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workloads: add meabo
Add automation for meabo micro-benchmark.
This commit is contained in:
sergei Trofimov
committed by
Marc Bonnici
Marc Bonnici
parent
f19ca4c00c
commit
b8343e545b
313
wa/workloads/meabo/__init__.py
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313
wa/workloads/meabo/__init__.py
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# Copyright 2016 ARM Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import os
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import re
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from wa import Workload, Parameter, Executable, ConfigError, WorkloadError
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from wa.utils.exec_control import once
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from wa.utils.types import list_of_ints
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phase_start_regex = re.compile(r"Starting phase\s+(?P<phase>\d+)")
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counter_value_regex = re.compile(r"Thread\s+(?P<thread>\d+)\s+(?P<name>\w+)\svalue\s+\=\s+(?P<value>\d+)")
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duration_regex = re.compile(r"Phase\s+(?P<phase>\d+)[\s\w\(\)]+\:\s+(?P<duration>\d+)")
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class Meabo(Workload):
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name = 'meabo'
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description = '''
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A multi-phased multi-purpose micro-benchmark. The micro-benchmark is
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composed of 10 phases that perform various generic calculations (from
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memory to compute intensive).
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It is a highly configurable tool which can be used for energy efficiency
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studies, ARM big.LITTLE Linux scheduler analysis and DVFS studies. It can
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be used for other benchmarking as well.
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All floating-point calculations are double-precision.
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| Phase 1: Floating-point & integer computations with good data locality
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| Phase 2: Vector multiplication & addition, 1 level of indirection in 1
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| source vector
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| Phase 3: Vector scalar addition and reductions
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| Phase 4: Vector addition
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| Phase 5: Vector addition, 1 level of indirection in both source vectors
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| Phase 6: Sparse matrix-vector multiplication
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| Phase 7: Linked-list traversal
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| Phase 8: Electrostatic force calculations
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| Phase 9: Palindrome calculations
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| Phase 10: Random memory accesses
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For more details and benchmark source, see:
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https://github.com/ARM-software/meabo
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.. note:: current implementation of automation relies on the executable to
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be either statically linked or for all necessary depencies to be
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installed on the target.
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'''
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parameters = [
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Parameter(
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'array_size',
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kind=int,
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description='''
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Size of arrays used in Phases 1, 2, 3, 4 and 5.
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''',
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constraint=lambda x: x > 0,
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default=1048576,
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),
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Parameter(
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'nrow',
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kind=int,
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description='''
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Number of rows for the sparse matrix used in Phase 6.
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''',
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constraint=lambda x: x > 0,
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default=16384,
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),
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Parameter(
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'ncol',
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kind=int,
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description='''
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Number of columns for the sparse matrix used in Phase 6.
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''',
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constraint=lambda x: x > 0,
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default=16384,
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),
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Parameter(
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'num_iterations',
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kind=int,
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description='''
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Number of iterations that core loop is executed.
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''',
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constraint=lambda x: x > 0,
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default=1000,
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),
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Parameter(
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'block_size',
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kind=int,
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description='''
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Block size used in Phase 1.
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''',
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constraint=lambda x: x > 0,
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default=8,
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),
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Parameter(
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'num_cpus',
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kind=int,
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description='''
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Number of total CPUs that the application can bind threads to.
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''',
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constraint=lambda x: x > 0,
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default=6,
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),
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Parameter(
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'per_phase_cpu_ids',
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kind=list_of_ints,
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description='''
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Sets which cores each phase is run on.
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''',
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constraint=lambda x: all(v>=-1 for v in x),
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default=[-1]*10,
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),
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Parameter(
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'num_hwcntrs',
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kind=int,
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description='''
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Only available when using PAPI. Controls how many hardware counters
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PAPI will get access to.
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''',
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constraint=lambda x: x >= 0,
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default=7,
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),
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Parameter(
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'run_phases',
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kind=list_of_ints,
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description='''
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Controls which phases to run.
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''',
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constraint=lambda x: all(0 < v <=10 for v in x),
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default=range(1, 11),
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),
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Parameter(
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'num_threads',
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kind=int,
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description='''
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Controls how many threads the application will be using.
