggml_gallocr_hash_get(galloc, view_src)->n_views += 1; + } + + if (node->flags & GGML_TENSOR_FLAG_INPUT) { + ggml_gallocr_allocate_node(galloc, graph->nodes[i], get_node_buffer_id(node_buffer_ids, i)); + } + + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (src == NULL) { + continue; + } + + ggml_gallocr_hash_get(galloc, src)->n_children += 1; + + // allocate explicit inputs + if (src->flags & GGML_TENSOR_FLAG_INPUT) { + ggml_gallocr_allocate_node(galloc, src, get_node_buffer_id(node_buffer_ids, i)); + } + } + } + + // allocate tensors + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + int buffer_id = get_node_buffer_id(node_buffer_ids, i); + + // allocate parents (only leafs need to be allocated at this point) + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * parent = node->src[j]; + if (parent == NULL) { + continue; + } + ggml_gallocr_allocate_node(galloc, parent, buffer_id); + } + + // allocate node + ggml_gallocr_allocate_node(galloc, node, buffer_id); + + AT_PRINTF("exec: %s (%s) <= ", ggml_op_desc(node), node->name); + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * parent = node->src[j]; + if (parent == NULL) { + continue; + } + AT_PRINTF("%s", parent->name); + if (j < GGML_MAX_SRC - 1 && node->src[j + 1] != NULL) { + AT_PRINTF(", "); + } + } + AT_PRINTF("\n"); + + // update parents + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * parent = node->src[j]; + if (parent == NULL) { + continue; + } + struct hash_node * p_hn = ggml_gallocr_hash_get(galloc, parent); + p_hn->n_children -= 1; + + AT_PRINTF("parent %s: %d children, %d views, allocated: %d\n", + parent->name, p_hn->n_children, p_hn->n_views, p_hn->allocated); + + if (p_hn->n_children == 0 && p_hn->n_views == 0) { + if (ggml_is_view(parent)) { + struct ggml_tensor * view_src = parent->view_src; + struct hash_node * view_src_hn = ggml_gallocr_hash_get(galloc, view_src); + view_src_hn->n_views -= 1; + AT_PRINTF("view_src %s: %d children, %d views\n", + view_src->name, view_src_hn->n_children, view_src_hn->n_views); + if (view_src_hn->n_views == 0 && view_src_hn->n_children == 0 && view_src_hn->allocated) { + ggml_gallocr_free_node(galloc, view_src); + } + } + else if (p_hn->allocated) { + ggml_gallocr_free_node(galloc, parent); + } + } + AT_PRINTF("\n"); + } + } +} + +bool ggml_gallocr_reserve_n(ggml_gallocr_t galloc, struct ggml_cgraph * graph, const int * node_buffer_ids, const int * leaf_buffer_ids) { + size_t hash_size = graph->visited_hash_table.size; + + // initialize hash table + if (galloc->hash_set.size < hash_size) { + free(galloc->hash_set.keys); + free(galloc->hash_values); + galloc->hash_set.size = hash_size; + galloc->hash_set.keys = calloc(hash_size, sizeof(struct ggml_tensor *)); + galloc->hash_values = calloc(hash_size, sizeof(struct hash_node)); + GGML_ASSERT(galloc->hash_set.keys != NULL); + GGML_ASSERT(galloc->hash_values != NULL); + } else { + // reset hash table + memset(galloc->hash_set.keys, 0, sizeof(struct ggml_tensor *) * galloc->hash_set.size); + memset(galloc->hash_values, 0, sizeof(struct hash_node) * galloc->hash_set.size); + } + + // reset allocators + for (int i = 0; i < galloc->n_buffers; i++) { + ggml_dyn_tallocr_reset(galloc->buf_tallocs[i]); + } + + // allocate in hash table + ggml_gallocr_alloc_graph_impl(galloc, graph, node_buffer_ids, leaf_buffer_ids); + + // set the node_allocs from the hash table + if (galloc->n_nodes < graph->n_nodes) { + free(galloc->node_allocs); + galloc->node_allocs = calloc(graph->n_nodes, sizeof(struct node_alloc)); + GGML_ASSERT(galloc->node_allocs != NULL); + } + galloc->n_nodes = graph->n_nodes; + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + