cfallows-amd
c45e20f325
Profile mode: Fix roofline plots for datatypes that have peakVALU only. Check for highest roofline to plot the bandwidth lines to proper height, don't rely on existence of peakMFMA for every datatype. Analyze mode: Add roofline-data-type option for viewing pdfs in standalone gui. Default is same as profile mode, FP32. --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com>
466 regels
18 KiB
Python
466 regels
18 KiB
Python
##############################################################################bl
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# MIT License
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#
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# Copyright (c) 2021 - 2025 Advanced Micro Devices, Inc. All Rights Reserved.
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#
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# Permission is hereby granted, free of charge, to any person obtaining a copy
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# of this software and associated documentation files (the "Software"), to deal
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# in the Software without restriction, including without limitation the rights
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# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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# copies of the Software, and to permit persons to whom the Software is
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# furnished to do so, subject to the following conditions:
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#
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# The above copyright notice and this permission notice shall be included in all
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# copies or substantial portions of the Software.
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#
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# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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# SOFTWARE.
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##############################################################################el
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import os
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import time
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from abc import ABC, abstractmethod
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from collections import OrderedDict
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from pathlib import Path
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import numpy as np
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import pandas as pd
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import plotly.graph_objects as go
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from dash import dcc, html
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from utils.logger import console_debug, console_error, console_log, demarcate
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from utils.roofline_calc import (
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MFMA_DATATYPES,
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PEAK_OPS_DATATYPES,
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SUPPORTED_DATATYPES,
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calc_ai,
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constuct_roof,
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)
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from utils.utils import mibench
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SYMBOLS = [0, 1, 2, 3, 4, 5, 13, 17, 18, 20]
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class Roofline:
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def __init__(self, args, mspec, run_parameters=None):
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self.__args = args
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self.__mspec = mspec
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self.__run_parameters = (
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run_parameters
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if run_parameters
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else {
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"workload_dir": None, # in some cases (i.e. --specs) path will not be given
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"device_id": 0,
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"sort_type": "kernels",
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"mem_level": "ALL",
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"include_kernel_names": False,
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"is_standalone": False,
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"roofline_data_type": ["FP32"],
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}
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)
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self.__ai_data = None
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self.__ceiling_data = None
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self.__figure = go.Figure()
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# Set roofline run parameters from args
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if hasattr(self.__args, "path") and not run_parameters:
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self.__run_parameters["workload_dir"] = self.__args.path
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if hasattr(self.__args, "roof_only") and self.__args.roof_only == True:
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self.__run_parameters["is_standalone"] = True
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if hasattr(self.__args, "kernel_names") and self.__args.kernel_names == True:
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self.__run_parameters["include_kernel_names"] = True
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if hasattr(self.__args, "mem_level") and self.__args.mem_level != "ALL":
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self.__run_parameters["mem_level"] = self.__args.mem_level
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if hasattr(self.__args, "sort") and self.__args.sort != "ALL":
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self.__run_parameters["sort_type"] = self.__args.sort
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if hasattr(
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self.__args, "roofline_data_type"
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) and self.__args.roofline_data_type != ["FP32"]:
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self.__run_parameters["roofline_data_type"] = self.__args.roofline_data_type
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self.validate_parameters()
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def validate_parameters(self):
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if self.__run_parameters["include_kernel_names"] and (
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not self.__run_parameters["is_standalone"]
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):
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console_error("--roof-only is required for --kernel-names")
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def roof_setup(self):
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# set default workload path if not specified
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if self.__run_parameters["workload_dir"] == str(
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Path(os.getcwd()).joinpath("workloads")
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):
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self.__run_parameters["workload_dir"] = str(
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Path(self.__run_parameters["workload_dir"]).joinpath(
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self.__args.name,
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self.__mspec.gpu_model,
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)
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)
