Datatype selection option for roofline (#624)
Added command line option to specify which datatype(s) to capture into the roofline PDF(s).
All datatypes are still collected by roofline call if applicable, but only specific datatypes are plotted into PDF outputs. Will dump out all datatypes into one graph, but separate FP from Int into two graphs if needed. Will skip datatype and give error message if the datatype is not valid on a particular gpu arch.
Default is FP32
Reworked roofline calls and plotting to be general enough such that any new datatypes added into rocm-amdgpu-bench can easily be reflected in rocprof-compute with simple modifications in roofline_calc.py.
Adjusted ctest to reflect expected default pdf outputs from roofline.
---------
Signed-off-by: Carrie Fallows <Carrie.Fallows@amd.com>
[ROCm/rocprofiler-compute commit: a492e92034]
This commit is contained in:
cfallows-amd
GitHub
@@ -33,7 +33,13 @@ import pandas as pd
|
||||
import plotly.graph_objects as go
|
||||
from dash import dcc, html
|
||||
|
||||
from utils.roofline_calc import calc_ai, constuct_roof
|
||||
from utils.roofline_calc import (
|
||||
MFMA_DATATYPES,
|
||||
PEAK_OPS_DATATYPES,
|
||||
SUPPORTED_DATATYPES,
|
||||
calc_ai,
|
||||
constuct_roof,
|
||||
)
|
||||
from utils.utils import (
|
||||
console_debug,
|
||||
console_error,
|
||||
@@ -60,6 +66,7 @@ class Roofline:
|
||||
"mem_level": "ALL",
|
||||
"include_kernel_names": False,
|
||||
"is_standalone": False,
|
||||
"roofline_data_type": ["FP32"],
|
||||
}
|
||||
)
|
||||
self.__ai_data = None
|
||||
@@ -76,7 +83,10 @@ class Roofline:
|
||||
self.__run_parameters["mem_level"] = self.__args.mem_level
|
||||
if hasattr(self.__args, "sort") and self.__args.sort != "ALL":
|
||||
self.__run_parameters["sort_type"] = self.__args.sort
|
||||
|
||||
if hasattr(
|
||||
self.__args, "roofline_data_type"
|
||||
) and self.__args.roofline_data_type != ["FP32"]:
|
||||
self.__run_parameters["roofline_data_type"] = self.__args.roofline_data_type
|
||||
self.validate_parameters()
|
||||
|
||||
def validate_parameters(self):
|
||||
@@ -121,19 +131,42 @@ class Roofline:
|
||||
msg += "\n\t%s -> %s" % (i, self.__ai_data[i])
|
||||
console_debug(msg)
|
||||
|
||||
# Generate a roofline figure for each data type
|
||||
fp32_fig = self.generate_plot(dtype="FP32")
|
||||
ml_combo_fig_fp32_fp64 = self.generate_plot(
|
||||
dtype="FP64",
|
||||
fig=fp32_fig,
|
||||
)
|
||||
fp16_fig = self.generate_plot(dtype="FP16")
|
||||
ml_combo_fig_int8_fp16 = self.generate_plot(
|
||||
dtype="I8",
|
||||
fig=fp16_fig,
|
||||
)
|
||||
if self.__mspec.gpu_series != "MI200":
|
||||
fig_fp8 = self.generate_plot(dtype="FP8")
|
||||
# Generate a roofline figure for the datatypes
|
||||
ops_figure = flops_figure = None
|
||||
ops_dt_list = flops_dt_list = ""
|
||||
for dt in self.__run_parameters["roofline_data_type"]:
|
||||
# Do not generate a roofline figure if the datatype is not supported on this gpu_arch
|
||||
if not str(dt) in SUPPORTED_DATATYPES[self.__mspec.gpu_arch]:
|
||||
console_error(
|
||||
"{} is not a supported datatype for roofline profiling on {}".format(
|
||||
str(dt), self.__mspec.gpu_model
|
||||
),
|
||||
exit=False,
|
||||
)
|
||||
continue
|
||||
|
||||
ops_flops = "Ops" if (str(dt[:1]) == "I") else "Flops"
|
||||
|
||||
if ops_flops == "Ops":
|
||||
if ops_figure:
|
||||
ops_combo_figure = self.generate_plot(
|
||||
dtype=str(dt),
|
||||
fig=ops_figure,
|
||||
)
|
||||
ops_figure = ops_combo_figure
|
||||
else:
|
||||
ops_figure = self.generate_plot(dtype=str(dt))
|
||||
ops_dt_list += "_" + str(dt)
|
||||
if ops_flops == "Flops":
|
||||
if flops_figure:
|
||||
flops_combo_figure = self.generate_plot(
|
||||
dtype=str(dt),
|
||||
fig=flops_figure,
|
||||
)
|
||||
flops_figure = flops_combo_figure
|
||||
else:
|
||||
