| // Copyright 2020 Google LLC |
| // |
| // This source code is licensed under the BSD-style license found in the |
| // LICENSE file in the root directory of this source tree. |
| |
| #include <assert.h> |
| #include <stdbool.h> |
| #include <stdint.h> |
| #include <stdlib.h> |
| |
| #include <xnnpack/memory-planner.h> |
| #include <xnnpack/subgraph.h> |
| |
| // Check if two xnn_value's lifecycles overlap. |
| inline static bool value_lifecycle_overlap(const struct xnn_value_usage* a, const struct xnn_value_usage* b) { |
| assert(a->last_node >= a->first_node); |
| assert(b->last_node >= b->first_node); |
| if (a->first_node < b->first_node) { |
| return a->last_node >= b->first_node; |
| } else { |
| return b->last_node >= a->first_node; |
| } |
| } |
| |
| // Use this comparison function to sort xnn_value_usage according to the |
| // tensor_size in decreasing order. |
| static inline int cmp_value_usage_tensor_size(const void* a, const void* b) { |
| const size_t tensor_size_a = (*(struct xnn_value_usage**)a)->tensor_size; |
| const size_t tensor_size_b = (*(struct xnn_value_usage**)b)->tensor_size; |
| return (tensor_size_b > tensor_size_a) - (tensor_size_b < tensor_size_a); |
| } |
| |
| static void populate_value_lifecycle(const xnn_subgraph_t subgraph, struct xnn_value_usage* usage) { |
| assert(subgraph != NULL); |
| if (subgraph->num_nodes == 0) { |
| return; |
| } |
| // As we initialized first/last_node in each xnn_value_usage to 0 as in 'xnn_init_value_mem_allocation_tracker', |
| // we start with the second node to tell whether first/last_node have been set or not, and check the first node last. |
| for (uint32_t nid = 1; nid < subgraph->num_nodes; ++nid) { |
| const struct xnn_node* node = subgraph->nodes + nid; |
| for (uint32_t i = 0; i < node->num_inputs; ++i) { |
| if (usage[node->inputs[i]].first_node == 0) { |
| usage[node->inputs[i]].first_node = nid; |
| } |
| usage[node->inputs[i]].last_node = nid; |
| } |
| for (uint32_t i = 0; i < node->num_outputs; ++i) { |
| if (usage[node->outputs[i]].first_node == 0) { |
| usage[node->outputs[i]].first_node = nid; |
| } |
| usage[node->outputs[i]].last_node = nid; |
| } |
| } |
| const struct xnn_node* first_node = subgraph->nodes; |
| for (uint32_t i = 0; i < first_node->num_inputs; ++i) { |
| usage[first_node->inputs[i]].first_node = 0; |
| } |
| for (uint32_t i = 0; i < first_node->num_outputs; ++i) { |
| usage[first_node->outputs[i]].first_node = 0; |
| } |
| } |
| |
| // Represent a memory block [start, end) |
| struct memory_block { |
| size_t start; |
| size_t end; |
| }; |
| |
| // Use this comparison function to sort memory_block according to the 'start' |
| // in increasing order. |
| static inline int cmp_memory_block(const void* a, const void* b) { |
| const size_t start_a = ((struct memory_block*)a)->start; |
| const size_t start_b = ((struct memory_block*)b)->start; |
| return (start_a > start_b) - (start_a < start_b); |
| } |
| |
| // Given the current live memory blocks, return the offset in a memory arena for a to-be-allocated value of size |
| // 'to_alloc_size'. |
| static size_t find_value_alloc_offset(struct memory_block* live_mem_blocks, |
| size_t num_mem_blocks, |
| size_t to_alloc_size) { |
| if (num_mem_blocks == 0) { |
| return 0; |
| } |
| |
| if (num_mem_blocks == 1) { |
| return live_mem_blocks[0].end; |
| } |
| |
| // Sort memory blocks according to 'start' in increasing order. |
| qsort(live_mem_blocks, num_mem_blocks, sizeof(struct memory_block), cmp_memory_block); |
| |
| // Coalesce overlapping or immediate adjacent memory blocks to form a list of non-overlapping memory blocks in order |
| // to find the smallest gap. |
| size_t num_coalesced_mem_blocks = 1; |
| for (size_t i = 1; i < num_mem_blocks; ++i) { |
| const size_t current_coalesced_end = |
| live_mem_blocks[num_coalesced_mem_blocks - 1].end; |
| if (live_mem_blocks[i].start > current_coalesced_end) { |
| assert(num_coalesced_mem_blocks <= i); |
| live_mem_blocks[num_coalesced_mem_blocks] = live_mem_blocks[i]; |
| num_coalesced_mem_blocks++; |
