mirror of https://github.com/hpcaitech/ColossalAI
450 lines
19 KiB
Python
450 lines
19 KiB
Python
# Refer from Zero Bubble Pipeline Parallelism.
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# Github: https://github.com/sail-sg/zero-bubble-pipeline-parallelism
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# Paper: https://arxiv.org/abs/2401.10241
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# The following applies to all files unless otherwise noted:
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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions
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# are met:
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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# * Neither the name of NVIDIA CORPORATION nor the names of its
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# contributors may be used to endorse or promote products derived
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# from this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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from collections import deque
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from dataclasses import dataclass
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@dataclass(eq=True, frozen=True)
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class ScheduledNode:
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type: str
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chunk: int
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stage: int
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minibatch: int
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start_time: int = 0
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completion_time: int = 0
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rollback: bool = False
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class PipelineGraph(object):
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"""PipelineGraph"""
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def __init__(
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self,
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n_stage,
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n_micro,
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f_cost,
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b_cost,
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w_cost,
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c_cost,
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f_mem,
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b_mem,
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w_mem,
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max_mem=None,
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):
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self.n_node = 6 * n_stage * n_micro
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self.n_stage = n_stage
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self.n_micro = n_micro
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self.f_cost = f_cost
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self.b_cost = b_cost
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self.w_cost = w_cost
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self.c_cost = c_cost
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self.f_mem = f_mem
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self.b_mem = b_mem
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self.w_mem = w_mem
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self.fbw_cost = [f_cost, b_cost, w_cost]
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self.fbw_mem = [f_mem, b_mem, w_mem]
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self.max_mem = max_mem or f_mem * self.n_stage * 2
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def get_id(self, cat, chunk, stage, micro):
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return (
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cat * 2 * self.n_stage * self.n_micro + chunk * self.n_stage * self.n_micro + stage * self.n_micro + micro
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)
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def try_v_schedule(self, fill_f=True, fill_b=True, approved_bubble=None):
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count = []
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for i in range(self.n_stage):
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count.append([0] * 6)
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end_time = [-1] * self.n_node
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cur_time = [0] * self.n_stage
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mem = [0] * self.n_stage
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stage_bubble = [0] * self.n_stage
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pending_w = [deque() for _ in range(self.n_stage)]
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schedule = [[] for _ in range(self.n_stage)]
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stage_str = [" " * i for i in range(self.n_stage)]
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if approved_bubble is None:
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approved_bubble = [-1] * self.n_stage
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max_approved_bubble = max(approved_bubble)
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def get_max_stage_bubble(stage=-1):
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max_stage_bubble = 0
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for bb in stage_bubble:
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max_stage_bubble = max(max_stage_bubble, bb)
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if stage >= 0:
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max_stage_bubble = max(max_stage_bubble, max_approved_bubble - approved_bubble[stage])
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return max_stage_bubble
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def put_w(stage):
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assert len(pending_w[stage]) > 0
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_, chunk_, _ = pending_w[stage].popleft()
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put(2, chunk_, stage)
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def put(cat, chunk, stage, assert_cnt=True):
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_tmp = _no_bubble = cur_time[stage] + self.fbw_cost[cat]
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_cnt = count[stage][cat * 2 + chunk]
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# assert _cnt < self.n_micro
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if _cnt >= self.n_micro:
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if not assert_cnt:
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stage_str[stage] += " "
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cur_time[stage] = _tmp # TODO
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return
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assert False
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assert mem[stage] + self.fbw_mem[cat] <= self.max_mem
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stage_str[stage] += "FfBbWw"[cat * 2 + chunk] + str(_cnt + 1) + " " * (3 - len(str(_cnt + 1)))
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if cat > 0 or chunk > 0:
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last_id = cat * 2 + chunk - 1
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if cat < 2:
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assert end_time[self.get_id(last_id // 2, last_id % 2, stage, _cnt)] >= 0
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else:
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assert end_time[self.get_id(1, chunk, stage, _cnt)] >= 0
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if chunk == 1 and cat < 2:
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if stage < self.n_stage - 1:
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_fa_id = self.get_id(cat, chunk, stage + 1, _cnt)