flops_figure = self.generate_plot(dtype=str(dt))
|
||||
flops_dt_list += "_" + str(dt)
|
||||
|
||||
# Create a legend and distinct kernel markers. This can be saved, optionally
|
||||
self.__figure = go.Figure(
|
||||
@@ -160,80 +193,55 @@ class Roofline:
|
||||
if self.__run_parameters["is_standalone"]:
|
||||
dev_id = str(self.__run_parameters["device_id"])
|
||||
|
||||
ml_combo_fig_fp32_fp64.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_fp32_fp64.pdf".format(dev_id)
|
||||
)
|
||||
ml_combo_fig_int8_fp16.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_int8_fp16.pdf".format(dev_id)
|
||||
)
|
||||
if self.__mspec.gpu_series != "MI200":
|
||||
fig_fp8.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_fp8.pdf".format(dev_id)
|
||||
)
|
||||
# only save a legend if kernel_names option is toggled
|
||||
if self.__run_parameters["include_kernel_names"]:
|
||||
self.__figure.write_image(
|
||||
self.__run_parameters["workload_dir"] + "/kernelName_legend.pdf"
|
||||
)
|
||||
time.sleep(1)
|
||||
# Re-save to remove loading MathJax pop up
|
||||
ml_combo_fig_fp32_fp64.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_fp32_fp64.pdf".format(dev_id)
|
||||
)
|
||||
ml_combo_fig_int8_fp16.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_int8_fp16.pdf".format(dev_id)
|
||||
)
|
||||
if self.__mspec.gpu_series != "MI200":
|
||||
fig_fp8.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}_fp8.pdf".format(dev_id)
|
||||
)
|
||||
if self.__run_parameters["include_kernel_names"]:
|
||||
self.__figure.write_image(
|
||||
self.__run_parameters["workload_dir"] + "/kernelName_legend.pdf"
|
||||
)
|
||||
for i in range(2):
|
||||
if ops_figure:
|
||||
ops_figure.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}{}.pdf".format(dev_id, ops_dt_list)
|
||||
)
|
||||
if flops_figure:
|
||||
flops_figure.write_image(
|
||||
self.__run_parameters["workload_dir"]
|
||||
+ "/empirRoof_gpu-{}{}.pdf".format(dev_id, flops_dt_list)
|
||||
)
|
||||
|
||||
# only save a legend if kernel_names option is toggled
|
||||
if self.__run_parameters["include_kernel_names"]:
|
||||
self.__figure.write_image(
|
||||
self.__run_parameters["workload_dir"] + "/kernelName_legend.pdf"
|
||||
)
|
||||
time.sleep(1)
|
||||
console_log("roofline", "Empirical Roofline PDFs saved!")
|
||||
else:
|
||||
if self.__mspec.gpu_series != "MI200":
|
||||
fp8_graph = html.Div(
|
||||
if ops_figure:
|
||||
ops_graph = html.Div(
|
||||
className="float-child",
|
||||
children=[
|
||||
html.H3(children="Empirical Roofline Analysis (FP8)"),
|
||||
dcc.Graph(figure=fig_fp8),
|
||||
html.H3(children="Empirical Roofline Analysis (Ops)"),
|
||||
dcc.Graph(figure=ops_figure),
|
||||
],
|
||||
)
|
||||
else:
|
||||
fp8_graph = None
|
||||
ops_graph = None
|
||||
if flops_figure:
|
||||
flops_graph = html.Div(
|
||||
className="float-child",
|
||||
children=[
|
||||
html.H3(children="Empirical Roofline Analysis (Flops)"),
|
||||
dcc.Graph(figure=flops_figure),
|
||||
],
|
||||
)
|
||||
else:
|
||||
flops_graph = None
|
||||
return html.Section(
|
||||
id="roofline",
|
||||
children=[
|
||||
html.Div(
|
||||
className="float-container",
|
||||
children=[
|
||||
html.Div(
|
||||
className="float-child",
|
||||
children=[
|
||||
html.H3(
|
||||
children="Empirical Roofline Analysis (FP32/FP64)"
|
||||
),
|
||||
dcc.Graph(figure=ml_combo_fig_fp32_fp64),
|
||||
],
|
||||
),
|
||||
html.Div(
|
||||
className="float-child",
|
||||
children=[
|
||||
html.H3(
|
||||
children="Empirical Roofline Analysis (FP16/INT8)"
|
||||
),
|
||||
dcc.Graph(figure=ml_combo_fig_int8_fp16),
|
||||
],
|
||||
),
|
||||
fp8_graph,
|
||||
ops_graph,
|
||||
flops_graph,
|
||||
],
|
||||
)
|
||||
],
|
||||
@@ -284,9 +292,10 @@ class Roofline:
|
||||
)
|
||||
)
|
||||
|
||||
ops_flops = "OP" if (dtype[:1] == "I") else "FLOP"
