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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import NvRules
def get_identifier():
return "SlowPipeLimiter"
def get_name():
return "Slow Pipe Limiter"
def get_description():
return "Slow pipe limiting compute utilization"
def get_section_identifier():
return "ComputeWorkloadAnalysis"
def apply(handle):
ctx = NvRules.get_context(handle)
action = ctx.range_by_idx(0).action_by_idx(0)
fe = ctx.frontend()
sm_busy = action.metric_by_name("sm__instruction_throughput.avg.pct_of_peak_sustained_active").as_double()
inst_issued_avg = action.metric_by_name("sm__inst_issued.avg.pct_of_peak_sustained_active").as_double()
inst_issued_max = action.metric_by_name("sm__inst_issued.max.pct_of_peak_sustained_active").as_double()
no_bound_threshold = 80
issued_avg_threshold = 20
diff_threshold = 25
doc_msg = " See the @url:Kernel Profiling Guide:https://docs.nvidia.com/nsight-compute/ProfilingGuide/index.html#metrics-decoder@ for the workloads handled by each pipeline."
pipe_diff = inst_issued_max - inst_issued_avg
if sm_busy >= no_bound_threshold and inst_issued_avg < issued_avg_threshold and pipe_diff > diff_threshold:
msg_id = fe.message("It is possible that a slow pipeline is preventing better kernel performance."\
" The average pipeline utilization of {:.1f}% is {:.1f}% lower than the maximum utilization of {:.1f}%."\
" Try moving compute to other pipelines, e.g. from fp64 to fp32 or int."\
"{}".format(inst_issued_avg, pipe_diff, inst_issued_max, doc_msg), "Slow Pipeline")
fe.focus_metric(msg_id, "sm__instruction_throughput.avg.pct_of_peak_sustained_active", sm_busy, NvRules.IFrontend.Severity_SEVERITY_DEFAULT, "{} >= {}".format(sm_busy, no_bound_threshold))
fe.focus_metric(msg_id, "sm__inst_issued.avg.pct_of_peak_sustained_active", inst_issued_avg, NvRules.IFrontend.Severity_SEVERITY_DEFAULT, "{} < {}".format(inst_issued_avg, issued_avg_threshold))
fe.focus_metric(msg_id, "sm__inst_issued.max.pct_of_peak_sustained_active", inst_issued_max, NvRules.IFrontend.Severity_SEVERITY_DEFAULT, "{} - {} > {}".format(inst_issued_max, inst_issued_avg, diff_threshold))
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