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# create new directory for roofline if it doesn't exist
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if not Path(self.__run_parameters["workload_dir"]).is_dir():
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os.makedirs(self.__run_parameters["workload_dir"])
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@demarcate
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def empirical_roofline(
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self,
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ret_df,
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):
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"""Generate a set of empirical roofline plots given a directory containing required profiling and benchmarking data"""
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if (
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not isinstance(self.__run_parameters["workload_dir"], list)
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and self.__run_parameters["workload_dir"] != None
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):
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self.roof_setup()
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# Create arithmetic intensity data that will populate the roofline model
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console_debug("roofline", "Path: %s" % self.__run_parameters["workload_dir"])
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self.__ai_data = calc_ai(self.__mspec, self.__run_parameters["sort_type"], ret_df)
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msg = "AI at each mem level:"
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for i in self.__ai_data:
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msg += "\n\t%s -> %s" % (i, self.__ai_data[i])
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console_debug(msg)
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# Generate a roofline figure for the datatypes
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ops_figure = flops_figure = None
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ops_dt_list = flops_dt_list = ""
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for dt in self.__run_parameters["roofline_data_type"]:
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# Do not generate a roofline figure if the datatype is not supported on this gpu_arch
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if not str(dt) in SUPPORTED_DATATYPES[self.__mspec.gpu_arch]:
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console_error(
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"{} is not a supported datatype for roofline profiling on {}".format(
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str(dt), self.__mspec.gpu_model
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),
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exit=False,
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)
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continue
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ops_flops = "Ops" if (str(dt[:1]) == "I") else "Flops"
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if ops_flops == "Ops":
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if ops_figure:
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ops_combo_figure = self.generate_plot(
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dtype=str(dt),
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fig=ops_figure,
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)
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ops_figure = ops_combo_figure
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else:
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ops_figure = self.generate_plot(dtype=str(dt))
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ops_dt_list += "_" + str(dt)
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if ops_flops == "Flops":
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if flops_figure:
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flops_combo_figure = self.generate_plot(
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dtype=str(dt),
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fig=flops_figure,
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)
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flops_figure = flops_combo_figure
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else:
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flops_figure = self.generate_plot(dtype=str(dt))
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flops_dt_list += "_" + str(dt)
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# Create a legend and distinct kernel markers. This can be saved, optionally
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self.__figure = go.Figure(
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go.Scatter(
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mode="markers",
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x=[0] * 10,
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y=self.__ai_data["kernelNames"],
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marker_symbol=SYMBOLS,
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marker_size=15,
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)
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)
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self.__figure.update_layout(
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title="Kernel Names and Markers",
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margin=dict(b=0, r=0),
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xaxis_range=[-1, 1],
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xaxis_side="top",
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yaxis_side="right",
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height=400,
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width=1000,
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)
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self.__figure.update_xaxes(dtick=1)
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# Output will be different depending on interaction type:
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# Save PDFs if we're in "standalone roofline" mode, otherwise return HTML to be used in GUI output
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if self.__run_parameters["is_standalone"]:
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dev_id = str(self.__run_parameters["device_id"])
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# Re-save to remove loading MathJax pop up
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for i in range(2):
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if ops_figure:
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ops_figure.write_image(
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self.__run_parameters["workload_dir"]
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+ "/empirRoof_gpu-{}{}.pdf".format(dev_id, ops_dt_list)
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)
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if flops_figure:
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flops_figure.write_image(
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self.__run_parameters["workload_dir"]
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+ "/empirRoof_gpu-{}{}.pdf".format(dev_id, flops_dt_list)
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)
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# only save a legend if kernel_names option is toggled
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if self.__run_parameters["include_kernel_names"]:
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self.__figure.write_image(
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self.__run_parameters["workload_dir"] + "/kernelName_legend.pdf"
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)
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time.sleep(1)
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console_log("roofline", "Empirical Roofline PDFs saved!")
