| # Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved. |
| # |
| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # Licensed under the Apache License, Version 2.0 (the License); you may |
| # not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an AS IS BASIS, WITHOUT |
| # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # Description: |
| # Allocate tensor addresses using a greedy algorithm. |
| from . import numeric_util |
| |
| |
| class GreedyAllocator: |
| def __init__(self, nng, arch, live_ranges, mem_area): |
| self.nng = nng |
| self.arch = arch |
| self.mem_area = mem_area |
| |
| self.live_ranges = live_ranges |
| self.memory_required = 0 |
| |
| self.current_allocs = [] |
| |
| def alloc(self, new_lr): |
| size = new_lr.size |
| current_top = 0 |
| if self.current_allocs: |
| current_top = max(start_addr + lr.size for start_addr, lr in self.current_allocs) |
| best_offset = numeric_util.round_up(current_top, new_lr.get_alignment()) |
| best_offset_fit = (1 << 64) - 1 |
| |
| current_offset = 0 |
| for start_addr, lr in self.current_allocs: |
| aligned_current_offset = numeric_util.round_up(current_offset, new_lr.get_alignment()) |
| if aligned_current_offset + size <= start_addr and start_addr - current_offset < best_offset_fit: |
| best_offset = current_offset |
| best_offset_fit = start_addr - current_offset |
| |
| current_offset = start_addr + lr.size |
| |
| best_offset = new_lr.set_address(best_offset) |
| self.memory_required = max(self.memory_required, best_offset + size) |
| self.current_allocs.append((best_offset, new_lr)) |
| self.current_allocs = list(sorted(self.current_allocs)) |
| |
| def dealloc(self, lr_to_dealloc): |
| self.current_allocs = [(start_addr, lr) for start_addr, lr in self.current_allocs if lr != lr_to_dealloc] |
| |
| def allocate_live_ranges(self, verbose_allocation): |
| lrs = set() |
| for lr in self.live_ranges.ranges.values(): |
| lrs.add((lr.start_time, lr.end_time, lr)) |
| |
| lrs = sorted(lrs) |
| |
| for curr_time, _, new_lr in lrs: |
| for _, lr in list(self.current_allocs): |
| if lr.end_time < curr_time: |
| self.dealloc(lr) |
| |
| self.alloc(new_lr) |
| |
| assert self.verify_allocation() |
| return self.memory_required |
| |
| def verify_allocation(self): |
| lrs = list(self.live_ranges.ranges.values()) |
| for n in lrs: |
| for m in lrs: |
| if n != m and n.overlaps_ranges(m): |
| overlap, tens_n, tens_m = n.overlaps_address(m) |
| if overlap and not (tens_n.equivalent(tens_m) and tens_n.address == tens_m.address): |
| print("Solution failed, overlapping buffer!") |
| print(tens_n.address, tens_n.address + n.size, n.name) |
| print(tens_m.address, tens_m.address + m.size, m.name) |
| print() |
| return False |
| |
| return True |
| |
| |
| def allocate_live_ranges(nng, arch, live_ranges, mem_area, verbose_allocation=False): |
| g = GreedyAllocator(nng, arch, live_ranges, mem_area) |
| return g.allocate_live_ranges(verbose_allocation) |