| continue; |
| } |
| if (live_mem_blocks[i].end > current_coalesced_end) { |
| live_mem_blocks[num_coalesced_mem_blocks - 1].end = live_mem_blocks[i].end; |
| } |
| } |
| |
| size_t smallest_gap_size = SIZE_MAX; |
| // The first index to live_mem_blocks that the 'to_alloc_size' should be allocated after. |
| size_t smallest_gap_index = num_coalesced_mem_blocks - 1; |
| for (size_t i = 0; i < num_coalesced_mem_blocks - 1; ++i) { |
| assert(live_mem_blocks[i + 1].start > live_mem_blocks[i].end); |
| const size_t gap = live_mem_blocks[i + 1].start - live_mem_blocks[i].end; |
| if (gap >= to_alloc_size && gap < smallest_gap_size) { |
| smallest_gap_index = i; |
| smallest_gap_size = gap; |
| } |
| } |
| return live_mem_blocks[smallest_gap_index].end; |
| } |
| |
| void xnn_init_value_allocation_tracker(struct xnn_value_allocation_tracker* tracker, const xnn_subgraph_t subgraph) { |
| tracker->subgraph = subgraph; |
| tracker->mem_arena_size = 0; |
| tracker->usage = xnn_allocate_zero_memory(sizeof(struct xnn_value_usage) * subgraph->num_values); |
| #if XNN_ENABLE_MEMOPT |
| populate_value_lifecycle(tracker->subgraph, tracker->usage); |
| #endif |
| tracker->min_value_id = XNN_INVALID_VALUE_ID; |
| tracker->max_value_id = XNN_INVALID_VALUE_ID; |
| } |
| |
| void xnn_add_value_allocation_tracker(struct xnn_value_allocation_tracker* tracker, |
| uint32_t value_id, |
| size_t tensor_size) { |
| tracker->usage[value_id].tensor_size = tensor_size; |
| if (tracker->min_value_id == XNN_INVALID_VALUE_ID) { |
| tracker->min_value_id = value_id; |
| } else { |
| // Note that values are expected to be added in increasing order. |
| assert(value_id > tracker->min_value_id); |
| assert(value_id > tracker->max_value_id); |
| } |
| |
| tracker->max_value_id = value_id; |
| } |
| |
| void xnn_plan_value_allocation_tracker(struct xnn_value_allocation_tracker* tracker) { |
| #if XNN_ENABLE_MEMOPT |
| if (tracker->min_value_id == XNN_INVALID_VALUE_ID) { |
| assert(tracker->max_value_id == XNN_INVALID_VALUE_ID); |
| return; |
| } |
| |
| const uint32_t num_values = tracker->max_value_id - tracker->min_value_id + 1; |
| struct xnn_value_usage** sorted_usage = xnn_allocate_zero_memory(sizeof(struct xnn_value_usage*) * num_values); |
| size_t num_values_to_alloc = 0; |
| for (size_t i = tracker->min_value_id; i <= tracker->max_value_id; ++i) { |
| struct xnn_value_usage* info = tracker->usage + i; |
| if (info->tensor_size != 0) { |
| sorted_usage[num_values_to_alloc++] = info; |
| } |
| } |
| qsort(sorted_usage, num_values_to_alloc, sizeof(struct xnn_value_usage*), cmp_value_usage_tensor_size); |
| |
| // Start the allocation planning process. |
| struct memory_block* current_live_mem_blocks = xnn_allocate_zero_memory( |
| sizeof(struct memory_block) * num_values_to_alloc); |
| size_t mem_arena_size = 0; |
| for (size_t i = 0; i < num_values_to_alloc; ++i) { |
| size_t num_live_mem_blocks = 0; |
| struct xnn_value_usage* current = sorted_usage[i]; |
| for (size_t j = 0; j < i; ++j) { |
| const struct xnn_value_usage* allocated = sorted_usage[j]; |
| if (value_lifecycle_overlap(current, allocated)) { |
| current_live_mem_blocks[num_live_mem_blocks++] = (struct memory_block){ |
| .start = allocated->alloc_offset, |
| .end = allocated->alloc_offset + allocated->tensor_size, |
| }; |
| } |
| } |
| current->alloc_offset = find_value_alloc_offset(current_live_mem_blocks, num_live_mem_blocks, current->tensor_size); |
| if (mem_arena_size < current->alloc_offset + current->tensor_size) { |
| mem_arena_size = current->alloc_offset + current->tensor_size; |
| } |
| } |
| |
| tracker->mem_arena_size = mem_arena_size; |
| xnn_release_memory(sorted_usage); |
| xnn_release_memory(current_live_mem_blocks); |
| #else |
| tracker->mem_arena_size = 0; |
| for (uint32_t i = tracker->min_value_id; i <= tracker->max_value_id; ++i) { |
| if (tracker->usage[i].tensor_size > 0) { |
| tracker->usage[i].alloc_offset = tracker->mem_arena_size; |
| tracker->mem_arena_size += tracker->usage[i].tensor_size; |
| } |
| } |
| #endif |
| } |