pattern_size = 6 from collections import Counter, deque from dataclasses import dataclass @dataclass(eq=True, frozen=True) class ScheduledNode: type: str chunk: int stage: int minibatch: int start_time: int completion_time: int def transform_schedule(schedule, f, b, w, c): result = [] stage_order = [] local_prev = {} stages = len(schedule) for sid, stage in enumerate(schedule): counter = Counter() order = [] for p in stage: if not p.strip(): continue mb = counter.get(p, 0) if order: local_prev[(sid, p, mb)] = order[-1] order.append((p, mb)) counter.update(p) stage_order.append(order) nmb = max(counter.values()) time_map = {} cost = { 'F': f, 'B': b, 'W': w, 'f': f, 'b': b, 'w': w, } def get_time(stage, type, mb): if (stage, type, mb) in time_map: return time_map.get((stage, type, mb)) time = 0 if (stage, type, mb) in local_prev: time = get_time(stage, *local_prev[(stage, type, mb)]) if type in "FB" and stage > 0: time = max(time, get_time(stage - 1, type, mb) + c) if type in "fb" and stage + 1< len(schedule): time = max(time, get_time(stage + 1, type, mb) + c) # print(f'{stage} {type}:{mb}', time + cost[type]) time_map[(stage, type, mb)] = time + cost[type] return time_map[(stage, type, mb)] r = 0 for sid, stage in enumerate(schedule): r = max(get_time(sid, 'W', nmb - 1) - get_time(sid, 'F', 0) + f, r) r = max(get_time(sid, 'w', nmb - 1) - get_time(sid, 'F', 0) + f, r) for sid, stage in enumerate(stage_order): result_stage = [] for p, mb in stage: result_stage.append(ScheduledNode( p.upper(), p in "fBW", sid, mb, get_time(sid, p, mb) - cost[p], get_time(sid, p, mb) ) ) result.append(result_stage) return result def evaluate_schedule(schedule, f, b, w, c): stage_order = [] local_prev = {} stages = len(schedule) for sid, stage in enumerate(schedule): counter = Counter() order = [] for p in stage: if not p.strip(): continue mb = counter.get(p, 0) if order: local_prev[(sid, p, mb)] = order[-1] order.append((p, mb)) counter.update(p) stage_order.append(order) nmb = max(counter.values()) time_map = {} cost = { 'F': f, 'B': b, 'W': w, 'f': f, 'b': b, 'w': w, } def get_time(stage, type, mb): if (stage, type, mb) in time_map: return time_map.get((stage, type, mb)) time = 0 if (stage, type, mb) in local_prev: time = get_time(stage, *local_prev[(stage, type, mb)]) if type in "FB" and stage > 0: time = max(time, get_time(stage - 1, type, mb) + c) if type in "fb" and stage + 1< len(schedule): time = max(time, get_time(stage + 1, type, mb) + c) # print(f'{stage} {type}:{mb}', time + cost[type]) time_map[(stage, type, mb)] = time + cost[type] return time_map[(stage, type, mb)] r = 0 for sid, stage in enumerate(schedule): r = max(get_time(sid, 'W', nmb - 1) - get_time(sid, 'F', 0) + f, r) r = max(get_time(sid, 'w', nmb - 1) - get_time(sid, 'F', 0) + f, r) return r debug = False def print_schedules(schedules, msg = None, force=False): if not debug and not force: return if msg is not None: print(msg) for seq in schedules: _str = "" for v in seq: _str += v print(_str) def get_building_block_str(pos): pattern = [" "] * pattern_size notations = "FfBbWw" for i, v in enumerate(pos): if v < 0: continue pattern[v] = notations[i] _str = "" for v in pattern: _str += v return _str def get_peak_mem(schedules, return_all=False): max_peak = 0 all_peak = [] for schedule_ in schedules: peak, mem = 0, 0 for v in schedule_: if v in "Ff": mem += 1 elif v in "Ww": mem -= 1 peak = max(peak, mem) all_peak.append(peak) max_peak = max(max_peak, peak) if return_all: return all_peak return max_peak def