Introduce powerful simulation script and provide an example
This commit is contained in:
142
scripts/simulation/example_ddr3_simulations.json
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142
scripts/simulation/example_ddr3_simulations.json
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@@ -0,0 +1,142 @@
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{
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"simulation": {
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"addressmapping": {
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"BANK_BIT": [
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6,
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7,
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8
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],
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"BYTE_BIT": [
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0,
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1,
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2
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],
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"COLUMN_BIT": [
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3,
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4,
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5,
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9,
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10,
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11,
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12,
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13,
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14,
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15
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],
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"ROW_BIT": [
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16,
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17,
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18,
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19,
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20,
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21,
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22,
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23,
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24,
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25,
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26,
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27,
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28,
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29
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]
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},
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"mcconfig": {
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"PagePolicy": "<page_policy>",
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"SchedulerBuffer": "<scheduler_buffer>",
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"RequestBufferSize": <scheduler_buffer_size>,
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"RefreshPolicy": "<refresh_policy>",
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"RefreshMaxPostponed": 0,
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"RefreshMaxPulledin": 0,
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"RefreshManagement": false,
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"Arbiter": "Simple",
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"CmdMux": "Oldest",
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"MaxActiveTransactions": 128,
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"PowerDownPolicy": "NoPowerDown",
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"RespQueue": "Fifo",
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"Scheduler": "FrFcfs"
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},
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"memspec": {
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"memarchitecturespec": {
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"burstLength": 8,
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"dataRate": 2,
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"nbrOfBanks": 8,
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"nbrOfChannels": 1,
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"nbrOfColumns": 1024,
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"nbrOfDevices": 8,
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"nbrOfRanks": 1,
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"nbrOfRows": 16384,
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"width": 8
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},
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"memoryId": "MICRON_1Gb_DDR3-1600_8bit_G",
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"memoryType": "DDR3",
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"mempowerspec": {
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"idd0": 70.0,
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"idd2n": 45.0,
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"idd2p0": 12.0,
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"idd2p1": 30.0,
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"idd3n": 45.0,
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"idd3p0": 35.0,
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"idd3p1": 35.0,
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"idd4r": 140.0,
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"idd4w": 145.0,
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"idd5": 170.0,
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"idd6": 8.0,
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"vdd": 1.5
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},
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"memtimingspec": {
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"ACTPDEN": 1,
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"AL": 0,
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"CCD": 4,
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"CKE": 3,
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"CKESR": 4,
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"CL": 10,
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"DQSCK": 0,
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"FAW": 24,
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"PRPDEN": 1,
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"RAS": 28,
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"RC": 38,
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"RCD": 10,
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"REFI": 6240,
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"REFPDEN": 1,
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"RFC": 88,
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"RL": 10,
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"RP": 10,
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"RRD": 5,
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"RTP": 6,
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"RTRS": 1,
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"WL": 8,
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"WR": 12,
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"WTR": 6,
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"XP": 6,
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"XPDLL": 20,
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"XS": 96,
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"XSDLL": 512,
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"clkMhz": 800
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}
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},
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"simconfig": {
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"AddressOffset": 0,
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"CheckTLM2Protocol": false,
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"DatabaseRecording": true,
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"Debug": false,
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"EnableWindowing": false,
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"PowerAnalysis": false,
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"SimulationName": "example",
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"SimulationProgressBar": false,
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"StoreMode": "NoStorage",
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"UseMalloc": false,
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"WindowSize": 1000
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},
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"simulationid": "ddr3-example",
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"tracesetup": [
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{
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"clkMhz": 2000,
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"type": "generator",
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"name": "gen1",
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"numRequests": 20000,
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"rwRatio": 0.85,
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"addressDistribution": "<pattern>"
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}
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]
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}
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}
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114
scripts/simulation/example_ddr3_simulations.py
Executable file
114
scripts/simulation/example_ddr3_simulations.py
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@@ -0,0 +1,114 @@
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#!/usr/bin/env python3
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import os
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import matplotlib.pyplot as plt
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from dataclasses import dataclass
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from simulation import (
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Simulation,
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Configuration,
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get_options_from_args,
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simulation_results,
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)
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script_directory = os.path.dirname(os.path.abspath(__file__))
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base_config = os.path.join(script_directory, "example_ddr3_simulations.json")
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simulations: list[Simulation] = []
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@dataclass(frozen=True)
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class SchedulerBuffer:
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buffer: str
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size: int
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refresh_policies = ["NoRefresh", "AllBank"]
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patterns = ["sequential", "random"]
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scheduler_buffers = [
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SchedulerBuffer("Bankwise", 8),
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SchedulerBuffer("Bankwise", 16),
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]
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for refresh_policy in refresh_policies:
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for scheduler_buffer in scheduler_buffers:
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for pattern in patterns:
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PAGE_POLICY = "Open" if pattern == "sequential" else "Closed"
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config = Configuration(
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f"{refresh_policy}_{scheduler_buffer.buffer}_{scheduler_buffer.size}_{pattern}",
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{
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"refresh_policy": refresh_policy,
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"pattern": pattern,
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"page_policy": PAGE_POLICY,
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"scheduler_buffer": scheduler_buffer.buffer,
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"scheduler_buffer_size": scheduler_buffer.size,
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},
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)
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simulations.append(Simulation(config))
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options = get_options_from_args()
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if options.base_config is None:
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options.base_config = base_config
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dataframe = simulation_results(options, simulations)
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# Generate interesting plots!