|
||||
|
||||
# Plot peak VALU ceiling
|
||||
# VALU info I8/FP16 not collected via microbench
|
||||
if dtype != "FP16" and dtype != "I8":
|
||||
if dtype in PEAK_OPS_DATATYPES:
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=self.__ceiling_data["valu"][0],
|
||||
@@ -298,20 +307,18 @@ class Roofline:
|
||||
(
|
||||
None
|
||||
if self.__run_parameters["is_standalone"]
|
||||
else "{} GFLOP/s".format(
|
||||
to_int(self.__ceiling_data["valu"][2])
|
||||
else "{} G{}/s".format(
|
||||
to_int(self.__ceiling_data["valu"][2], ops_flops)
|
||||
)
|
||||
),
|
||||
"{} GFLOP/s".format(to_int(self.__ceiling_data["valu"][2])),
|
||||
"{} G{}/s".format(
|
||||
to_int(self.__ceiling_data["valu"][2]), ops_flops
|
||||
),
|
||||
],
|
||||
textposition="top left",
|
||||
)
|
||||
)
|
||||
|
||||
if dtype == "FP16":
|
||||
pos = "bottom left"
|
||||
else:
|
||||
pos = "top left"
|
||||
# Plot peak MFMA ceiling
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
@@ -324,26 +331,26 @@ class Roofline:
|
||||
(
|
||||
None
|
||||
if self.__run_parameters["is_standalone"]
|
||||
else "{} GFLOP/s".format(to_int(self.__ceiling_data["mfma"][2]))
|
||||
else "{} G{}/s".format(
|
||||
to_int(self.__ceiling_data["mfma"][2]), ops_flops
|
||||
)
|
||||
),
|
||||
"{} GFLOP/s".format(to_int(self.__ceiling_data["mfma"][2])),
|
||||
"{} G{}/s".format(to_int(self.__ceiling_data["mfma"][2]), ops_flops),
|
||||
],
|
||||
textposition=pos,
|
||||
textposition="top left",
|
||||
)
|
||||
)
|
||||
#######################
|
||||
# Plot Application AI
|
||||
#######################
|
||||
if dtype != "I8" and dtype != "FP64":
|
||||
# Plot the arithmetic intensity points for each cache level
|
||||
# Omitting I8 AIs to clean up graph. FP16 tends to be higher.
|
||||
# Plot the arithmetic intensity points for each cache level
|
||||
if ops_flops == "FLOP":
|
||||
fig.add_trace(
|
||||
go.Scatter(
|
||||
x=self.__ai_data["ai_l1"][0],
|
||||
y=self.__ai_data["ai_l1"][1],
|
||||
name="ai_l1",
|
||||
name=dtype + "_ai_l1",
|
||||
mode="markers",
|
||||
marker={"color": "#00CC96"},
|
||||
marker_symbol=(
|
||||
SYMBOLS if self.__run_parameters["include_kernel_names"] else None
|
||||
),
|
||||
@@ -353,9 +360,8 @@ class Roofline:
|
||||
go.Scatter(
|
||||
x=self.__ai_data["ai_l2"][0],
|
||||
y=self.__ai_data["ai_l2"][1],
|
||||
name="ai_l2",
|
||||
name=dtype + "_ai_l2",
|
||||
mode="markers",
|
||||
marker={"color": "#EF553B"},
|
||||
marker_symbol=(
|
||||
SYMBOLS if self.__run_parameters["include_kernel_names"] else None
|
||||
),
|
||||
@@ -365,22 +371,30 @@ class Roofline:
|
||||
go.Scatter(
|
||||
x=self.__ai_data["ai_hbm"][0],
|
||||
y=self.__ai_data["ai_hbm"][1],
|
||||
name="ai_hbm",
|
||||
name=dtype + "_ai_hbm",
|
||||
mode="markers",
|
||||
marker={"color": "#636EFA"},
|
||||
marker_symbol=(
|
||||
SYMBOLS if self.__run_parameters["include_kernel_names"] else None
|
||||
),
|
||||
)
|
||||
)
|
||||
|
||||
# Set layout
|
||||
fig.update_layout(
|
||||
xaxis_title="Arithmetic Intensity (FLOPs/Byte)",
|
||||
yaxis_title="Performance (GFLOP/sec)",
|
||||
hovermode="x unified",
|
||||
margin=dict(l=50, r=50, b=50, t=50, pad=4),
|
||||
)
|
||||
# Set layout
|
||||
fig.update_layout(
|
||||
xaxis_title="Arithmetic Intensity (FLOPs/Byte)",
|
||||
yaxis_title="Performance (GFLOP/sec)",
|
||||
hovermode="x unified",
|
||||
margin=dict(l=50, r=50, b=50, t=50, pad=4),
|
||||
)
|
||||
else:
|
||||
# Set layout
|
||||
fig.update_layout(
|
||||
xaxis_title="Bandwidth (GB/sec)",
|
||||
yaxis_title="Performance (GOP/sec)",
|
||||
hovermode="x unified",
|
||||
margin=dict(l=50, r=50, b=50, t=50, pad=4),
|
||||
)
|
||||
|
||||
fig.update_xaxes(type="log", autorange=True)
|
||||
fig.update_yaxes(type="log", autorange=True)
|
||||
|
||||
|
||||
Viittaa uudesa ongelmassa
Block a user