calc_bubble(schedules): stage_bubbles = [] for i in range(len(schedules)): max_len = 0 count = 0 for j in range(len(schedules[i])): if schedules[i][j] != ' ': max_len = j + 1 count += 1 stage_bubbles.append(max_len - count - i) return stage_bubbles def init_repeated_schedule(p, m, building_block): repeated = [] _len = 4 * p + m + 1 for i in range(p): str_i = get_building_block_str(building_block[i]) * _len repeated_i = [] for v in str_i: repeated_i.append(v) repeated.append(repeated_i) return repeated def clear_invalid(repeated, stage, pos, offset=-1): while 0 <= pos < len(repeated[stage]): repeated[stage][pos] = ' ' pos += offset * pattern_size return repeated def clear_invalid_index(repeated, m): p = len(repeated) index = pattern_size for identifier in "FfBb": if identifier in "FB": _iter = range(p) else: _iter = range(p - 1, -1, -1) for i in _iter: for j in range(pattern_size): if repeated[i][index] == identifier: clear_invalid(repeated, i, index - pattern_size, offset=-1) clear_invalid(repeated, i, index + pattern_size * m, offset=1) index += 1 if identifier in "Bb": w_identifier = {'B': 'W', 'b': 'w'}[identifier] for k in range(pattern_size): if repeated[i][index + k] == w_identifier: clear_invalid(repeated, i, index + k - pattern_size, offset=-1) clear_invalid(repeated, i, index + k + pattern_size * m, offset=1) break break index += 1 return repeated def process_warmup_without_increasing_peak_mem(schedules, m): """ FFFFFFFFFF fBWfBWfBWfBWfBW b FFFFFFFFF f fBWfBWfBWfBWFBWb FFFFFFFF f f fBWfBWfBWFBW b FFFFFFF f f f fBWfBWFBW Bb FFFFFF f f f f fBWFBWFBWb FFFFFfFf f f f BWFBW b FFFfFfFfFf f BW Bb FfFfFfFfFfF BWb We reorganize the warmup phase in the following way (i -> pipeline stage from 0): 1. Before the first B, we set #f = min(i+1, peak_mem//2), #F = peak_mem - #f 2. Before the first b, #f = peak_mem//2 3. The offset between the first B is 1 4. Before the first b, we use the pattern of (BWf)*j + (BWF)*k, where j = max(0, peak_mem//2 - (i+1)), k = max(0, #W - j - 1) """ # process warmup phase (before the first b) p = len(schedules) peak_mem = get_peak_mem(schedules) peak_mem = min(peak_mem, 2 * p) cnt_f, cnt_ff = [], [] for i in range(p): cc_ff = min(i + 1, peak_mem // 2) cc_ff = min(cc_ff, m) cc_f = min(peak_mem - cc_ff, m) cnt_f.append(cc_f) cnt_ff.append(cc_ff) distance_b2bb = 0 for j in range(len(schedules[p - 1])): if schedules[p - 1][j] == 'B': for k in range(j, len(schedules[p - 1])): if schedules[p - 1][k] == 'b': distance_b2bb = k - j break break for i in range(p): c_f, c_ff, c_b, c_w = 0, 0, 0, 0 for j in range(len(schedules[i])): char = schedules[i][j] if char == 'F': c_f += 1 elif char == 'f': c_ff += 1 elif char == 'B': c_b += 1 elif char == 'W': c_w += 1 elif char == 'b': break # This logic can be removed because it is too complicated and should not impact the optimal solution bj = j while j < len(schedules[i]): char = schedules[i][j] if char == 'f' and c_ff < cnt_ff[p - 1]: schedules[i][j] = ' ' c_ff += 1 if char == 'B' and c_b < c_ff: if c_b < (2 * (p - i) + distance_b2bb) // 3 or c_b < cnt_ff[p - 1] - cnt_ff[i]: # there is empty space, or the number of B is not enough to cover extra f schedules[i][j] = ' ' c_b += 1 if char == 'W' and c_w < c_b: if c_w < (2 * (p - i) + distance_b2bb - 1) // 3 or c_w < cnt_ff[p - 1] - cnt_ff[i]: # there is empty space, or the number of W is not enough to cover extra f schedules[i][j] = ' ' c_w += 1 j += 1 j = bj while j < len(schedules[i]): if schedules[i][j] == 'F': if c_f < c_ff or c_f < cnt_f[i] or c_f - cnt_f[i] + c_ff - cnt_ff[i] < c_w - 1: # put enough F, or there are some unused BW schedules[i][j] = ' ' c_f += 1 j += 1 break else: assert char == ' ' schedules[i][j] = ' ' # assert c_f >= cnt_f[i] and c_ff >= cnt_ff[i] # assert c_w >= cnt_ff[p - 1] - cnt_ff[i] and c_b >= cnt_ff[p - 1] - cnt_ff[i] j = i u_f, u_ff, u_b, u_w = 0, 0, 0, 0 for _ in range(2 * (p - 1 - i)): if u_f < cnt_f[i] and u_f < c_f: schedules[i][j] = 'F' u_f += 1 j += 1 for _ in range(i + 1): if u_f < cnt_f[i] and u_f < c_f: schedules[i][j] = 'F' u_f += 1 j += 1 if u_ff < cnt_ff[i] and u_ff < c_ff: schedules[i][j] = 'f' u_ff += 1 j += 1 while u_f < c_f or u_ff < c_ff or u_b < c_b or u_w < c_w: if u_b < c_b: schedules[i][j] = 'B' u_b += 1 j += 1 if u_w < c_w: schedules[i][j] = 'W' u_w += 1 j += 1 if u_ff < c_ff: assert u_ff < u_f schedules[i][j] = 'f' u_ff += 1 elif u_f < c_f: schedules[i][j] = 'F' u_f += 1 j += 1 return schedules def squeeze_without_change_order(schedules, m): p = len(schedules) squeezed = [[' '] * len(schedules[_]) for _ in range(p)] max_len = check_and_get_schedule_len(schedules) identifier_cnt = [{_id: 0 for _id in "FfBbWw"} for _ in range(p)] identifier_index = [{_id: -1 for _id in "FfBbWw"} for _ in range(p * m)] stage_index = [0 for _ in range(p)] for j in range(max_len): for _dir in range(2): if _dir == 0: _iter = range(p) else: _iter = range(p - 1, -1, -1) for i in _iter: identifier = schedules[i][j] if identifier == ' ': continue if _dir == 0 and identifier in "fbw": continue if _dir == 1 and identifier in "FBW": continue _cnt = identifier_cnt[i][identifier] assert _cnt < m, "{} - {}, {}".format(i, identifier, _cnt) if identifier in "Ww" or (i == 0 and identifier in "FB") or (i == p - 1 and identifier in "fb"): if i == 0 and identifier == 'B': assert identifier_index[_cnt * p + i]['f'] >= 0 if i == p - 1 and identifier == 'f': assert identifier_index[_cnt * p + i]['F'] >= 0 if i == p - 1 and identifier == 'b': assert identifier_index[_cnt * p + i]['B'] >= 0 index = stage_index[i] elif identifier in "FB": assert identifier_index[_cnt * p + i - 1][identifier] >= 0, "{} {} {}".format(i, identifier,_cnt) index = max(identifier_index[_cnt * p + i - 1][identifier] + 1, stage_index[i]) elif identifier in "fb": assert identifier_index[_cnt * p + i + 1][identifier] >= 0, "{} {} {}".format(i, identifier,_cnt) index = max(identifier_index[_cnt * p + i + 1][identifier] + 1, stage_index[i]) else: raise squeezed[i][index] = identifier identifier_cnt[i][identifier] = _cnt + 1 identifier_index[_cnt * p + i][identifier] = index stage_index[i] = index + 1 new_len = max(stage_index) for i in range(p): squeezed[i] = squeezed[i][:new_len] return squeezed def process_cooldown(schedules, m): """ fBW bwbwbwbw fBWBW bwbwbwbw fBWBWBW bwbwbwbw fBWBWBWBW bwbwbwbw f BWBWBWBbWbwbwbww f BWBWBbBbWbWbwwww f BWBbBbBbWbWWwwww f BbBbBbBbWWWWwwww We reorganize the cooldown phase in the following way (i -> pipeline stage from 0): 1. After the last f, we set #b = (peak_mem+1)//2, and #B = min(i+1, peak_mem - #b) 2. After the last f, we make all the dependencies as tight as possible """ p = len(schedules) peak_mem = get_peak_mem(schedules) assert peak_mem <= 2 * p, peak_mem max_bb = (peak_mem + 1) // 2 max_bb = min(max_bb, m) max_b = min(peak_mem - max_bb, m) # 1: reorganize B/b and remove W/w in cooldown phase starting_index = -1 for i in range(p): c_b, c_bb, c_w, c_ww = 0, 0, 0, 0 last_ff_index = -1 # collect B/b which can be reordered for j in range(len(schedules[i]) - 1, -1, -1): char = schedules[i][j] if