def _nsight(self, cmd, profile_from_start):
if profile_from_start:
profile_cmd = "nsys nvprof -o tmp.qdrep {}".format(cmd)
else:
profile_cmd = "nsys nvprof --profile-from-start=off -o tmp.qdrep {}".format(
cmd)
return system.run_command(profile_cmd)
def launch(benchmark_script, benchmark_script_args, with_nvprof=False):
"""
If with_nvprof is True, it will launch the following command firstly to
get the gpu_time:
nvprof python benchmark_script benchmark_script_args
Then the normal testing command will be launched:
python benchmark_script benchmark_script_args
"""
cmd = "{} {} {}".format(sys.executable, benchmark_script,
" ".join(benchmark_script_args))
if with_nvprof:
stdout, exit_code = _nvprof(cmd)
if exit_code == 0:
parse_status, gpu_time = _parse_nvprof_logs(stdout.split("\n"))
else:
parse_status = False
if parse_status:
return gpu_time
else:
print("Runing Error:\n {}".format(stdout))
else:
stdout, exit_code = system.run_command(cmd)
print(stdout)
if exit_code != 0:
sys.exit(exit_code)
return 0.0
def is_ampere_gpu():
stdout, exit_code = system.run_command("nvidia-smi -L")
if exit_code == 0:
gpu_list = stdout.split("\n")
if len(gpu_list) >= 1:
#print(gpu_list[0])
# GPU 0: NVIDIA A100-SXM4-40GB (UUID: xxxx)
return gpu_list[0].find("A100") > 0
return False
def launch(benchmark_script,
benchmark_script_args,
task="speed",
repeat=1,
sync_interval=80,
with_nvprof=False,
profile_from_start=True):
"""
If with_nvprof is True, it will launch the following command firstly to
get the gpu_time:
nvprof python benchmark_script benchmark_script_args
Then the normal testing command will be launched:
python benchmark_script benchmark_script_args
"""
if with_nvprof:
if task == "speed" and not profile_from_start:
_set_args(benchmark_script_args, "--profiler", "nvprof")
elif task == "scheduling":
_set_args(benchmark_script_args, "--profiler", "nvprof_nvtx")
cmd = "{} {} {}".format(sys.executable, benchmark_script,
" ".join(benchmark_script_args))
if with_nvprof:
if task == "speed":
if is_ampere_gpu():
runner = NsightRunner()
else:
runner = NvprofRunner()
gpu_time = runner.run(cmd, profile_from_start)
_set_args(benchmark_script_args, "--profiler", "none")
return gpu_time
elif task == "scheduling":
runner = NsightRunnerForDynamicScheduling()
scheduling_time_dict = runner.run(cmd, 5, repeat + 1,
sync_interval)
_set_args(benchmark_script_args, "--profiler", "none")
return scheduling_time_dict
else:
stdout, exit_code = system.run_command(cmd)
print(stdout)
if exit_code != 0:
sys.exit(exit_code)
return 0.0
def _nvprof(self, cmd, profile_from_start):
if profile_from_start:
profile_cmd = "nvprof {}".format(cmd)
else:
profile_cmd = "nvprof --profile-from-start off {}".format(cmd)
return system.run_command(profile_cmd)
def _nsight_nvtx(self, cmd):
return system.run_command(
"nsys profile -t cuda,nvtx --stats true -o tmp.qdrep --force-overwrite true {}"
.format(cmd))
def _nvprof(cmd):
return system.run_command("nvprof {}".format(cmd))
def _nvprof(self, cmd):
return system.run_command(
"nvprof --profile-from-start off {}".format(cmd))
def _nsight(self, cmd):
return system.run_command(
"nsys nvprof --profile-from-start=off -o tmp.qdrep {}".format(cmd))