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else:
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if ops_figure:
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ops_graph = html.Div(
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className="float-child",
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children=[
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html.H3(children="Empirical Roofline Analysis (Ops)"),
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dcc.Graph(figure=ops_figure),
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],
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)
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else:
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ops_graph = None
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if flops_figure:
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flops_graph = html.Div(
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className="float-child",
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children=[
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html.H3(children="Empirical Roofline Analysis (Flops)"),
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dcc.Graph(figure=flops_figure),
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],
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)
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else:
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flops_graph = None
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return html.Section(
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id="roofline",
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children=[
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html.Div(
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className="float-container",
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children=[
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ops_graph,
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flops_graph,
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],
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)
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],
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)
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@demarcate
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def generate_plot(self, dtype, fig=None) -> go.Figure():
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"""Create graph object from ai_data (coordinate points) and ceiling_data (peak FLOP and BW) data."""
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if fig is None:
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fig = go.Figure()
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plot_mode = "lines+text" if self.__run_parameters["is_standalone"] else "lines"
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self.__ceiling_data = constuct_roof(
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roofline_parameters=self.__run_parameters,
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dtype=dtype,
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)
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console_debug("roofline", "Ceiling data:\n%s" % self.__ceiling_data)
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#######################
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# Plot ceilings
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#######################
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if self.__run_parameters["mem_level"] == "ALL":
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cache_hierarchy = ["HBM", "L2", "L1", "LDS"]
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else:
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cache_hierarchy = self.__run_parameters["mem_level"]
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# Plot peak BW ceiling(s)
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for cache_level in cache_hierarchy:
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fig.add_trace(
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go.Scatter(
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x=self.__ceiling_data[cache_level.lower()][0],
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y=self.__ceiling_data[cache_level.lower()][1],
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name="{}-{}".format(cache_level, dtype),
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mode=plot_mode,
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hovertemplate="<b>%{text}</b>",
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text=[
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"{} GB/s".format(
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to_int(self.__ceiling_data[cache_level.lower()][2])
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),
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(
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None
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if self.__run_parameters["is_standalone"]
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else "{} GB/s".format(
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to_int(self.__ceiling_data[cache_level.lower()][2])
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)
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),
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],
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textposition="top right",
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)
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)
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ops_flops = "OP" if (dtype[:1] == "I") else "FLOP"
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# Plot peak VALU ceiling
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if dtype in PEAK_OPS_DATATYPES:
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fig.add_trace(
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go.Scatter(
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x=self.__ceiling_data["valu"][0],
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y=self.__ceiling_data["valu"][1],
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name="Peak VALU-{}".format(dtype),
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mode=plot_mode,
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hovertemplate="<b>%{text}</b>",
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text=[
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(
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None
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if self.__run_parameters["is_standalone"]
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else "{} G{}/s".format(
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to_int(self.__ceiling_data["valu"][2]), ops_flops
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)
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),
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"{} G{}/s".format(
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to_int(self.__ceiling_data["valu"][2]), ops_flops
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),
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],
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textposition="top left",
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)
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)
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# Plot peak MFMA ceiling
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if dtype in MFMA_DATATYPES:
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fig.add_trace(
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go.Scatter(
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x=self.__ceiling_data["mfma"][0],
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y=self.__ceiling_data["mfma"][1],
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name="Peak MFMA-{}".format(dtype),
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mode=plot_mode,
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hovertemplate="<b>%{text}</b>",
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text=[
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(
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None
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if self.__run_parameters["is_standalone"]
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else "{} G{}/s".format(
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to_int(self.__ceiling_data["mfma"][2]), ops_flops
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)
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),
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"{} G{}/s".format(
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to_int(self.__ceiling_data["mfma"][2]), ops_flops
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),
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],
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textposition="top left",
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)
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)
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#######################
