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TheRock/rocm-systems/projects/rocprofiler-sdk/tests/rocprofv3/counter-collection/queue-overflow/validate.py
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

145 lines
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Python

#!/usr/bin/env python3
# MIT License
#
# Copyright (c) 2024-2026 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.
# Regression coverage for the hsa-runtime InterceptQueue retry/overflow hang
# during counter collection. The multistream workload launches 100 streams x
# 100 iterations = 10000 kernel dispatches. Counter collection rewrites every
# dispatch (counter start/stop packets) via the hsa-runtime InterceptQueue, so
# a regression either hangs (the execute test hits its TIMEOUT) or drops
# dispatches / corrupts the ring copy. The assertions below require that all
# 10000 dispatches were captured with valid SQ_WAVES data.
import sys
import pytest
import pandas as pd
import re
# multistream: 100 streams x 100 iterations (see tests/bin/multistream/multistream_app.cpp)
EXPECTED_DISPATCHES = 100 * 100
KERNEL_NAME = "add(int, float*, float*)"
def is_helper(name):
return bool(re.search(r"__amd_rocclr_.*", name))
def test_validate_counter_collection_queue_overflow(input_data: pd.DataFrame):
df = input_data
assert not df.empty
df_agent_id = df["Agent_Id"].str.split(" ").str[-1]
assert (df_agent_id.astype(int).values >= 0).all()
assert (df["Queue_Id"].astype(int).values > 0).all()
assert (df["Process_Id"].astype(int).values > 0).all()
# only real (non-rocclr-helper) kernel dispatched by multistream is the add kernel
real_kernels = sorted(
x for x in df["Kernel_Name"].unique().tolist() if not is_helper(x)
)
assert real_kernels == [KERNEL_NAME]
# all counters requested are SQ_WAVES and every dispatch reported a positive value
assert df["Counter_Name"].str.contains("SQ_WAVES").all()
assert (df["Counter_Value"].astype(int).values > 0).all()
# key regression check: every one of the 10000 dispatches was captured (a hang or
# out-of-bounds ring copy in the overflow/retry path would strand or drop dispatches)
add_rows = df[df["Kernel_Name"] == KERNEL_NAME]
assert len(add_rows) == EXPECTED_DISPATCHES
# dispatch ids are unique and contiguous from 1
di_list = df["Dispatch_Id"].astype(int).values.tolist()
di_uniq = sorted(df["Dispatch_Id"].unique().tolist())
di_expect = [idx + 1 for idx in range(len(di_list))]
assert di_expect == di_uniq
def test_validate_counter_collection_queue_overflow_json(json_data):
data = json_data["rocprofiler-sdk-tool"]
counter_collection_data = data["callback_records"]["counter_collection"]
# at present, AQLProfile has bugs when reporting the counters for below architectures
skip_gfx = ("gfx1101", "gfx1102", "gfx1150", "gfx1151", "gfx1152", "gfx1153")
def get_kernel_name(kernel_id):
return data["kernel_symbols"][kernel_id]["formatted_kernel_name"]
def get_agent(agent_id):
for agent in data["agents"]:
if agent["id"]["handle"] == agent_id["handle"]:
return agent
return None
def get_counter(counter_id):
for counter in data["counters"]:
if counter["id"]["handle"] == counter_id["handle"]:
return counter
return None
dispatch_ids = []
add_dispatches = 0
for counter in counter_collection_data:
dispatch_data = counter["dispatch_data"]["dispatch_info"]
assert dispatch_data["dispatch_id"] > 0
assert dispatch_data["agent_id"]["handle"] > 0
assert dispatch_data["queue_id"]["handle"] > 0
agent = get_agent(dispatch_data["agent_id"])
kernel_name = get_kernel_name(dispatch_data["kernel_id"])
assert agent is not None
assert len(kernel_name) > 0
dispatch_ids.append(dispatch_data["dispatch_id"])
if is_helper(kernel_name):
continue
add_dispatches += 1
sq_waves_values = []
for record in counter["records"]:
counter_meta = get_counter(record["counter_id"])
assert counter_meta is not None, f"record:\n\t{record}"
assert (
counter_meta["name"] == "SQ_WAVES"
), f"record:\n\t{record}\ncounter:\n\t{counter_meta}"
if agent["name"] not in skip_gfx:
sq_waves_values.append(record["value"])
if agent["name"] not in skip_gfx:
assert sum(sq_waves_values) > 0, "SQ_WAVES value is not > 0"
# key regression check: all 10000 dispatches captured, none stranded/dropped
assert add_dispatches == EXPECTED_DISPATCHES
di_uniq = sorted(set(dispatch_ids))
di_expect = [idx + 1 for idx in range(len(dispatch_ids))]
assert di_expect == di_uniq
if __name__ == "__main__":
exit_code = pytest.main(["-x", __file__] + sys.argv[1:])
sys.exit(exit_code)