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for refresh_policy in refresh_policies:
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refresh_policy_filter = dataframe["refresh_policy"] == refresh_policy
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for scheduler_buffer in scheduler_buffers:
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scheduler_buffer_filter = (
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dataframe["scheduler_buffer"] == scheduler_buffer.buffer
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)
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scheduler_buffer_size_filter = (
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dataframe["scheduler_buffer_size"] == scheduler_buffer.size
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)
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filters = (
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refresh_policy_filter
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& scheduler_buffer_filter
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& scheduler_buffer_size_filter
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)
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TEMP_DATAFRAME = dataframe[filters]
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for pattern in patterns:
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pattern_filter = dataframe["pattern"] == pattern
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plt.figure(figsize=(8.0, 12.0))
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filters = (
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refresh_policy_filter
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& scheduler_buffer_filter
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& scheduler_buffer_size_filter
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)
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TEMP_DATAFRAME = dataframe[filters]
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plt.bar(
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"pattern",
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"bandwidth",
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data=TEMP_DATAFRAME,
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)
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# Plot MAX line
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plt.bar(
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"MAX",
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"max_bandwidth",
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data=TEMP_DATAFRAME,
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color="darkgray",
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)
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title = f"{refresh_policy} {scheduler_buffer.buffer} {scheduler_buffer.size}"
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plt.title(title)
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plt.axis(ymin=0, ymax=120)
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plt.xlabel("Access Pattern")
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plt.ylabel("Bandwidth [Gb/s]")
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plt.savefig(f"{options.out_dir}/{title}.png")
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plt.close()
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3
scripts/simulation/requirements.txt
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3
scripts/simulation/requirements.txt
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@@ -0,0 +1,3 @@
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tqdm
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pandas
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matplotlib
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331
scripts/simulation/simulation.py
Executable file
331
scripts/simulation/simulation.py
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@@ -0,0 +1,331 @@
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import argparse
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import subprocess
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import sys
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import sqlite3
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import json
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import os
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import re
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from pathlib import Path
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from dataclasses import dataclass, fields
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from typing import Optional
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from multiprocessing.pool import ThreadPool
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from tqdm import tqdm
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import pandas as pd
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sys.path.append("extensions/apps/traceAnalyzer/scripts")
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from metrics import (
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average_response_latency_in_ns,
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max_response_latency_in_ns,
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memory_active_in_percent,
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maximum_data_rate,
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)
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@dataclass
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class Options:
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dramsys: Path
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override: bool
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out_dir: Path
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simulate: bool
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metrics: bool
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base_config: Path | None
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resource_dir: Path | None = None
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jobs: int | None = None
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@dataclass(frozen=True)
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class SubConfig:
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name: str
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parameters: dict[str, str]
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@dataclass(frozen=True)
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class Statistics:
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filename: str
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databus_utilization: float
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bandwidth: float
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max_bandwidth: float
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avg_latency: float
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max_latency: float
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@dataclass(frozen=True)
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class Configuration:
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name: str
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tokens: dict[str, str | int]
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@dataclass
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class Simulation:
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config: Configuration
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directory: Optional[str] = None
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statistics: Optional[list[Statistics]] = None
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def run_dramsys(dramsys: Path, simulation_dir: Path, resource_dir: Path | None):
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with open(f"{simulation_dir}/out.txt", "w", encoding="utf-8") as output_file:
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command = [dramsys.absolute(), "config.json"]
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if resource_dir is not None:
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command.append(resource_dir)
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subprocess.run(command, cwd=simulation_dir, stdout=output_file, check=True)
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def calculate_simulation_metrics(simulation: Simulation):
