# Copyright 2019 PerfKitBenchmarker Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Runs stress-ng. From the stress-ng ubuntu documentation: stress-ng will stress test a computer system in various selectable ways. It was designed to exercise various physical subsystems of a computer as well as the various operating system kernel interfaces. stress-ng also has a wide range of CPU specific stress tests that exercise floating point, integer, bit manipulation and control flow. stress-ng manpage: http://manpages.ubuntu.com/manpages/xenial/man1/stress-ng.1.html """ import logging from absl import flags import numpy from perfkitbenchmarker import configs from perfkitbenchmarker import sample FLAGS = flags.FLAGS BENCHMARK_NAME = 'stress_ng' BENCHMARK_CONFIG = """ stress_ng: description: Runs stress-ng vm_groups: default: vm_spec: *default_dual_core disk_spec: *default_50_gb """ VALID_CPU_METHODS = frozenset({ 'all', 'ackermann', 'bitops', 'callfunc', 'cdouble', 'cfloat', 'clongdouble', 'correlate', 'crc16', 'decimal32', 'decimal64', 'decimal128', 'dither', 'djb2a', 'double', 'euler', 'explog', 'fft', 'fibonacci', 'float', 'fnv1a', 'gamma', 'gcd', 'gray', 'hamming', 'hanoi', 'hyperbolic', 'idct', 'int128', 'int64', 'int32', 'int16', 'int8', 'int128float', 'int128double', 'int128longdouble', 'int128decimal32', 'int128decimal64', 'int128decimal128', 'int64float', 'int64double', 'int64longdouble', 'int32float', 'int32double', 'int32longdouble', 'jenkin', 'jmp', 'ln2', 'longdouble', 'loop', 'matrixprod', 'nsqrt', 'omega', 'parity', 'phi', 'pi', 'pjw', 'prime', 'psi', 'queens', 'rand', 'rand48', 'rgb', 'sdbm', 'sieve', 'sqrt', 'trig', 'union', 'zeta', }) VALID_STRESSORS = frozenset({ 'affinity', 'af-alg', 'aio', 'aio-linux', 'apparmor', 'bigheap', 'brk', 'bsearch', 'cache', 'chdir', 'chmod', 'clock', 'clone', 'context', 'cpu', 'cpu-online', 'crypt', 'daemon', 'dentry', 'dir', 'dup', 'epoll', 'eventfd', 'exec', 'fallocate', 'fault', 'fcntl', 'fiemap', 'fifo', 'filename', 'flock', 'fork', 'fp-error', 'fstat', 'futex', 'get', 'getrandom', 'getdent', 'handle', 'hdd', 'heapsort', 'hsearch', 'icache', 'iosync', 'inotify', 'itimer', 'kcmp', 'key', 'kill', 'klog', 'lease', 'link', 'lockbus', 'lockf', 'longjmp', 'lsearch', 'malloc', 'matrix', 'membarrier', 'memcpy', 'memfd', 'mergesort', 'mincore', 'mknod', 'mlock', 'mmap', 'mmapfork', 'mmapmany', 'mremap', 'msg', 'mq', 'nice', 'null', 'numa', 'oom-pipe', 'open', 'personality', 'pipe', 'poll', 'procfs', 'pthread', 'ptrace', 'qsort', 'quota', 'rdrand', 'readahead', 'remap-file-pages', 'rename', 'rlimit', 'seccomp', 'seek', 'sem-posix', 'sem-sysv', 'shm-posix', 'shm-sysv', 'sendfile', 'sigfd', 'sigfpe', 'sigpending', 'sigq', 'sigsegv', 'sigsuspend', 'sleep', 'socket', 'socket-fd', 'socket-pair', 'spawn', 'splice', 'stack', 'str', 'stream', 'switch', 'symlink', 'sync-file', 'sysinfo', 'sysfs', 'tee', 'timer', 'timerfd', 'tsc', 'tsearch', 'udp', 'udp-flood', 'unshare', 'urandom', 'userfaultfd', 'utime', 'vecmath', 'vfork', 'vm', 'vm-rw', 'vm-splice', 'wait', 'wcs', 'xattr', 'yield', 'zero', 'zlib', 'zombie', }) CPU_SUITE = frozenset({ 'af-alg', 'bsearch', 'context', 'cpu', 'cpu-online', 'crypt', 'fp-error', 'getrandom', 'heapsort', 'hsearch', 'longjmp', 'lsearch', 'matrix', 'mergesort', 'numa', 'qsort', 'rdrand', 'str', 'stream', 'tsc', 'tsearch', 'vecmath', 'wcs', 'zlib', }) CPU_CACHE_SUITE = frozenset({ 'bsearch', 'cache', 'heapsort', 'hsearch', 'icache', 'lockbus', 'lsearch', 'malloc', 'matrix', 'membarrier', 'memcpy', 'mergesort', 'qsort', 'str', 'stream', 'tsearch', 'vecmath', 'wcs', 'zlib', }) MEMORY_SUITE = frozenset({ 'bsearch', 'context', 'heapsort', 'hsearch', 'lockbus', 'lsearch', 'malloc', 'matrix', 'membarrier', 'memcpy', 'memfd', 'mergesort', 'mincore', 'null', 'numa', 'oom-pipe', 'pipe', 'qsort', 'stack', 'str', 'stream', 'tsearch', 'vm', 'vm-rw', 'wcs', 'zero', 'zlib', }) # Run the stressors that are each part of all of the compute related stress-ng # classes: cpu, cpu-cache, and memory. DEFAULT_STRESSORS = sorted( CPU_SUITE.intersection(CPU_CACHE_SUITE).intersection(MEMORY_SUITE) ) flags.DEFINE_integer( 'stress_ng_duration', 10, 'Number of seconds to run the test.' ) flags.DEFINE_boolean( 'stress_ng_calc_geomean', True, 'Whether to calculate geomean or not.' ) flags.DEFINE_list( 'stress_ng_custom_stressors', DEFAULT_STRESSORS, 'List of stressors to run against. Default combines cpu,' 'cpu-cache, and memory suites', ) flags.DEFINE_list( 'stress_ng_cpu_methods', [], 'List of cpu methods to run with. By default none are ran.', ) ALL_WORKLOADS = ['small', 'medium', 'large'] flags.DEFINE_list( 'stress_ng_thread_workloads', ['large'], 'List of threads sizes to run against. Options are' 'small (1 thread total), medium (1 thread per 2 cpus), and ' 'large (1 thread per cpu).', ) flags.register_validator( 'stress_ng_thread_workloads', lambda workloads: workloads and set(workloads).issubset(ALL_WORKLOADS), ) def _GeoMeanOverflow(iterable): """Returns the geometric mean. See https://en.wikipedia.org/wiki/Geometric_mean#Relationship_with_logarithms Args: iterable: a list of positive floats to take the geometric mean of. Returns: The geometric mean of the list. """ a = numpy.log(iterable) return numpy.exp(a.sum() / len(a)) def StressngCustomStressorsValidator(stressors): """Returns whether or not the list of custom stressors is valid.""" return VALID_STRESSORS.issuperset(set(stressors)) def StressngCpuMethodsValidator(cpu_methods): """Returns whether or not the list of cpu methods is valid.""" return 'all_cpu_methods' in cpu_methods or VALID_CPU_METHODS.issuperset( set(cpu_methods) ) flags.register_validator( 'stress_ng_custom_stressors', StressngCustomStressorsValidator ) flags.register_validator('stress_ng_cpu_methods', StressngCpuMethodsValidator) def GetConfig(user_config): return configs.LoadConfig(BENCHMARK_CONFIG, user_config, BENCHMARK_NAME) def Prepare(benchmark_spec): """Installs stress-ng on the target vm. Args: benchmark_spec: The benchmark specification. Contains all data that is required to run the benchmark. """ vm = benchmark_spec.vms[0] vm.InstallPackages('stress-ng') def _ParseStressngResult( metadata, output, cpu_method=None ) -> sample.Sample | None: """Returns stress-ng data as a sample. Sample output eg: stress-ng: info: [2566] dispatching hogs: 2 context stress-ng: info: [2566] successful run completed in 5.00s stress-ng: info: [2566] stressor bogo ops real time usr time sys time bogo ops/s bogo ops/s stress-ng: info: [2566] (secs) (secs) (secs) (real time) (usr+sys time) stress-ng: info: [2566] context 22429 5.00 5.49 4.48 4485.82 2249.65 Args: metadata: metadata of the sample. output: the output of the stress-ng benchmark. cpu_method: an optional flag for the cpu