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assert end_time[_fa_id] >= 0
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_tmp = max(_tmp, end_time[_fa_id] + self.c_cost + self.fbw_cost[cat])
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if chunk == 0 and cat < 2:
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if stage > 0:
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_fa_id = self.get_id(cat, chunk, stage - 1, _cnt)
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assert end_time[_fa_id] >= 0, f"{cat}, {chunk}, {stage}, {_cnt}"
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_tmp = max(_tmp, end_time[_fa_id] + self.c_cost + self.fbw_cost[cat])
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_id = self.get_id(cat, chunk, stage, _cnt)
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if count[stage][0] > 0:
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stage_bubble[stage] += _tmp - _no_bubble
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end_time[_id] = _tmp
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cur_time[stage] = _tmp
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mem[stage] += self.fbw_mem[cat]
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# noinspection PyTypeChecker
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schedule[stage].append((cat, chunk, _cnt))
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if cat == 1:
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pending_w[stage].append((2, chunk, _cnt))
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count[stage][cat * 2 + chunk] += 1
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for i in range(self.n_stage):
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put(0, 0, i)
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for i in range(self.n_stage - 1, -1, -1):
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if i == self.n_stage - 1:
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put(0, 1, i)
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continue
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tmp = end_time[self.get_id(0, 1, i + 1, 0)] + self.c_cost
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while (
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mem[i] + self.fbw_mem[0] * (2 + i * 2) <= self.max_mem
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and cur_time[i] + self.fbw_cost[0] <= tmp
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and count[i][0] < self.n_micro
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):
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for j in range(i + 1):
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put(0, 0, j)
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put(0, 1, i)
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iter_chunk_ = 0
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end_tmp = 0
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for i in range(self.n_stage):
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if i == 0:
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end_tmp = cur_time[0] + self.fbw_cost[1]
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continue
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tmp = end_tmp + self.c_cost
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while (
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count[i][0] + count[i][1] < count[i - 1][0] + count[i - 1][1]
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or count[i][1] <= count[i - 1][1] < self.n_micro
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):
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for j in range(self.n_stage - 1, i - 1, -1):
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if count[j][iter_chunk_] < self.n_micro:
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put(0, iter_chunk_, j)
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iter_chunk_ = 1 - iter_chunk_
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for _ in range(2 * self.n_micro):
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# check mem before putting b
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for i in range(self.n_stage):
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while mem[i] + self.fbw_mem[1] > self.max_mem:
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assert len(pending_w[i]) > 0
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put_w(i)
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b0_ranks, b1_ranks = [], []
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for i in range(self.n_stage):
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if count[i][3] >= count[i][2]:
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b0_ranks.append(i)
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elif i == self.n_stage - 1:
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b1_ranks.append(i)
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else:
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fa_id = self.get_id(1, 1, i + 1, count[i][3])
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if end_time[fa_id] >= 0 or count[i][2] >= self.n_micro:
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b1_ranks.append(i)
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else:
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b0_ranks.append(i)
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b_ranks = []
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# put b1
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for i in reversed(b1_ranks):
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b_ranks.append((i, 1))
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# put b0
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for i in b0_ranks:
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b_ranks.append((i, 0))
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for i, _chunk_ in b_ranks:
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fa_id = -1
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if _chunk_ == 1 and i < self.n_stage - 1:
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fa_id = self.get_id(1, 1, i + 1, count[i][3])
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if _chunk_ == 0 and i > 0:
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fa_id = self.get_id(1, 0, i - 1, count[i][2])
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while (
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len(pending_w[i]) > 0
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and fa_id >= 0
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and end_time[fa_id] + self.c_cost >= cur_time[i] + self.fbw_cost[2]
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):
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# fill the bubble
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put_w(i)
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if (
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len(pending_w[i]) > 0
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and end_time[fa_id] + self.c_cost - cur_time[i] > get_max_stage_bubble(i) - stage_bubble[i]
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):
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if _chunk_ == 1:
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put_w(i)
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elif fill_b:
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put_w(i)
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put(1, _chunk_, i)
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# put f
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for i in range(self.n_stage):
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if count[i][1] >= self.n_micro:
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continue
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put_item = None
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if count[i][1] >= count[i][0]:
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put_item = 0
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elif i == self.n_stage - 1:
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put_item = 1
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else:
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if end_time[self.get_id(0, 1, i + 1, count[i][1])] >= 0:
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put_item = 1
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elif count[i][0] < self.n_micro:
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if i == 0:
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put_item = 0
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elif end_time[self.get_id(0, 0, i - 1, count[i][0])] >= 0:
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put_item = 0
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if put_item is None:
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continue
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# check mem before putting f
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while mem[i] + self.fbw_mem[0] > self.max_mem:
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assert len(pending_w[i]) > 0
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put_w(i)
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fa_id = -1
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if put_item == 0 and i > 0:
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fa_id = self.get_id(0, 0, i - 1, count[i][0])
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if put_item == 1 and i < self.n_stage - 1:
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fa_id = self.get_id(0, 1, i + 1, count[i][1])
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while (
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len(pending_w[i]) > 0
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and fa_id >= 0
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and end_time[fa_id] + self.c_cost >= cur_time[i] + self.fbw_cost[2]
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):
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# fill the bubble
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put_w(i)
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if (
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len(pending_w[i]) > 0
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and end_time[fa_id] + self.c_cost - cur_time[i] > get_max_stage_bubble(i) - stage_bubble[i]
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):
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if fill_f:
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put_w(i)
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put(0, put_item, i)
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for i in range(self.n_stage):
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while len(pending_w[i]) > 0:
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put_w(i)
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max_bubble = get_max_stage_bubble()
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expected_time = sum(self.fbw_cost) * self.n_micro * 2
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max_bubble / expected_time
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if max_approved_bubble < 0 or max_bubble < max_approved_bubble:
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_schedule, _end_time, _max_bubble = self.try_v_schedule(
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fill_f=fill_f,
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fill_b=fill_b,
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approved_bubble=stage_bubble,
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)
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if _max_bubble < max_bubble:
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return _schedule, _end_time, _max_bubble
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return schedule, end_time, max_bubble
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def print_details(self, end_time, print_scaling=1):
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for stage in range(self.n_stage):
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stage_str = ["."] * int(max(end_time) / print_scaling)
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for _cat in range(3):
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for _chunk in range(2):
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for _micro in range(self.n_micro):
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_id = self.get_id(_cat, _chunk, stage, _micro)
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if end_time[_id] < 0:
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continue
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end = int(end_time[_id] / print_scaling)
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start = int((end_time[_id] - self.fbw_cost[_cat]) / print_scaling)
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for j in range(start, end):
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if j == start or j == end - 1:
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stage_str[j] = "FfBbWw"[_cat * 2 + _chunk]
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elif j == start + 1:
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if _micro >= 10:
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stage_str[j] = str(_micro // 10)
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else:
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stage_str[j] = str(_micro)
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elif j == start + 2 and _micro >= 10:
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stage_str[j] = str(_micro % 10)
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else:
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stage_str[j] = "-"
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_str = ""
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for _c in stage_str:
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_str += _c
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print(_str)
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def get_v_schedule(self, only_run_time=False):
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schedule, end_time, max_bubble = None, None, None
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expected_time = sum(self.fbw_cost) * self.n_micro * 2
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for fill_b in [True, False]:
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for fill_f in [True, False]:
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_schedule, _end_time, _max_bubble = self.try_v_schedule(fill_b=fill_b, fill_f=fill_f)
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if max_bubble is None or _max_bubble < max_bubble:
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max_bubble = _max_bubble
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schedule = _schedule
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end_time = _end_time
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if only_run_time:
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return max_bubble + expected_time
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max_bubble / (expected_time + max_bubble)
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local_order = [[] for _ in range(self.n_stage)]
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comm_id = {}
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comm_id_counter = 0
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post_validation_time = 0
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for i in range(self.n_stage - 1, -1, -1):
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pv_id = min(2 * (self.n_stage - 1 - i), self.n_micro - 1)
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post_validation_time = max(
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post_validation_time, end_time[self.get_id(0, 0, i, pv_id)] - self.fbw_cost[0] - self.c_cost
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)
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# post_validation_time = 0
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for it in ["RECV_", "SEND_", ""]:
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if i == 0 and it == "SEND_":
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continue
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if i == self.n_stage - 1 and it == "RECV_":
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continue
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# stage_ = i - 1 if it == "RECV_" else i
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stage_ = i
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local_order[stage_].append(
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ScheduledNode(
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type=it + "POST_VALIDATION",
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chunk=0,
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stage=stage_,
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minibatch=0,
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start_time=post_validation_time,
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completion_time=post_validation_time,
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)
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)
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comm_id[local_order[stage_][-1]] = comm_id_counter
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comm_id_counter += 1
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for i in range(self.n_stage):
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for _cat_, _chunk_, _micro_ in schedule[i]:
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complete_time = end_time[self.get_id(_cat_, _chunk_, i, _micro_)]
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local_order[i].append(
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ScheduledNode(
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type="FBW"[_cat_],
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chunk=_chunk_ if _cat_ == 0 else 1 - _chunk_,
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stage=i,
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minibatch=_micro_,
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start_time=complete_time - self.fbw_cost[_cat_],
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completion_time=complete_time,
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)
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)
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if _cat_ == 2: # no communication for W
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continue
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cat_str = "FORWARD" if _cat_ == 0 else "BACKWARD"
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def communicate(send_recv, stage_):
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# noinspection PyTypeChecker
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local_order[stage_].append(
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ScheduledNode(
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type=send_recv + cat_str,
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chunk=_chunk_ if _cat_ == 0 else 1 - _chunk_,
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stage=stage_,
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minibatch=_micro_,
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start_time=complete_time,
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completion_time=complete_time,
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)
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)
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comm_id[local_order[stage_][-1]] = comm_id_counter
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if _chunk_ == 1 and i > 0:
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communicate("SEND_", i)
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communicate("RECV_", i - 1)
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if _chunk_ == 0 and i < self.n_stage - 1:
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communicate("SEND_", i)
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communicate("RECV_", i + 1)
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comm_id_counter += 1
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for rank in range(self.n_stage):
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# For nodes with the same timestamp on the same stage, communication will be prioritized.
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def even_breaker(x: ScheduledNode):
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# Compute nodes are always delayed.
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if x.type in ["F", "B", "W"]:
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return comm_id_counter
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# For comm nodes, order by their unique comm id
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return comm_id[x]
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local_order[rank] = list(sorted(local_order[rank], key=lambda x: (x.start_time, even_breaker(x))))
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# If a recv with intersects with previous computation, reorder them so that recv
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# is executed before computation and hence can be overlapped.
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for i in range(len(local_order[rank])):
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if (
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i > 0
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and local_order[rank][i - 1].type in {"F", "B", "W"}
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and local_order[rank][i].type.startswith("RECV")
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and "POST_VALIDATION" not in local_order[rank][i].type
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and local_order[rank][i].start_time <= local_order[rank][i - 1].completion_time
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):
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local_order[rank][i], local_order[rank][i - 1] = local_order[rank][i - 1], local_order[rank][i]
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local_order_with_rollback = [[] for _ in range(self.n_stage)]
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for rank in range(self.n_stage):
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rollback_comm = set()
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if rank > 0:
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for node in local_order[rank - 1]:
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if node.type == "POST_VALIDATION":
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break
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if node.type == "SEND_FORWARD":
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assert node.chunk == 0
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rollback_comm.add(node.minibatch)
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for node in local_order[rank]:
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if node.type == "RECV_FORWARD" and node.chunk == 0 and node.minibatch in rollback_comm:
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rollback = True
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rollback_comm.remove(node.minibatch)
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else:
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rollback = False
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local_order_with_rollback[rank].append(
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ScheduledNode(
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type=node.type,
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chunk=node.chunk,
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stage=node.stage,
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minibatch=node.minibatch,
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|
start_time=node.start_time,
|
|
completion_time=node.completion_time,
|
|
rollback=rollback,
|
|
)
|
|
)
|
|
assert len(rollback_comm) == 0
|
|
|
|
return local_order_with_rollback
|