char == 'f' and last_ff_index == -1: last_ff_index = j if char == 'B' and c_b < i + 1 and c_b < max_b: schedules[i][j] = ' ' c_b += 1 if char == 'b' and c_bb < max_bb: schedules[i][j] = ' ' c_bb += 1 # clear W in the tail (#W + #w >= peak_mem & #W >= #B & #w >= #b) for j in range(len(schedules[i]) - 1, -1, -1): char = schedules[i][j] if c_w >= c_b and c_ww >= c_bb and c_w + c_ww >= peak_mem: break if char == 'W': schedules[i][j] = ' ' c_w += 1 if char == 'w': schedules[i][j] = ' ' c_ww += 1 if i == 0: starting_index = last_ff_index # reorganize B/b in the tail for k in range(c_bb): index = starting_index - i + 2 * p - 2 * k assert schedules[i][index] == ' ', "{} {} {}".format(schedules[i][index], k, i) schedules[i][index] = 'b' for k in range(c_b): index = starting_index + 1 + i - 2 * k # assert schedules[i][index] == ' ', schedules[i][index] schedules[i][index] = 'B' # 2: add W back in cooldown phase max_len = 0 for i in range(p): c_w, c_ww = 0, 0 last_w_index = -1 for j in range(len(schedules[i]) - 1, -1, -1): if schedules[i][j] in "Ww": last_w_index = j break for j in range(len(schedules[i])): char = schedules[i][j] if char == 'B': c_w += 1 elif char == 'b': c_ww += 1 elif char == 'W': c_w -= 1 elif char == 'w': c_ww -= 1 if char == ' ' and j > last_w_index: if c_w > 0: schedules[i][j] = 'W' c_w -= 1 elif c_ww > 0: schedules[i][j] = 'w' c_ww -= 1 for _ in range(c_w): schedules[i].append('W') for _ in range(c_ww): schedules[i].append('w') max_len = max(max_len, len(schedules[i])) for i in range(p): for _ in range(len(schedules[i]), max_len): schedules[i].append(' ') schedules = squeeze_without_change_order(schedules, m) return schedules def check_and_get_schedule_len(schedules): max_len = 0 for seq in schedules: assert max_len == 0 or max_len == len(seq) max_len = max(max_len, len(seq)) return max_len def release_w_in_warmup_if_under_memory(schedules, peak_mem = None): """ FF fBWfBW bwbw -> FF fBfBWW bwbw FF f fBW BW bwbw -> FF f fBWBW bwbw FF f f BW BbWbww -> FF f f BWBbWbww FfFf BbWBbwWw -> FfFf BbBbWwWw When the number of micro-batches is too small (than mem), the warmup phase is not optimal. We simply remove some preceding W to fully utilize the memory to reduce unnecessary bubbles. """ p = len(schedules) max_len = check_and_get_schedule_len(schedules) all_peak_mem = get_peak_mem(schedules, return_all=True) peak_mem = peak_mem or max(all_peak_mem) min_peak = min(all_peak_mem) for i in range(p): cnt = 0 padding = [" "] * (peak_mem - min_peak) for j in range(max_len): if all_peak_mem[i] + cnt >= peak_mem: break if schedules[i][j] in "Ww": padding[cnt] = schedules[i][j] schedules[i][j] = ' ' cnt += 1 schedules[i].extend(padding) # max_len += peak_mem - min_peak return schedules def reorder_greedily_without_increasing_peak_mem(schedules, m, starting_index = None, ending_index = None, peak_mem = None): """ We iterate all the cells from left to right. If a vacant cell (which means a bubble) is encountered, we try to find a computation pass to fill this bubble. We iterate all the following computation passes in the same device, and check whether it is possible to move if we keep all other passes unchanged. If the check succeeds, we move it to the vacant cell, and the bubble is filled. """ p = len(schedules) if starting_index is not None: assert isinstance(starting_index, list) and len(starting_index) == p if ending_index is not None: assert isinstance(ending_index, list) and len(ending_index) == p peak_mem = peak_mem or get_peak_mem(schedules) max_len = check_and_get_schedule_len(schedules) starting_index = starting_index or [0] * p ending_index = ending_index or [max_len] * p last_index = [{_id: -1 for _id in "FfBbWw"} for _ in range(p)] for i in range(p): for j in range(max_len): identifier = schedules[i][j] if identifier == ' ': continue last_index[i][identifier] = j stage_mem = [0] * p def update_mem(stage_i, pass_c): if pass_c in "Ff": stage_mem[stage_i] += 1 elif pass_c in "Ww": stage_mem[stage_i] -= 1 identifier_cnt = [{_id: 0 for _id in "FfBbWw"} for _ in range(p)] identifier_index = [{_id: -1 for _id in "FfBbWw"} for _ in range(p * m)] for j in range(0, max_len): for i in range(p): identifier = schedules[i][j] if identifier in "FfBbWw": _cnt = identifier_cnt[i][identifier] identifier_cnt[i][identifier] = _cnt + 1 identifier_index[_cnt * p + i][identifier] = j update_mem(i, identifier) continue assert identifier == ' ' if j < starting_index[i] or j >= ending_index[i]: continue available = set() for c in "FfBbWw": if last_index[i][c] > j: available.add(c) mem_delta, peak_delta = 0, 0 for k in range(j + 1, ending_index[i]): if len(available) == 0: break identifier = schedules[i][k] if identifier in "Ff": mem_delta += 1 elif identifier in "Ww": mem_delta -= 1 prev_peak = peak_delta peak_delta = max(peak_delta, mem_delta) if identifier == ' ' or identifier not in available: continue available.remove(identifier) if identifier in "Ff" and stage_mem[i] + prev_peak >= peak_mem: # will increase peak memory continue can_move = True _cnt = identifier_cnt[i][identifier] if identifier in "FB": if i > 0: _index = identifier_index[_cnt * p + i - 1][identifier] if _index <= -1 or _index >= j: can_move = False elif identifier == 'B': if identifier_cnt[i]['f'] <= _cnt: can_move = False elif identifier in "fb": if i + 1 < p: _index = identifier_index[_cnt * p + i + 1][identifier] if _index <= -1 or _index >= j: can_move = False else: _pi = 'F' if identifier == 'f' else 'B' if identifier_cnt[i][_pi] <= _cnt: can_move = False elif identifier in "Ww": _bi = 'B' if identifier == 'W' else 'b' if identifier_cnt[i][_bi] <= _cnt: can_move = False else: assert False if not can_move: continue # if i == 0: # print(peak_mem, stage_mem[i], identifier, mem_delta) schedules[i][j] = identifier schedules[i][k] = ' ' identifier_cnt[i][identifier] = _cnt + 1 identifier_index[_cnt * p + i][identifier] = j update_mem(i, identifier) break return schedules def check_correctness(schedules, m, raise_exception=False): p = len(schedules) c_index = [{_id: -1 for _id in "FfBbWw"} for _ in range(p * m)] for i in range(p): c_cnt = {_id: 0 for _id in "FfBbWw"} for j in range(len(schedules[i])): c = schedules[i][j] if c in "FfBbWw": _cnt = c_cnt[c] assert _cnt < m c_index[_cnt * p + i][c] = j c_cnt[c] = _cnt + 1 for c in "FfBbWw": if c_cnt[c] != m: assert not raise_exception return False for i in range(p): for j in range(m): for c in "FfBbWw": if c_index[j * p + i][c] == -1: assert not raise_exception return False if c_index[j * p + i]['B'] >= c_index[j * p + i]['W']: assert not raise_exception, f"{i} {j} {c}" return False if c_index[j * p + i]['b'] >= c_index[j * p + i]['w']: assert not raise_exception return False if i == 0: if c_index[j * p + i]['f'] >= c_index[j * p + i]['B']: assert not raise_exception return False elif i == p - 1: if c_index[j * p + i]['F'] >= c_index[j * p + i]['f']: assert not raise_exception return False if c_index[j * p + i]['B'] >= c_index[j * p + i]['b']: assert not raise_exception return False else: if c_index[j * p + i - 