colramos-amd
121 lines
3.7 KiB
Python
121 lines
3.7 KiB
Python
##############################################################################bl
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# MIT License
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#
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# Copyright (c) 2021 - 2024 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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#
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# Define all common data storage classes,
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# predifned dict and global functions.
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#
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import pandas as pd
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from typing import Dict, List, Mapping, Generator
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from dataclasses import dataclass, field
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from collections import OrderedDict
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@dataclass
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class ArchConfig:
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# [id: panel_config] pairs
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panel_configs: OrderedDict = field(default=dict)
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# [id: df] pairs
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dfs: Dict[int, pd.DataFrame] = field(default_factory=dict)
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# NB:
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# dfs_type should be a meta info embeded into df.
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# pandas.DataFrame.attrs is experimental and may change without warning.
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# So do it as below for now.
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# [id: df_type] pairs
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dfs_type: Dict[int, str] = field(default_factory=dict)
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# [Index: Metric name] pairs
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metric_list: Dict[str, str] = field(default_factory=dict)
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# [Metric name: Counters] pairs
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metric_counters: Dict[str, list] = field(default_factory=dict)
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@dataclass
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class Workload:
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sys_info: pd.DataFrame = None
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raw_pmc: pd.DataFrame = None
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dfs: Dict[int, pd.DataFrame] = field(default_factory=dict)
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dfs_type: Dict[int, str] = field(default_factory=dict)
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filter_kernel_ids: List[int] = field(default_factory=list)
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filter_gpu_ids: List[int] = field(default_factory=list)
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filter_dispatch_ids: List[int] = field(default_factory=list)
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avail_ips: List[int] = field(default_factory=list)
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# Metrics will be calculated ONLY when the header(key) is in below list
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supported_field = [
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"Value",
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"Minimum",
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"Maximum",
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"Average",
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"Median",
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"Min",
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"Max",
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"Avg",
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"Pct of Peak",
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"Peak",
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"Count",
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"Mean",
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"Pct",
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"Std Dev",
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"Q1",
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"Q3",
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"Expression",
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# Special keywords for L2 channel
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"Channel",
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"L2 Cache Hit Rate",
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"Requests",
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"L2 Read",
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"L2 Write",
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"L2 Atomic",
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"L2-Fabric Requests",
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"L2-Fabric Read",
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"L2-Fabric Write and Atomic",
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"L2-Fabric Atomic",
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"L2 Read Req",
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"L2 Write Req",
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"L2 Atomic Req",
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"L2-Fabric Read Req",
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"L2-Fabric Write and Atomic Req",
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"L2-Fabric Atomic Req",
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"L2-Fabric Read Latency",
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"L2-Fabric Write Latency",
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"L2-Fabric Atomic Latency",
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"L2-Fabric Read Stall (PCIe)",
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"L2-Fabric Read Stall (Infinity Fabric™)",
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"L2-Fabric Read Stall (HBM)",
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"L2-Fabric Write Stall (PCIe)",
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"L2-Fabric Write Stall (Infinity Fabric™)",
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"L2-Fabric Write Stall (HBM)",
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"L2-Fabric Write Starve",
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]
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# The prefix of raw pmc_perf.csv
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pmc_perf_file_prefix = "pmc_perf"
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