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# Plot Application AI
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#######################
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# Plot the arithmetic intensity points for each cache level
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if ops_flops == "FLOP":
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fig.add_trace(
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go.Scatter(
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x=self.__ai_data["ai_l1"][0],
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y=self.__ai_data["ai_l1"][1],
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name=dtype + "_ai_l1",
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mode="markers",
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marker_symbol=(
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SYMBOLS if self.__run_parameters["include_kernel_names"] else None
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),
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)
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)
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fig.add_trace(
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go.Scatter(
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x=self.__ai_data["ai_l2"][0],
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y=self.__ai_data["ai_l2"][1],
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name=dtype + "_ai_l2",
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mode="markers",
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marker_symbol=(
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SYMBOLS if self.__run_parameters["include_kernel_names"] else None
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),
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)
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)
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fig.add_trace(
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go.Scatter(
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x=self.__ai_data["ai_hbm"][0],
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y=self.__ai_data["ai_hbm"][1],
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name=dtype + "_ai_hbm",
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mode="markers",
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marker_symbol=(
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SYMBOLS if self.__run_parameters["include_kernel_names"] else None
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),
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)
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)
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# Set layout
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fig.update_layout(
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xaxis_title="Arithmetic Intensity (FLOPs/Byte)",
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yaxis_title="Performance (GFLOP/sec)",
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hovermode="x unified",
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margin=dict(l=50, r=50, b=50, t=50, pad=4),
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)
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else:
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# Set layout
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fig.update_layout(
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xaxis_title="Bandwidth (GB/sec)",
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yaxis_title="Performance (GOP/sec)",
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hovermode="x unified",
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margin=dict(l=50, r=50, b=50, t=50, pad=4),
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)
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fig.update_xaxes(type="log", autorange=True)
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fig.update_yaxes(type="log", autorange=True)
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return fig
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@demarcate
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def standalone_roofline(self):
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if (
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not isinstance(self.__run_parameters["workload_dir"], list)
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and self.__run_parameters["workload_dir"] != None
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):
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self.roof_setup()
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# Change vL1D to a interpretable str, if required
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if "vL1D" in self.__run_parameters["mem_level"]:
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self.__run_parameters["mem_level"].remove("vL1D")
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self.__run_parameters["mem_level"].append("L1")
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app_path = str(
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Path(self.__run_parameters["workload_dir"]).joinpath("pmc_perf.csv")
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)
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roofline_exists = Path(app_path).is_file()
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if not roofline_exists:
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console_error("roofline", "{} does not exist".format(app_path))
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t_df = OrderedDict()
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t_df["pmc_perf"] = pd.read_csv(app_path)
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self.empirical_roofline(ret_df=t_df)
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@abstractmethod
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def profile(self):
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if self.__args.roof_only:
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# check for roofline benchmark
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console_log(
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"roofline", "Checking for roofline.csv in " + str(self.__args.path)
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)
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roof_path = str(Path(self.__args.path).joinpath("roofline.csv"))
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if not Path(roof_path).is_file():
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mibench(self.__args, self.__mspec)
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# check for profiling data
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console_log(
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"roofline", "Checking for pmc_perf.csv in " + str(self.__args.path)
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)
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app_path = str(Path(self.__args.path).joinpath("pmc_perf.csv"))
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if not Path(app_path).is_file():
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console_log("roofline", "pmc_perf.csv not found. Generating...")
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if not self.__args.remaining:
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console_error(
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"profiling"
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"An <app_cmd> is required to run.\rrocprof-compute profile -n test -- <app_cmd>"
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)
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# TODO: Add an equivelent of characterize_app() to run profiling directly out of this module
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elif self.__args.no_roof:
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console_log("roofline", "Skipping roofline.")
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else:
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mibench(self.__args, self.__mspec)
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# NB: Currently the post_prossesing() method is the only one being used by rocprofiler-compute,
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# we include pre_processing() and profile() methods for those who wish to borrow the roofline module
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@abstractmethod
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def post_processing(self):
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if self.__run_parameters["is_standalone"]:
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self.standalone_roofline()
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|
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def to_int(a):
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if str(type(a)) == "<class 'NoneType'>":
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return np.nan
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else:
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return int(a)
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