mirror of https://github.com/hpcaitech/ColossalAI
100 lines
2.9 KiB
Python
100 lines
2.9 KiB
Python
from dataclasses import dataclass
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from typing import List
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import torch
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from colossalai.context.singleton_meta import SingletonMeta
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from colossalai.fx.profiler import calculate_fwd_out, calculate_fwd_tmp
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from .region import Region
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@dataclass
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class NodeInfo:
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node_id: int = 0
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runtime_fwd_mem: float = 0
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runtime_bwd_mem: float = 0
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class NvDevicePower:
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"""
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NVIDIA GPU computing performance (TFLOPs).
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"""
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RTX3080_FP16 = 70
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RTX3080_FP32 = 34.1
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RTX3090_FP16 = 71
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RTX3090_FP32 = 35.7
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V100_FP16 = 31.4
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V100_FP32 = 15.7
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A100_FP16 = 78
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A100_FP32 = 19.5
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class GlobalRuntimeInfo(metaclass=SingletonMeta):
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def __init__(self):
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self.h2d_stream = torch.cuda.Stream()
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self.d2h_stream = torch.cuda.Stream()
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self.fwd_prefetch_event_map = {}
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self.bwd_prefetch_event_map = {}
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self.region_list = []
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def compute_act_peak_mem(region_list: List[Region]) -> float:
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act_peak_mem = 0
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runtime_mem = 0
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# forward
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for region in region_list:
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for node in region.nodes:
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runtime_mem = runtime_mem + \
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calculate_fwd_tmp(node) + calculate_fwd_out(node)
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act_peak_mem = max(runtime_mem, act_peak_mem)
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# backward
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bwd_deps = {}
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for region in region_list.__reversed__():
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for node in region.nodes.__reversed__():
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runtime_mem -= calculate_fwd_out(node)
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runtime_mem = runtime_mem + \
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node.meta['bwd_mem_tmp'] + node.meta['bwd_mem_out']
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act_peak_mem = max(runtime_mem, act_peak_mem)
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runtime_mem = runtime_mem - \
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node.meta['bwd_mem_tmp'] - calculate_fwd_tmp(node)
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# free bwd_mem_out
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bwd_deps[node] = len(node.all_input_nodes)
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for user_node in node.users:
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if user_node in bwd_deps:
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bwd_deps[user_node] -= 1
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if bwd_deps[user_node] <= 0:
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runtime_mem -= user_node.meta['bwd_mem_out']
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return act_peak_mem
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def compute_max_param_mem(region_list: List[Region]) -> float:
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return max(region.param_size for region in region_list)
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def compute_total_param_mem(region_list: List[Region]) -> float:
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return sum(region.param_size for region in region_list if region.r_id <= region.shared_rid)
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def requires_upload_p_in_fwd(shared_reg: Region):
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return (shared_reg.r_id >= shared_reg.shared_rid) or (shared_reg.r_id < shared_reg.shared_rid
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and shared_reg.need_offload)
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def requires_release_p_in_bwd(shared_reg: Region):
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return (shared_reg.r_id >= shared_reg.shared_rid) or (shared_reg.r_id < shared_reg.shared_rid
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and shared_reg.need_offload)
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def requires_offload_g_in_bwd(region: Region):
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return region.param_size and (region.r_id <= region.shared_rid)
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