# Copyright 2021 Max Planck Institute for Software Systems, and # National University of Singapore # # Permission is hereby granted, free of charge, to any person obtaining # a copy of this software and associated documentation files (the # "Software"), to deal in the Software without restriction, including # without limitation the rights to use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the Software, and to # permit persons to whom the Software is furnished to do so, subject to # the following conditions: # # The above copyright notice and this permission notice shall be # included in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY # CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """This is the top-level module of the SimBricks orchestration framework that users interact with.""" import argparse import asyncio import fnmatch import importlib import importlib.util import json import os import pickle import signal import sys from simbricks.orchestration import exectools from simbricks.orchestration.experiment import experiment_environment from simbricks.orchestration.simulation import base as sim_base from simbricks.orchestration.instantiation import base as inst_base from simbricks.orchestration.runtime_new import runs from simbricks.orchestration.runtime_new import command_executor from simbricks.orchestration.runtime_new import simulation_executor def parse_args() -> argparse.Namespace: parser = argparse.ArgumentParser() # general arguments for experiments parser.add_argument( "experiments", metavar="EXP", type=str, nargs="+", help="Python modules to load the experiments from", ) parser.add_argument( "--list", action="store_const", const=True, default=False, help="List available experiment names", ) parser.add_argument( "--filter", metavar="PATTERN", type=str, nargs="+", help="Only run experiments matching the given Unix shell style patterns", ) parser.add_argument( "--pickled", action="store_const", const=True, default=False, help="Interpret experiment modules as pickled runs instead of .py files", ) parser.add_argument( "--runs", metavar="N", type=int, default=1, help="Number of repetition of each experiment", ) parser.add_argument( "--firstrun", metavar="N", type=int, default=1, help="ID for first run" ) parser.add_argument( "--force", action="store_const", const=True, default=False, help="Run experiments even if output already exists (overwrites output)", ) parser.add_argument( "--verbose", action="store_const", const=True, default=False, help="Verbose output, for example, print component simulators' output", ) parser.add_argument( "--pcap", action="store_const", const=True, default=False, help="Dump pcap file (if supported by component simulator)", ) parser.add_argument( "--profile-int", metavar="S", type=int, default=None, help="Enable periodic sigusr1 to each simulator every S seconds.", ) # arguments for the experiment environment g_env = parser.add_argument_group("Environment") g_env.add_argument( "--repo", metavar="DIR", type=str, default=os.path.dirname(__file__) + "/..", help="SimBricks repository directory", ) g_env.add_argument( "--workdir", metavar="DIR", type=str, default="./out/", help="Work directory base", ) g_env.add_argument( "--outdir", metavar="DIR", type=str, default="./out/", help="Output directory base", ) g_env.add_argument( "--cpdir", metavar="DIR", type=str, default="./out/", help="Checkpoint directory base", ) g_env.add_argument( "--hosts", metavar="JSON_FILE", type=str, default=None, help="List of hosts to use (json)", ) g_env.add_argument( "--shmdir", metavar="DIR", type=str, default=None, help="Shared memory directory base (workdir if not set)", ) # arguments for the parallel runtime g_par = parser.add_argument_group("Parallel Runtime") g_par.add_argument( "--parallel", dest="runtime", action="store_const", const="parallel", default="sequential", help="Use parallel instead of sequential runtime", ) g_par.add_argument( "--cores", metavar="N", type=int, default=len(os.sched_getaffinity(0)), help="Number of cores to use for parallel runs", ) g_par.add_argument( "--mem", metavar="N", type=int, default=None, help="Memory limit for parallel runs (in MB)", ) # arguments for the slurm runtime g_slurm = parser.add_argument_group("Slurm Runtime") g_slurm.add_argument( "--slurm", dest="runtime", action="store_const", const="slurm", default="sequential", help="Use slurm instead of sequential runtime", ) g_slurm.add_argument( "--slurmdir", metavar="DIR", type=str, default="./slurm/", help="Slurm communication directory", ) # arguments for the distributed runtime g_dist = parser.add_argument_group("Distributed