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186 lines
6.7 KiB
Python
186 lines
6.7 KiB
Python
# Copyright (C) 2021 - 2024 Advanced Micro Devices, Inc. All rights reserved.
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in
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# all copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
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# THE SOFTWARE.
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"""Timing utilities."""
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import collections
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import perflib
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import logging
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from dataclasses import dataclass, field
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from pathlib import Path as path
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from typing import List
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from typing import Set
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from numpy import ceil
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@dataclass
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class Timer:
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bench: str = ""
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accutest: str = ""
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active_tests_tokens: Set[bytes] = field(default_factory=set)
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lib: List[str] = field(default_factory=list)
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out: List[str] = field(default_factory=list)
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device: int = 0
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ntrial: int = 10
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mp_size: int = 1
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mp_exec: str = ""
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ingrid: List[int] = field(default_factory=list)
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outgrid: List[int] = field(default_factory=list)
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ngpus: int = 1
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verbose: bool = False
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timeout: float = 0
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sequence: int = None
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hipskip: bool = True
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def run_cases(self, generator):
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bench = path(self.bench)
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if not bench.is_file():
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raise RuntimeError(f"Unable to find (dyna-)bench: {self.bench}")
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if self.mp_size > 1 and self.mp_exec == None:
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raise RuntimeError(f"Unable to find mpi executable {self.bench}")
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failed_tokens = []
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# get a list of powers of two less or equal than the number of requested resources,
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# to be used for scalability experiments
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gpu_list_pow2 = lambda n: [
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2**i for i in range(int(ceil(n**0.5)) + 1) if 2**i <= n
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]
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total_prob_count = 0
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no_accutest_prob_count = 0
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for prob in generator.generate_problems():
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total_prob_count += 1
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n_resources = 1
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# scalability for single-proc multi-GPU:
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if self.ngpus > 1 and self.mp_size == 1:
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n_resources = self.ngpus
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# scalability for single-proc using 1-GPU per MPI:
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elif self.mp_size > 1 and self.ngpus == 1:
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n_resources = self.mp_size
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scaling = prob.meta.get('scaling')
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if scaling != None:
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list_of_gpus = gpu_list_pow2(n_resources)
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else:
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list_of_gpus = [n_resources]
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ws_factor = 1
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for g in list_of_gpus:
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token, seconds, success, __, __ = perflib.bench.run(
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self.bench,
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tuple([ws_factor * l for l in prob.length]),
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direction=prob.direction,
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real=prob.real,
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inplace=prob.inplace,
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precision=prob.precision,
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nbatch=prob.nbatch,
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mp_size=g if self.mp_size > 1 else 1,
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mp_exec=self.mp_exec,
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ingrid=self.ingrid,
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outgrid=self.outgrid,
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ngpus=g if self.ngpus > 1 else 1,
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ntrial=self.ntrial,
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device=self.device,
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libraries=self.lib,
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verbose=self.verbose,
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timeout=self.timeout,
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sequence=self.sequence,
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skiphip=self.hipskip,
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scalability=(scaling != None))
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if scaling == 'weak':
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ws_factor *= 2
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if success:
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for idx, vals in enumerate(seconds):
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out = path(self.out[idx])
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logging.info("output: " + str(out))
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meta = {'title': prob.tag}
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meta.update(prob.meta)
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perflib.utils.write_dat(out, token, seconds[idx], meta)
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else:
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failed_tokens.append(token)
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if self.active_tests_tokens and token.encode(
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) not in self.active_tests_tokens:
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no_accutest_prob_count += 1
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logging.info(f'No accuracy test coverage for: ' + token)
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if no_accutest_prob_count > 0:
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print('\t')
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logging.warning(
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str(no_accutest_prob_count) + f' out of ' +
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str(total_prob_count) +
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f' problems do not have accuracy coverage.' +
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f' Refer to rocfft-perf.log for details.')
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return failed_tokens
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@dataclass
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class GroupedTimer:
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bench: str = ""
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accutest: str = ""
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active_tests_tokens: Set[bytes] = field(default_factory=set)
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lib: List[str] = field(default_factory=list)
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out: List[str] = field(default_factory=list)
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device: int = 0
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ntrial: int = 10
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mp_size: int = 1
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mp_exec: str = ""
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ngpus: int = 1
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verbose: bool = False
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timeout: float = 0
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def run_cases(self, generator):
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failed_tokens = []
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all_problems = collections.defaultdict(list)
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for problem in generator.generate_problems():
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all_problems[problem.tag].append(problem)
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total_problems = sum([len(v) for v in all_problems.values()])
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print(
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f'Timing {total_problems} problems in {len(all_problems)} groups')
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if self.accutest:
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accutest = path(self.accutest)
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if not accutest.is_file():
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raise RuntimeError(
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f'Unable to find accuracy test: {self.accutest}')
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self.active_tests_tokens = perflib.accutest.get_active_tests_tokens(
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accutest)
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for i, (tag, problems) in enumerate(all_problems.items()):
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print(
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f'\n{tag} (group {i} of {len(all_problems)}): {len(problems)} problems'
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)
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timer = Timer(**self.__dict__)
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timer.out = [path(x) / (tag + '.dat') for x in self.out]
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failed_tokens += timer.run_cases(
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perflib.generators.VerbatimGenerator(problems))
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return failed_tokens
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