struct node_alloc * node_alloc = &galloc->node_allocs[i]; + if (node->view_src || node->data) { + node_alloc->dst.buffer_id = -1; + node_alloc->dst.offset = SIZE_MAX; + node_alloc->dst.size_max = 0; + } else { + struct hash_node * hn = ggml_gallocr_hash_get(galloc, node); + node_alloc->dst.buffer_id = hn->buffer_id; + node_alloc->dst.offset = hn->offset; + node_alloc->dst.size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], node); + } + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (!src || src->view_src || src->data) { + node_alloc->src[j].buffer_id = -1; + node_alloc->src[j].offset = SIZE_MAX; + node_alloc->src[j].size_max = 0; + } else { + struct hash_node * hn = ggml_gallocr_hash_get(galloc, src); + node_alloc->src[j].buffer_id = hn->buffer_id; + node_alloc->src[j].offset = hn->offset; + node_alloc->src[j].size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], src); + } + } + } + if (galloc->n_leafs < graph->n_leafs) { + free(galloc->leaf_allocs); + galloc->leaf_allocs = calloc(graph->n_leafs, sizeof(galloc->leaf_allocs[0])); + GGML_ASSERT(galloc->leaf_allocs != NULL); + } + galloc->n_leafs = graph->n_leafs; + for (int i = 0; i < graph->n_leafs; i++) { + struct ggml_tensor * leaf = graph->leafs[i]; + struct hash_node * hn = ggml_gallocr_hash_get(galloc, leaf); + galloc->leaf_allocs[i].buffer_id = hn->buffer_id; + if (leaf->view_src || leaf->data) { + galloc->leaf_allocs[i].leaf.buffer_id = -1; + galloc->leaf_allocs[i].leaf.offset = SIZE_MAX; + galloc->leaf_allocs[i].leaf.size_max = 0; + } else { + galloc->leaf_allocs[i].leaf.buffer_id = hn->buffer_id; + galloc->leaf_allocs[i].leaf.offset = hn->offset; + galloc->leaf_allocs[i].leaf.size_max = ggml_backend_buft_get_alloc_size(galloc->bufts[hn->buffer_id], leaf); + } + } + + // reallocate buffers if needed + for (int i = 0; i < galloc->n_buffers; i++) { + // if the buffer type is used multiple times, we reuse the same buffer + for (int j = 0; j < i; j++) { + if (galloc->buf_tallocs[j] == galloc->buf_tallocs[i]) { + galloc->buffers[i] = galloc->buffers[j]; + break; + } + } + + size_t cur_size = galloc->buffers[i] ? ggml_backend_buffer_get_size(galloc->buffers[i]) : 0; + size_t new_size = ggml_dyn_tallocr_max_size(galloc->buf_tallocs[i]); + + // even if there are no tensors allocated in this buffer, we still need to allocate it to initialize views + if (new_size > cur_size || galloc->buffers[i] == NULL) { +#ifndef NDEBUG + fprintf(stderr, "%s: reallocating %s buffer from size %.02f MiB to %.02f MiB\n", __func__, ggml_backend_buft_name(galloc->bufts[i]), cur_size / 1024.0 / 1024.0, new_size / 1024.0 / 1024.0); +#endif + + ggml_backend_buffer_free(galloc->buffers[i]); + galloc->buffers[i] = ggml_backend_buft_alloc_buffer(galloc->bufts[i], new_size); + if (galloc->buffers[i] == NULL) { + fprintf(stderr, "%s: failed to allocate %s buffer of size %zu\n", __func__, ggml_backend_buft_name(galloc->bufts[i]), new_size); + return false; + } + ggml_backend_buffer_set_usage(galloc->buffers[i], GGML_BACKEND_BUFFER_USAGE_COMPUTE); + } + } + + return true; +} + +bool ggml_gallocr_reserve(ggml_gallocr_t galloc, struct ggml_cgraph *graph) { + return ggml_gallocr_reserve_n(galloc, graph, NULL, NULL); +} + +static void ggml_gallocr_init_tensor(ggml_gallocr_t galloc, struct ggml_tensor * tensor, struct tensor_alloc * tensor_alloc) { + int buffer_id = tensor_alloc->buffer_id; + assert(tensor->data || tensor->view_src || ggml_backend_buffer_get_alloc_size(galloc->buffers[buffer_id], tensor) <= tensor_alloc->size_max); + + if (tensor->view_src != NULL) { + if (tensor->buffer == NULL) { + assert(tensor_alloc->offset == SIZE_MAX); + if (tensor->view_src->buffer == NULL) { + // this tensor was allocated without ggml-backend + return; + } + ggml_backend_view_init(tensor); + } + } else { + if (tensor->data == NULL) { + assert(tensor_alloc->offset != SIZE_MAX); + assert(ggml_backend_buffer_get_alloc_size(galloc->buffers[buffer_id], tensor) <= tensor_alloc->size_max); + void * base = ggml_backend_buffer_get_base(galloc->buffers[buffer_id]); + void * addr = (char *)base + tensor_alloc->offset; + ggml_backend_tensor_alloc(galloc->buffers[buffer_id], tensor, addr); + } else { + if (tensor->buffer == NULL) { + // this tensor was allocated without ggml-backend + return; + } + } + } +} + +static bool ggml_gallocr_node_needs_realloc(ggml_gallocr_t galloc, struct ggml_tensor * node, struct tensor_alloc * talloc) { + ggml_backend_buffer_type_t buft = talloc->buffer_id != -1 ? galloc->bufts[talloc->buffer_id] : NULL; + size_t node_size = (node->data || node->view_src) ? 0 : ggml_backend_buft_get_alloc_size(buft, node); + return talloc->size_max >= node_size; +} + +static bool ggml_gallocr_needs_realloc(ggml_gallocr_t galloc, struct ggml_cgraph * graph) { + if (galloc->n_nodes != graph->n_nodes) { +#ifndef NDEBUG + fprintf(stderr, "%s: graph has different number of nodes\n", __func__); +#endif + return true; + } + + if (galloc->n_leafs != graph->n_leafs) { +#ifndef NDEBUG + fprintf(stderr, "%s: graph has different number of leafs\n", __func__); +#endif + return true; + } + + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + struct node_alloc * node_alloc = &galloc->node_allocs[i]; + + if (!ggml_gallocr_node_needs_realloc(galloc, node, &node_alloc->dst)) { +#ifndef NDEBUG + fprintf(stderr, "%s: node %s is not valid\n", __func__, node->name); +#endif + return true; + } + + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (src == NULL) { + continue; + } + if (!ggml_gallocr_node_needs_realloc(galloc, src, &node_alloc->src[j])) { +#ifndef NDEBUG + fprintf(stderr, "%s: src %d (%s) of node %s is not valid\n", __func__, j, src->name, node->name); +#endif + return true; + } + } + } + + return false; +} + +bool ggml_gallocr_alloc_graph(ggml_gallocr_t galloc, struct ggml_cgraph * graph) { + if (ggml_gallocr_needs_realloc(galloc, graph)) { + if (galloc->n_buffers == 1) { +#ifndef NDEBUG + fprintf(stderr, "%s: reallocating buffers automatically\n", __func__); +#endif + if (!ggml_gallocr_reserve(galloc, graph)) { + return false; + } + } else { +#ifndef NDEBUG + fprintf(stderr, "%s: cannot reallocate multi buffer graph automatically, call reserve\n", __func__); +#endif + return false; + } + } + + // reset buffers + for (int i = 0; i < galloc->n_buffers; i++) { + if (galloc->buffers[i] != NULL) { + ggml_backend_buffer_reset(galloc->buffers[i]); + } + } + + // allocate the graph tensors from the previous assignments + // leafs + for (int i = 0; i < graph->n_leafs; i++) { + struct ggml_tensor * leaf = graph->leafs[i]; + struct leaf_alloc * leaf_alloc = &galloc->leaf_allocs[i]; + ggml_gallocr_init_tensor(galloc, leaf, &leaf_alloc->leaf); + } + // nodes + for (int i = 0; i < graph->n_nodes; i++) { + struct ggml_tensor * node = graph->nodes[i]; + struct node_alloc * node_alloc = &galloc->node_allocs[i]; + for (int j = 0; j < GGML_MAX_SRC; j++) { + struct ggml_tensor * src = node->src[j]; + if (src == NULL) { + continue; + } + ggml_gallocr_init_tensor(galloc, src, &node_alloc->src[j]); + } + ggml_gallocr_init_tensor(galloc, node, &node_alloc->dst); + } + + return true; +} + +size_t ggml_gallocr_get_buffer_size(ggml_gallocr_t galloc, int buffer_id) { + GGML_ASSERT(buffer_id >= 0 && buffer_id < galloc->n_buffers); + + if (galloc->buffers[buffer_id] == NULL) { + return 