method for the cpu stressor. """ output_list = output.splitlines() output_matrix = [i.split() for i in output_list] if len(output_matrix) < 5: logging.error('output is missing') return None while output_matrix[-1][-1] == 'stressor)': output_matrix.pop() assert output_matrix[-3][-4] == 'bogo' and output_matrix[-3][-3] == 'ops/s' assert output_matrix[-2][-4] == '(real' and output_matrix[-2][-3] == 'time)' line = output_matrix[-1] name = line[3] value = float(line[-2]) # parse bogo ops/s (real time) if name == 'cpu' and cpu_method: return sample.Sample( metric=cpu_method, value=value, unit='bogus_ops_sec', # bogus operations per second metadata=metadata, ) return sample.Sample( metric=name, value=value, unit='bogus_ops_sec', # bogus operations per second metadata=metadata, ) def _RunWorkload(vm, num_threads): """Runs stress-ng on the target vm. Args: vm: The target vm to run on. num_threads: Number of instances of stressors to launch. Returns: A list of sample.Sample objects. """ metadata = { 'duration_sec': FLAGS.stress_ng_duration, 'threads': num_threads, } samples = [] values_to_geomean_list = [] stressors = FLAGS.stress_ng_custom_stressors for stressor in stressors: cmd = ( 'stress-ng --{stressor} {numthreads} --metrics-brief ' '-t {duration}'.format( stressor=stressor, numthreads=num_threads, duration=FLAGS.stress_ng_duration, ) ) stdout, stderr = vm.RemoteCommand(cmd) stdout = stderr stressng_sample = _ParseStressngResult(metadata, stdout) if stressng_sample: samples.append(stressng_sample) values_to_geomean_list.append(stressng_sample.value) cpu_methods = ( VALID_CPU_METHODS if 'all_cpu_methods' in FLAGS.stress_ng_cpu_methods else FLAGS.stress_ng_cpu_methods ) for cpu_method in cpu_methods: cmd = ( 'stress-ng --cpu {numthreads} --metrics-brief ' '-t {duration} --cpu-method {cpu_method}'.format( numthreads=num_threads, duration=FLAGS.stress_ng_duration, cpu_method=cpu_method, ) ) stdout, _ = vm.RemoteCommand(cmd) stressng_sample = _ParseStressngResult(metadata, stdout, cpu_method) if stressng_sample: samples.append(stressng_sample) values_to_geomean_list.append(stressng_sample.value) if FLAGS.stress_ng_calc_geomean: geomean_metadata = metadata.copy() geomean_metadata['stressors'] = stressors # True only if each stressor provided a value geomean_metadata['valid_run'] = len(values_to_geomean_list) == len( stressors ) + len(cpu_methods) geomean_sample = sample.Sample( metric='STRESS_NG_GEOMEAN', value=_GeoMeanOverflow(values_to_geomean_list), unit='bogus_ops_sec', metadata=geomean_metadata, ) samples.append(geomean_sample) return samples def Run(benchmark_spec): """Runs stress-ng on the target vm. Args: benchmark_spec: The benchmark specification. Contains all data that is required to run the benchmark. Returns: A list of sample.Sample objects. """ vm = benchmark_spec.vms[0] samples = [] for workload in FLAGS.stress_ng_thread_workloads: if workload == 'small': samples.extend(_RunWorkload(vm, 1)) elif workload == 'medium': samples.extend(_RunWorkload(vm, vm.NumCpusForBenchmark() / 2)) elif workload == 'large': samples.extend(_RunWorkload(vm, vm.NumCpusForBenchmark())) return samples def Cleanup(benchmark_spec): """Cleans up stress-ng from the target vm. Args: benchmark_spec: The benchmark specification. Contains all data that is required to run the benchmark. """ vm = benchmark_spec.vms[0] vm.Uninstall('stress-ng')