polished output format for communication profiler and pcie profiler (#404)

fixed typing error
pull/411/head
HELSON 2022-03-14 16:07:45 +08:00 committed by GitHub
parent aaead33cfe
commit dfd0363f68
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3 changed files with 74 additions and 44 deletions

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@ -6,20 +6,25 @@ from torch.autograd.profiler import profile
import torch.distributed as dist
from torch.distributed import ReduceOp
from colossalai.utils import get_current_device
from .prof_utils import BaseProfiler, _format_time, _format_memory, _format_bandwith
from .prof_utils import BaseProfiler, _format_time, _format_memory, _format_bandwidth
from typing import List, Optional
def _get_code_location(depth: int):
ret = ""
length = len(inspect.stack())
for i in range(3, min(length, depth + 1)):
ret = []
length = min(len(inspect.stack()), depth + 1)
for i in range(3, length):
upper_frame = inspect.stack()[i]
function_name = inspect.stack()[i - 1].function
info = upper_frame.filename + "(" + str(upper_frame.lineno) + "): " + function_name + "\n"
ret += info
ret.append(upper_frame.filename)
ret.append('(')
ret.append(str(upper_frame.lineno))
ret.append('): ')
ret.append(function_name)
if i != length - 1:
ret.append('\n')
return ret
return ''.join(ret)
torch_all_reduce = dist.all_reduce
@ -100,8 +105,9 @@ class CommProfiler(BaseProfiler):
def result_list(self, sep: str = "\n"):
res = []
def append(s: str):
res.append(s)
def append(s: str = None):
if s is not None:
res.append(s)
res.append(sep)
if self.warn_flag:
@ -110,19 +116,26 @@ class CommProfiler(BaseProfiler):
append("Collective communication profiling result:")
append("total cuda time: {}".format(_format_time(self.total_cuda_time)))
append("average bandwith: {}".format(_format_bandwith(self.total_comm_vol, self.total_cuda_time)))
append("average bandwidth: {}".format(_format_bandwidth(self.total_comm_vol, self.total_cuda_time)))
append("total number of calls: {}".format(self.total_count))
append("All events:\n----------------------------------------")
append("All events:")
seperation = '-' * 74
row_format = '{:^10}' + '{:^12}' * 2 + '{:^16}' + '{:^12}' * 2
append(seperation)
append(row_format.format('Location', 'GPU time', 'Percentage', 'Comm volume', 'Bandwidth', 'Num of calls'))
append(seperation)
show_list = sorted(self.ops_record.items(), key=lambda kv: -kv[1].self_cuda_time)
for location, event in show_list:
append(location)
append("self cuda time: {}".format(_format_time(event.self_cuda_time)))
append("{:.1f}% of total communication time".format(event.self_cuda_time / self.total_cuda_time * 100.0))
append("self communication volme: {}".format(_format_memory(event.self_comm_vol)))
append("average bandwith: {}".format(_format_bandwith(event.self_comm_vol, event.self_cuda_time)))
append("number of calls: {}".format(event.self_count))
append("----------------------------------------")
append(
row_format.format('', _format_time(event.self_cuda_time),
'{:.1f}%'.format(event.self_cuda_time / self.total_cuda_time * 100.0),
_format_memory(event.self_comm_vol),
_format_bandwidth(event.self_comm_vol, event.self_cuda_time), event.self_count))
append()
return ''.join(res)