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''',
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constraint=lambda x: x >= 0,
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default=0,
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),
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Parameter(
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'bind_to_cpu_set',
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kind=int,
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description='''
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Controls whether threads will be bound to a core set, or each
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individual thread will be bound to a specific core within the core
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set.
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''',
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constraint=lambda x: 0 <= x <= 1,
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default=1,
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),
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Parameter(
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'llist_size',
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kind=int,
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description='''
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Size of the linked list available for each thread.
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''',
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constraint=lambda x: x > 0,
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default=16777216,
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),
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Parameter(
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'num_particles',
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kind=int,
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description='''
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Number of particles used in Phase 8.
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''',
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constraint=lambda x: x > 0,
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default=1048576,
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),
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Parameter(
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'num_palindromes',
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kind=int,
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description='''
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Number of palindromes used in Phase 9.
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''',
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constraint=lambda x: x > 0,
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default=1024,
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),
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Parameter(
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'num_randomloc',
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kind=int,
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description='''
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Number of random memory locations accessed in Phase 10.
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''',
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constraint=lambda x: x > 0,
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default=2097152,
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),
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Parameter(
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'run_timeout',
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kind=int,
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description="""
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Timeout for execution of the test.
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""",
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constraint=lambda x: x > 0,
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default=60 * 45,
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),
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]
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options = [
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('-s', 'array_size'),
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('-B', 'bind_to_cpu_set'),
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('-b', 'block_size'),
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('-l', 'llist_size'),
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('-c', 'ncol'),
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('-r', 'nrow'),
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('-C', 'num_cpus'),
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('-H', 'num_hwcntrs'),
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('-i', 'num_iterations'),
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('-x', 'num_palindromes'),
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('-p', 'num_particles'),
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('-R', 'num_randomloc'),
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('-T', 'num_threads'),
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]
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def validate(self):
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if len(self.run_phases) != len(self.per_phase_cpu_ids):
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msg = "Number of phases doesn't match the number of CPU mappings"
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raise ConfigError(msg)
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def initialize(self, context):
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self._install_executable(context)
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self._build_command()
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def setup(self, context):
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self.output = None
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def run(self, context):
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self.output = self.target.execute(self.command,
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timeout=self.run_timeout)
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def update_output(self, context):
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if self.output is None:
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self.logger.warning('Did not collect output')
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return
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outfile = os.path.join(context.output_directory, 'meabo-output.txt')
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with open(outfile, 'wb') as wfh:
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wfh.write(self.output)
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context.add_artifact('meabo-output', outfile, kind='raw')
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cur_phase = 0
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for line in self.output.split('\n'):
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line = line.strip()
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match = phase_start_regex.search(line)
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if match:
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cur_phase = match.group('phase')
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match = counter_value_regex.search(line)
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if match:
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if cur_phase == 0:
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msg = 'Matched thread performance counters outside of phase!'
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raise WorkloadError(msg)
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name = 'phase_{}_thread_{}_{}'.format(cur_phase,
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match.group('thread'),
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match.group('name'))
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context.result.add_metric(name, int(match.group('value')))
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match = duration_regex.search(line)
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if match:
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context.add_metric("phase_{}_duration".format(match.group('phase')),
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int(match.group('duration')), units="ns")
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def finalize(self, context):
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self._uninstall_executable()
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def _build_command(self):
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self.command = self.target_exe
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# We need to calculate the phase mask
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phase_mask = 0
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for phase in self.run_phases:
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phase_mask |= 1<<(phase-1)
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self.command += ' -P {:d}'.format(phase_mask)
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# Set the CPU ids for each phase we are running
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for phase, cpu_id in zip(self.run_phases, self.per_phase_cpu_ids):
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self.command += ' -{0:1d} {1:d}'.format(phase, cpu_id)
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# We need to append extra arguments to the command based on the
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# parameters passed in from the agenda.
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for option, param_name in self.options:
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param_value = getattr(self, param_name, None)
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if param_value is not None:
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self.command += ' {} {}'.format(option, param_value)
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@once
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def _install_executable(self, context):
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resource = Executable(self, self.target.abi, 'meabo')
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host_exe = context.resolver.get(resource)
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Meabo.target_exe = self.target.install(host_exe)
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@once
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def _uninstall_executable(self):
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self.target.uninstall_executable(self.target_exe)
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