0; + } + + for (int i = 0; i < buffer_id; i++) { + if (galloc->buffers[i] == galloc->buffers[buffer_id]) { + // this buffer is the same as a previous one due to the same buffer type being used multiple times + // only return the buffer size the first time it appears to avoid double counting + return 0; + } + } + + return ggml_backend_buffer_get_size(galloc->buffers[buffer_id]); +} + +// utils + +static bool alloc_tensor_range(struct ggml_context * ctx, + struct ggml_tensor * first, struct ggml_tensor * last, + ggml_backend_buffer_type_t buft, size_t size, + ggml_backend_buffer_t ** buffers, size_t * n_buffers) { + ggml_backend_buffer_t buffer = ggml_backend_buft_alloc_buffer(buft, size); + if (buffer == NULL) { +#ifndef NDEBUG + fprintf(stderr, "%s: failed to allocate %s buffer of size %zu\n", __func__, ggml_backend_buft_name(buft), size); +#endif + for (size_t i = 0; i < *n_buffers; i++) { + ggml_backend_buffer_free((*buffers)[i]); + } + free(*buffers); + return false; + } + + struct ggml_tallocr tallocr = ggml_tallocr_new(buffer); + + for (struct ggml_tensor * t = first; t != last; t = ggml_get_next_tensor(ctx, t)) { + if (t->data == NULL) { + if (t->view_src == NULL) { + ggml_tallocr_alloc(&tallocr, t); + } else if (t->buffer == NULL) { + ggml_backend_view_init(t); + } + } else { + if (t->view_src != NULL && t->buffer == NULL) { + // view of a pre-allocated tensor + ggml_backend_view_init(t); + } + } + } + + *buffers = realloc(*buffers, sizeof(ggml_backend_buffer_t) * (*n_buffers + 1)); + (*buffers)[(*n_buffers)++] = buffer; + + return true; +} + +ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors_from_buft(struct ggml_context * ctx, ggml_backend_buffer_type_t buft) { + GGML_ASSERT(ggml_get_no_alloc(ctx) == true); + + size_t alignment = ggml_backend_buft_get_alignment(buft); + size_t max_size = ggml_backend_buft_get_max_size(buft); + + ggml_backend_buffer_t * buffers = NULL; + size_t n_buffers = 0; + + size_t cur_buf_size = 0; + struct ggml_tensor * first = ggml_get_first_tensor(ctx); + for (struct ggml_tensor * t = first; t != NULL; t = ggml_get_next_tensor(ctx, t)) { + size_t this_size = 0; + if (t->data == NULL && t->view_src == NULL) { + this_size = GGML_PAD(ggml_backend_buft_get_alloc_size(buft, t), alignment); + } + + if (this_size > max_size) { + fprintf(stderr, "%s: tensor %s is too large to fit in a %s buffer (tensor size: %zu, max buffer size: %zu)\n", + __func__, t->name, + ggml_backend_buft_name(buft), + this_size, max_size); + for (size_t i = 0; i < n_buffers; i++) { + ggml_backend_buffer_free(buffers[i]); + } + free(buffers); + return NULL; + } + + if ((cur_buf_size + this_size) > max_size) { + // allocate tensors in the current buffer + if (!alloc_tensor_range(ctx, first, t, buft, cur_buf_size, &buffers, &n_buffers)) { + return NULL; + } + first = t; + cur_buf_size = this_size; + } else { + cur_buf_size += this_size; + } + } + + // allocate remaining tensors + if (cur_buf_size > 0) { + if (!alloc_tensor_range(ctx, first, NULL, buft, cur_buf_size, &buffers, &n_buffers)) { + return NULL; + } + } + + if (n_buffers == 0) { +#ifndef NDEBUG + fprintf(stderr, "%s: all tensors in the context are already allocated\n", __func__); +#endif + return NULL; + } + + ggml_backend_buffer_t buffer; + if (n_buffers == 1) { + buffer = buffers[0]; + } else { + buffer = ggml_backend_multi_buffer_alloc_buffer(buffers, n_buffers); + } + free(buffers); + return buffer; +} + +ggml_backend_buffer_t ggml_backend_alloc_ctx_tensors(struct ggml_context * ctx, ggml_backend_t backend) { + return ggml_backend_alloc_ctx_tensors_from_buft(ctx, ggml_backend_get_default_buffer_type(backend)); +} |