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rocm-systems/projects/rocprofiler-compute/src/rocprof_compute_tui/analysis_tui.py
T
xuchen-amd b6a7d72212 TUI: Kernel Selection (#769)
[ROCm/rocprofiler-compute commit: 9ddee8de2e]
2025-08-01 11:31:43 -04:00

148 lines
5.6 KiB
Python

##############################################################################bl
# MIT License
#
# Copyright (c) 2025 Advanced Micro Devices, Inc. All Rights Reserved.
#
# 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.
##############################################################################el
import copy
from pathlib import Path
from rocprof_compute_analyze.analysis_base import OmniAnalyze_Base
from rocprof_compute_tui.utils.tui_utils import (
get_top_kernels_and_dispatch_ids,
process_panels_to_dataframes,
)
from utils import file_io, parser, schema
from utils.kernel_name_shortener import kernel_name_shortener
from utils.logger import console_error, demarcate
class tui_analysis(OmniAnalyze_Base):
def __init__(self, args, supported_archs, path):
super().__init__(args, supported_archs)
self.path = str(path)
self.arch = None
self.raw_dfs = {}
self.kernel_dfs = {}
# -----------------------
# Required child methods
# -----------------------
@demarcate
def pre_processing(self):
self._profiling_config = file_io.load_profiling_config(self.path)
self._runs = self.initalize_runs()
if self.get_args().random_port:
console_error("--gui flag is required to enable --random-port")
self._runs[self.path].raw_pmc = file_io.create_df_pmc(
self.path,
self.get_args().nodes,
self.get_args().spatial_multiplexing,
self.get_args().kernel_verbose,
self.get_args().verbose,
self._profiling_config,
)
if self.get_args().spatial_multiplexing:
self._runs[self.path].raw_pmc = self.spatial_multiplex_merge_counters(
self._runs[self.path].raw_pmc
)
file_io.create_df_kernel_top_stats(
df_in=self._runs[self.path].raw_pmc,
raw_data_dir=self.path,
filter_gpu_ids=self._runs[self.path].filter_gpu_ids,
filter_dispatch_ids=self._runs[self.path].filter_dispatch_ids,
filter_nodes=self._runs[self.path].filter_nodes,
time_unit=self.get_args().time_unit,
max_stat_num=self.get_args().max_stat_num,
kernel_verbose=self.get_args().kernel_verbose,
)
kernel_name_shortener(
self._runs[self.path].raw_pmc, self.get_args().kernel_verbose
)
# 1. load top kernel
parser.load_kernel_top(
workload=self._runs[self.path], dir=self.path, args=self.get_args()
)
# 2. load table data for each kernel
self.raw_dfs.clear()
for idx in self._runs[self.path].raw_pmc.index:
kernel_df = self._runs[self.path].raw_pmc.loc[[idx]]
kernel_name = kernel_df.pmc_perf["Kernel_Name"].loc[idx]
this_dfs = copy.deepcopy(self._runs[self.path].dfs)
parser.eval_metric(
this_dfs,
self._runs[self.path].dfs_type,
self._runs[self.path].sys_info.iloc[0],
kernel_df,
self.get_args().debug,
self._profiling_config,
)
self.raw_dfs[kernel_name] = this_dfs
def initalize_runs(self, normalization_filter=None):
sysinfo_path = Path(self.path)
sys_info = file_io.load_sys_info(sysinfo_path.joinpath("sysinfo.csv"))
self.arch = sys_info.iloc[0]["gpu_arch"]
args = self.get_args()
self.generate_configs(
self.arch,
args.config_dir,
args.list_stats,
args.filter_metrics,
sys_info.iloc[0],
)
self.load_options(normalization_filter)
w = schema.Workload()
w.sys_info = file_io.load_sys_info(sysinfo_path.joinpath("sysinfo.csv"))
mspec = self.get_socs()[self.arch]._mspec
if args.specs_correction:
w.sys_info = parser.correct_sys_info(mspec, args.specs_correction)
w.avail_ips = w.sys_info["ip_blocks"].item().split("|")
w.dfs = copy.deepcopy(self._arch_configs[self.arch].dfs)
w.dfs_type = self._arch_configs[self.arch].dfs_type
self._runs[self.path] = w
return self._runs
@demarcate
def run_kernel_analysis(self):
self.kernel_dfs.clear()
for kernel_name, df in self.raw_dfs.items():
self.kernel_dfs[kernel_name] = process_panels_to_dataframes(
self.get_args(), df, self._arch_configs[self.arch], roof_plot=None
)
return self.kernel_dfs
@demarcate
def run_top_kernel(self):
return get_top_kernels_and_dispatch_ids(self._runs)