1]['F'] >= c_index[j * p + i]['F']: assert not raise_exception return False if c_index[j * p + i - 1]['B'] >= c_index[j * p + i]['B']: assert not raise_exception return False if c_index[j * p + i + 1]['f'] >= c_index[j * p + i]['f']: assert not raise_exception return False if c_index[j * p + i + 1]['b'] >= c_index[j * p + i]['b']: assert not raise_exception return False return True def relabel_w(schedules, m): p = len(schedules) c_cnt = [{_id: 0 for _id in "FfBbWw"} for _ in range(p)] for i in range(p): for j in range(len(schedules[i])): if schedules[i][j] == ' ': continue c_cnt[i][schedules[i][j]] += 1 for c in "FfBbWw": assert c_cnt[i][c] == m, f"{i}, {c}, {c_cnt[i][c]}" for i in range(p): w_queue = deque(maxlen=2 * m) for j in range(len(schedules[i])): identifier = schedules[i][j] if identifier == 'B': w_queue.append('W') elif identifier == 'b': w_queue.append('w') elif identifier in "Ww": assert len(w_queue) > 0, f"{i} {j}" schedules[i][j] = w_queue.popleft() assert len(w_queue) == 0 return schedules def remove_redundancy(schedules, m): for sid in range(len(schedules)): cnt = {_id: 0 for _id in "FfBbWw"} for i in range(len(schedules[sid])): if schedules[sid][i] == ' ': continue if cnt[schedules[sid][i]] >= m: schedules[sid][i] = ' ' else: cnt[schedules[sid][i]] += 1 return schedules def schedule_by_building_block(p, m, building_block, max_mem, keep_stable_phase=False): # Apply the framework of repeating-squeezing-reordering # 1. repeating redundant_m = max(m, 2 * p) # we add some redundant micro-batches to avoid unexpected bugs schedules = init_repeated_schedule(p, redundant_m, building_block) schedules = clear_invalid_index(schedules, redundant_m) init_peak_mem = get_peak_mem(schedules) if (m == redundant_m and init_peak_mem > max_mem) or init_peak_mem > 2 * p: return None, init_peak_mem, [6 * m] * p print_schedules(schedules, "after repeating") # 2. squeezing schedules = squeeze_without_change_order(schedules, redundant_m) print_schedules(schedules, "after squeezing") # 3. reordering # 3.a. reorder warm-up schedules = process_warmup_without_increasing_peak_mem(schedules, redundant_m) # must work with m >= 2p schedules = squeeze_without_change_order(schedules, redundant_m) if keep_stable_phase: ending_index = [0] * p # before second b for i in range(p): bb_cnt = 0 for j in range(len(schedules[i])): if schedules[i][j] == 'b': bb_cnt += 1 if bb_cnt >= 2: ending_index[i] = j break schedules = reorder_greedily_without_increasing_peak_mem(schedules, redundant_m, ending_index=ending_index) peak_mem = get_peak_mem(schedules) if debug: assert peak_mem <= init_peak_mem, f"{init_peak_mem}, {peak_mem}" if peak_mem > init_peak_mem: return None, init_peak_mem, [6 * m] * p if m < redundant_m: # 4. remove redundancy schedules = remove_redundancy(schedules, m) if m <= p and 2 * m <= max_mem: schedules = release_w_in_warmup_if_under_memory(schedules, peak_mem=min(2 * p, peak_mem)) schedules = squeeze_without_change_order(schedules, m) print_schedules(schedules, "after removing redundancy") init_peak_mem = peak_mem = get_peak_mem(schedules) if peak_mem > max_mem: return None, peak_mem, [6 * m] * p # 3.b. reorder cool-down schedules = process_cooldown(schedules, m) if keep_stable_phase: starting_index = [0] * p for i in range(p): for j in range(len(schedules[i])): if schedules[i][j] == 'F': starting_index[i] = j schedules = reorder_greedily_without_increasing_peak_mem(schedules, m, starting_index=starting_index) if not keep_stable_phase: reorder_greedily_without_increasing_peak_mem(schedules, m) schedules = relabel_w(schedules, m) print_schedules(schedules, "after reordering") peak_mem = get_peak_mem(schedules) if debug: assert peak_mem <= init_peak_mem, f"{init_peak_mem}, {peak_mem}" if peak_mem > init_peak_mem: return None, init_peak_mem, [6 * m] * p # return if not check_correctness(schedules, m, raise_exception=debug): return None, peak_mem, [6 * m] * p stage_bubbles = calc_bubble(schedules) if debug: print(peak_mem, stage_bubbles) print("-" * 100) return schedules, peak_mem, stage_bubbles def fill_w_in_building_block(pattern): f, ff, b, bb, w, ww = 0, 1, 2, 3, 4, 5 vis = [False] * pattern_size for v in pattern: if v >= 0: vis[v] = True assert pattern[b] >= 0 and pattern[bb] >= 0 for v, vw in [(b, w), (bb, ww)]: for j in range(pattern_size): pos = (pattern[v] + j) % pattern_size if not vis[pos]: pattern[vw] = pos vis[pos] = True break return pattern def get_building_block(pattern_0, offset_0, offset_1, len_0, p): # see Appendix A in the paper build_block = [pattern_0] for i in range(p - 1): last_pattern = build_block[i] new_pattern = [-1] * pattern_size vis = [False] * pattern_size if i < len_0: offset = offset_0 else: offset = offset_1 for v, v_o in enumerate(offset): pos = (last_pattern[v] + v_o + pattern_size) % pattern_size assert 0 <= pos < pattern_size if vis[pos]: return None vis[pos] = True new_pattern[v] = pos new_pattern = fill_w_in_building_block(new_pattern) build_block.append(new_pattern) return build_block def schedule(p, m, cost, max_mem): f, ff, b, bb, w, ww = 0, 1, 2, 3, 4, 5 available_starting_patterns = [] # iterate available patterns for the first row/device of a building block for ff_i in range(1, pattern_size): for b_i in range(1, pattern_size): for bb_i in range(1, pattern_size): if ff_i == b_i or ff_i == bb_i or b_i == bb_i: continue pattern = [0, ff_i, b_i, bb_i, -1, -1] pattern = fill_w_in_building_block(pattern) available_starting_patterns.append(pattern) # available uniform offsets, see Section 3.1 in the paper. available_offsets = [ # [\delta_F^0, \delta_F^1, \delta_B^1, \delta_B^0] [1, -1, 1, -1], [2, -1, 2, -1], [3, -1, 3, -1], [4, -1, 4, -1], [5, -1, 5, -1] ] # available_starting_patterns = available_starting_patterns[:1] best_schedule = None best_bubble = None peak_mem2min_bubble = {} for pattern_0 in available_starting_patterns: for i_0 in range(len(available_offsets)): for i_1 in range(i_0 + 1): for len_0 in range(1, p): offset_0 = available_offsets[i_0] offset_1 = available_offsets[i_1] build_block = get_building_block(pattern_0, offset_0, offset_1, len_0, p) if build_block is None: continue s, peak_mem, bubbles = schedule_by_building_block(p, m, build_block, min(2 * p, max_mem)) if peak_mem > 2 * p or peak_mem > max_mem: break if s is None: continue max_bubble = evaluate_schedule(s, *cost) if best_schedule is None or max_bubble < best_bubble: best_schedule, best_bubble = s, max_bubble max_bubble = max(bubbles) min_bubble = min(peak_mem2min_bubble.get(peak_mem, max_bubble), max_bubble) peak_mem2min_bubble[peak_mem] = min_bubble mem2bubble = {} for peak_mem in sorted(peak_mem2min_bubble.keys()): bubble = peak_mem2min_bubble[peak_mem] mem2bubble[peak_mem] = bubble # expected_bubble = max(0, 6 * p - 1 - 3 * peak_mem) expected_bubble = 3 * p - 1 - 3 * peak_mem + max(3 * p, p - 1 + (1+(peak_mem+1)//2)*2) # expected_bubble = 6 * p - 1 - 3 * peak_mem print(peak_mem, bubble, expected_bubble, "|", bubble - expected_bubble) print(mem2bubble) res = transform_schedule(best_schedule, *cost) return res