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@ -1,6 +1,6 @@
from pathlib import Path
from torch.autograd.profiler import profile
from .prof_utils import BaseProfiler, _format_time, _format_memory, _format_bandwith
from .prof_utils import BaseProfiler, _format_time, _format_memory, _format_bandwidth
from typing import List
@ -24,6 +24,7 @@ def _reduce_location(locations: List[str]) -> str:
for lo in locations:
ret.append(lo)
ret.append("\n")
ret = ret[:-1]
return ''.join(ret)
@ -48,18 +49,23 @@ class PcieProfiler(BaseProfiler):
TODO: Merge pcie profiler into communication profiler
"""
def __init__(self,
dtype: str = "fp32",
depth: int = 1,
total_count: int = 0,
total_pcie_vol: int = 0,
total_cuda_time: int = 0):
def __init__(self, dtype: str = "fp32", depth: int = 1):
super().__init__(profiler_name="Pcie", priority=10)
self.depth = depth
self.data_size = _get_size(dtype)
self.total_count = total_count
self.total_pcie_vol = total_pcie_vol
self.total_cuda_time = total_cuda_time
self.h2d_count = 0
self.h2d_time = 0
self.d2h_count = 0
self.d2h_time = 0
self.ops_record = dict()
self.profiler = None
def reset(self):
self.h2d_count = 0
self.h2d_time = 0
self.d2h_count = 0
self.d2h_time = 0
self.ops_record = dict()
self.profiler = None
@ -81,17 +87,20 @@ class PcieProfiler(BaseProfiler):
for event in events:
if event.name == "aten::copy_":
t_shape = event.input_shapes[0]
if len(t_shape) == 0 or event.cuda_time_total == 0:
if len(t_shape) == 0 or event.cuda_time_total == 0 or len(event.stack) == 0:
continue
current_comm_event = PcieEvent(1, self.data_size * _get_numel(t_shape), event.cuda_time_total)
self.total_count += current_comm_event.count
self.total_pcie_vol += current_comm_event.pcie_vol
self.total_cuda_time += current_comm_event.cuda_time
code_location = _reduce_location(event.stack[:self.depth])
if code_location in self.ops_record:
self.ops_record[code_location].add(current_comm_event)
else:
self.ops_record[code_location] = current_comm_event
elif 'Memcpy HtoD' in event.name:
self.h2d_count += 1
self.h2d_time += event.cuda_time_total
elif 'Memcpy DtoH' in event.name:
self.d2h_count += 1
self.d2h_time += event.cuda_time_total
self.profiler = None
@ -108,24 +117,32 @@ class PcieProfiler(BaseProfiler):
def result_list(self, sep: str = "\n"):
res = []
def append(s: str):
res.append(s)
def append(s: str = None):
if s is not None:
res.append(s)
res.append(sep)
append("Pcie profiling result:")
append("total cuda time: {}".format(_format_time(self.total_cuda_time)))
append("average bandwith: {}".format(_format_bandwith(self.total_pcie_vol, self.total_cuda_time)))
append("total number of calls: {}".format(self.total_count))
append("All events:\n----------------------------------------")
append("time of data transmission (CPU -> GPU): {}".format(_format_time(self.h2d_time)))
append("number of transmission (CPU -> GPU): {}".format(self.h2d_count))
append("time of data transmission (GPU -> CPU): {}".format(_format_time(self.d2h_time)))
append("number of transmission (GPU -> CPU): {}".format(self.d2h_count))
append("Possible data transmission events in PCIE:")
seperation = '-' * 62
row_format = '{:^10}' + '{:^12}' + '{:^16}' + '{:^12}' * 2
append(seperation)
append(row_format.format('Location', 'GPU time', 'Trans volume', 'Bandwidth', 'Num of calls'))
append(seperation)
show_list = sorted(self.ops_record.items(), key=lambda kv: -kv[1].cuda_time)
for location, event in show_list:
append(location)
append("cuda time: {}".format(_format_time(event.cuda_time)))
append("{:.1f}% of total pcie time".format(event.cuda_time / self.total_cuda_time * 100.0))
append("pcie volme: {}".format(_format_memory(event.pcie_vol)))
append("average bandwith: {}".format(_format_bandwith(event.pcie_vol, event.cuda_time)))
append("number of calls: {}".format(event.count))
append("----------------------------------------")
append(
row_format.format('', _format_time(event.cuda_time), _format_memory(event.pcie_vol),
_format_bandwidth(event.pcie_vol, event.cuda_time), event.count))
append()
return ''.join(res)

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@ -32,7 +32,7 @@ def _format_memory(nbytes):
return str(nbytes) + ' B'
def _format_bandwith(volme: float or int, time_us: int):
def _format_bandwidth(volme: float or int, time_us: int):
sec_div_mb = (1000.0 / 1024.0)**2
mb_per_sec = volme / time_us * sec_div_mb