Add roofline cli_generate_plot method (#737)
Add option to print out roofline plot in terminal using plotext. Takes in one datatype and returns the str from plot.build() which contains the visual plot of roofline analysis for said datatype. --------- Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com>
This commit is contained in:
cfallows-amd
GitHub
+219
-1
@@ -30,10 +30,17 @@ 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 plotext as plt
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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.logger import (
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console_debug,
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console_error,
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console_log,
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console_warning,
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demarcate,
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)
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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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@@ -408,6 +415,217 @@ class Roofline:
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return fig
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@demarcate
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def cli_generate_plot(self, dtype):
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"""
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Plot CLI mode roofline analysis in terminal using plotext
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:param dtype: The datatype to be profiled
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:type method: str
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:return: Build the current figure using plot.build(), or None if datatype is not valid for the architecture
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:rtype: str or None
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"""
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console_debug("roofline", "Generating roofline plot for CLI")
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if not (str(dtype) 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(dtype), self.__mspec.gpu_model
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),
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exit=False,
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)
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return
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# Check proper datatype input - takes single str
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if not isinstance(dtype, str):
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console_error("Unsupported datatype input - must be str")
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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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color_scheme = {
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"HBM": "blue+",
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"L2": "green+",
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"L1": "red+",
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"LDS": "orange+",
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"VALU": "white",
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"MFMA": "magenta+",
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}
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kernel_markers = {
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0: "star",
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1: "cross",
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2: "sd",
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3: "shamrock",
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4: "at",
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5: "atom",
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}
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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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self.__ai_data = calc_ai(self.__mspec, self.__run_parameters["sort_type"], t_df)
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plt.clf()
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plt.plotsize(plt.tw(), plt.th())
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ops_flops = "OP" if (dtype[:1] == "I") else "FLOP" # For printing purposes
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# Plot BW Lines
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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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for cache_level in cache_hierarchy:
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plt.plot(
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self.__ceiling_data[cache_level.lower()][0],
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self.__ceiling_data[cache_level.lower()][1],
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label="{}-{}".format(cache_level, dtype),
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marker="braille",
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color=color_scheme[cache_level],
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)
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plt.text(
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str(round(self.__ceiling_data[cache_level.lower()][2])) + " GB/s",
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x=self.__ceiling_data[cache_level.lower()][0][0],
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y=self.__ceiling_data[cache_level.lower()][1][0],
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background="black",
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color="white",
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alignment="left",
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)
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console_debug(
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"roofline",
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cache_level
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+ ": [{},{}], [{},{}], {}".format(
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str(self.__ceiling_data[cache_level.lower()][0][0]),
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str(self.__ceiling_data[cache_level.lower()][0][1]),
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str(self.__ceiling_data[cache_level.lower()][1][0]),
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str(self.__ceiling_data[cache_level.lower()][1][1]),
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str(self.__ceiling_data[cache_level.lower()][2]),
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),
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)
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# Plot VALU and MFMA Peak
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if dtype in PEAK_OPS_DATATYPES:
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plt.plot(
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self.__ceiling_data["valu"][0],
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[
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self.__ceiling_data["valu"][1][0] - 0.1,
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self.__ceiling_data["valu"][1][1] - 0.1,
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],
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label="Peak VALU-{}".format(dtype),
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marker="braille",
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color=color_scheme["VALU"],
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)
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plt.text(
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str(round(self.__ceiling_data["valu"][2])) + " G{}/s".format(ops_flops),
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x=self.__ceiling_data["valu"][0][1] - 800,
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y=self.__ceiling_data["valu"][1][1],
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background="black",
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color="white",
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alignment="right",
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)
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console_debug(
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"roofline",
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"VALU: [{},{}], [{},{}], {}".format(
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str(self.__ceiling_data["valu"][0][0]),
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str(self.__ceiling_data["valu"][0][1]),
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str(self.__ceiling_data["valu"][1][0]),
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str(self.__ceiling_data["valu"][1][1]),
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str(self.__ceiling_data["valu"][2]),
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),
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)
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else:
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console_warning("No PEAK measurement available for {}".format(dtype))
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if dtype in MFMA_DATATYPES:
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plt.plot(
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self.__ceiling_data["mfma"][0],
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[
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self.__ceiling_data["mfma"][1][0] - 0.1,
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self.__ceiling_data["mfma"][1][1] - 0.1,
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],
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label="Peak MFMA-{}".format(dtype),
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marker="braille",
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color=color_scheme["MFMA"],
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)
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plt.text(
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str(round(self.__ceiling_data["mfma"][2])) + " G{}/s".format(ops_flops),
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x=self.__ceiling_data["mfma"][0][1] - 800,
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y=self.__ceiling_data["mfma"][1][1],
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background="black",
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color="white",
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alignment="right",
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)
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console_debug(
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"roofline",
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"MFMA: [{},{}], [{},{}], {}".format(
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str(self.__ceiling_data["mfma"][0][0]),
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str(self.__ceiling_data["mfma"][0][1]),
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str(self.__ceiling_data["mfma"][1][0]),
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str(self.__ceiling_data["mfma"][1][1]),
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str(self.__ceiling_data["mfma"][2]),
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),
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)
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else:
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console_warning("No MFMA measurement available for {}".format(dtype))
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# Plot Application AI
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for cache_level in cache_hierarchy:
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key = "ai_" + cache_level.lower()
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if key in self.__ai_data:
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for i in range(len(self.__ai_data["kernelNames"])):
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# Zero intensity level means no data reported for this cache level
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if self.__ai_data[key][0][i] > 0 and self.__ai_data[key][1][i] > 0:
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plt.plot(
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[self.__ai_data[key][0][i]],
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[self.__ai_data[key][1][i]],
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label="AI_"
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+ cache_level
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+ "_{}".format(self.__ai_data["kernelNames"][i]),
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color=color_scheme[cache_level],
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marker=kernel_markers[i % len(kernel_markers)],
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)
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console_debug(
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"roofline",
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"AI_{}: {}, {}".format(
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self.__ai_data["kernelNames"][i],
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self.__ai_data[key][0][i],
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self.__ai_data[key][1][i],
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),
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)
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plt.xlabel("Arithmetic Intensity ({})s/Byte)".format(ops_flops))
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plt.ylabel("Performance (GFLOP/sec)")
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plt.title("Roofline ({})".format(dtype))
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# Canvas config
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plt.theme("pro")
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plt.xscale("log")
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plt.yscale("log")
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# Build figure
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# Print plot using `plt._utility.write(self.cli_generate_plot(dtype))`
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return plt.build()
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@demarcate
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def standalone_roofline(self):
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if (
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