Runtime") g_dist.add_argument( "--dist", dest="runtime", action="store_const", const="dist", default="sequential", help="Use sequential distributed runtime instead of local", ) g_dist.add_argument( "--auto-dist", action="store_const", const=True, default=False, help="Automatically distribute non-distributed experiments", ) g_dist.add_argument( "--proxy-type", metavar="TYPE", type=str, default="sockets", help="Proxy type to use (sockets,rdma) for auto distribution", ) return parser.parse_args() def load_executors(path: str) -> list[exectools.Executor]: """Load hosts list from json file and return list of executors.""" with open(path, "r", encoding="utf-8") as f: hosts = json.load(f) exs = [] for h in hosts: if h["type"] == "local": ex = command_executor.LocalExecutor() elif h["type"] == "remote": ex = command_executor.RemoteExecutor(h["host"], h["workdir"]) if "ssh_args" in h: ex.ssh_extra_args += h["ssh_args"] if "scp_args" in h: ex.scp_extra_args += h["scp_args"] else: raise RuntimeError('invalid host type "' + h["type"] + '"') ex.ip = h["ip"] exs.append(ex) return exs def warn_multi_exec(executors: list[command_executor.Executor]): if len(executors) > 1: print( "Warning: multiple hosts specified, only using first one for now", file=sys.stderr, ) def add_exp( simulation: sim_base.Simulation, rt: runs.base.Runtime, run_number: int, prereq: runs.base.Run | None, create_cp: bool, restore_cp: bool, args: argparse.Namespace, ) -> inst_base.InstantiationEnvironment: outpath = f"{args.outdir}/{simulation.name}-{run_number}.json" if os.path.exists(outpath) and not args.force: print(f"skip {e.name} run {run_number}") return None workdir = f"{args.workdir}/{simulation.name}/{run_number}" cpdir = f"{args.cpdir}/{simulation.name}/0" if args.shmdir is not None: shmdir = f"{args.shmdir}/{simulation.name}/{run_number}" shm_base = "" # TODO if args.shmdir is not None: env.shm_base = os.path.abspath(shmdir) # TODO: user can specify output base output_base = "" tmp_sim_files = "" # TODO inst_env = inst_base.InstantiationEnvironment( repo_path="", workdir=workdir, cpdir=cpdir, create_cp=create_cp, restore_cp=restore_cp, shm_base=shm_base, output_base=output_base, tmp_simulation_files=tmp_sim_files, ) run = runs.base.Run( simulation=simulation, inst_env=inst_env, prereq=prereq, ) rt.add_run(run) return run def main(): args = parse_args() if args.hosts is None: executors = [command_executor.LocalExecutor()] else: executors = load_executors(args.hosts) # initialize runtime if args.runtime == "parallel": warn_multi_exec(executors) rt = runs.LocalParallelRuntime( cores=args.cores, mem=args.mem, verbose=args.verbose, executor=executors[0] ) elif args.runtime == "slurm": rt = runs.SlurmRuntime(args.slurmdir, args, verbose=args.verbose) elif args.runtime == "dist": rt = runs.DistributedSimpleRuntime(executors, verbose=args.verbose) else: warn_multi_exec(executors) rt = runs.LocalSimpleRuntime(verbose=args.verbose, executor=executors[0]) if args.profile_int: rt.enable_profiler(args.profile_int) # load experiments if not args.pickled: # default: load python modules with experiments simulations: list[sim_base.Simulation] = [] for path in args.experiments: modname, _ = os.path.splitext(os.path.basename(path)) class ExperimentModuleLoadError(Exception): pass spec = importlib.util.spec_from_file_location(modname, path) if spec is None: raise ExperimentModuleLoadError("spec is None") mod = importlib.util.module_from_spec(spec) if spec.loader is None: raise ExperimentModuleLoadError("spec.loader is None") spec.loader.exec_module(mod) simulations += mod.experiments if args.list: for sim in simulations: print(sim.name) sys.exit(0) for sim in simulations: # TODO: do we want a sitributed SImulation class? --> probably not, choose slightly different abstraction if args.auto_dist and not isinstance(sim, exps.DistributedExperiment): sim = runtime.auto_dist(sim, executors, args.proxy_type) # apply filter if any specified if (args.filter) and (len(args.filter) > 0): match = False for f in args.filter: match = fnmatch.fnmatch(sim.name, f) if match: break if not match: continue # if this is an experiment with a checkpoint we might have to create # it # TODO: what to do / how to handel checkpointing if sim.checkpoint: prereq = add_exp(e, rt, 0, None, True, False, args) else: prereq = None for run in range(args.firstrun, args.firstrun + args.runs): add_exp(e, rt, run, prereq, False, sim.checkpoint, args) else: # otherwise load pickled run object for path in args.experiments: with open(path, "rb") as f: rt.add_run(pickle.load(f)) # register interrupt handler signal.signal(signal.SIGINT, lambda *_: rt.interrupt()) # invoke runtime to run experiments asyncio.run(rt.start()) if __name__ == "__main__": main()