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simulation_dir = simulation.directory
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stats: list[Statistics] = []
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for file in os.listdir(simulation_dir):
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if file.endswith(".tdb"):
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connection = sqlite3.connect(f"{simulation_dir}/{file}")
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try:
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max_bandwidth = maximum_data_rate(connection) / 1000
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avg_latency = average_response_latency_in_ns(connection)
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max_latency = max_response_latency_in_ns(connection)
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databus_utilization = memory_active_in_percent(connection) / 100
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bandwidth = databus_utilization * max_bandwidth
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stats.append(
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Statistics(
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file,
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databus_utilization,
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bandwidth,
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max_bandwidth,
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avg_latency,
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max_latency,
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)
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)
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except Exception as error:
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print(
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f"Warning: Could not calculate metrics for {simulation_dir}/{file}: {error}"
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)
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simulation.statistics = stats
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# Replace placeholders with actual values
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def replace_placeholders(config_json: str, tokens: dict) -> str:
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for key, value in tokens.items():
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placeholder = f"<{key}>"
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config_json = config_json.replace(placeholder, str(value))
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return config_json
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@dataclass
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class WorkItem:
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dramsys: Path
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simulation: Simulation
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base_config: Path
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resource_dir: Path | None
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def simulate(
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work_item: WorkItem,
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):
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simulation_dir = work_item.simulation.directory
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json_config = None
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with open(work_item.base_config, encoding="utf-8") as config_file:
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config_string = config_file.read()
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config_string = replace_placeholders(
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config_string, work_item.simulation.config.tokens
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)
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json_config = json.loads(config_string)
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simulation_json = simulation_dir / "config.json"
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# Save config besides simulation directory
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with open(simulation_json, "w", encoding="utf-8") as config_file:
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json.dump(json_config, config_file, indent=4)
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run_dramsys(work_item.dramsys, simulation_dir, work_item.resource_dir)
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calculate_simulation_metrics(work_item.simulation)
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def generate_dataframe(simulations: list[Simulation], out_dir: str) -> pd.DataFrame:
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# Pack results in a panda dataframe
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labels = ["name", "channel"]
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statistic_labels = list(map(lambda field: field.name, fields(Statistics)))
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# Get one simulation...
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config_keys, _ = zip(*simulations[0].config.tokens.items())
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labels.extend(config_keys)
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labels.extend(statistic_labels)
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entries = []
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for simulation in simulations:
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_, config_values = zip(*simulation.config.tokens.items())
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for stat in simulation.statistics:
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channel_pattern = re.compile("(?<=ch)[0-9]+")
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channel = int(channel_pattern.search(stat.filename)[0])
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entries.append(
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[
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simulation.config.name,
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channel,
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*config_values,
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stat.filename,
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stat.databus_utilization,
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stat.bandwidth,
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stat.max_bandwidth,
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stat.avg_latency,
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stat.max_latency,
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||||
]
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)
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dataframe = pd.DataFrame(data=entries, columns=labels)
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dataframe.to_csv(f"{out_dir}/statistics.csv", sep=";")
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return dataframe
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def populate_simulation_directories(
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simulations: list[Simulation], out_dir: str, override: bool
|
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):
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for simulation in simulations:
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simulation_dir = Path(f"{out_dir}/simulations/{simulation.config.name}")
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try:
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simulation_dir.mkdir(parents=True, exist_ok=override)
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except FileExistsError:
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print(
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"Previous simulations artifacts found. To continue, enable the force override flag."
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)
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sys.exit(-1)
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simulation.directory = simulation_dir
|
||||
|
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|
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def calculate_metrics(
|
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simulations: list[Simulation], out_dir: str, jobs: int | None
|
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) -> pd.DataFrame:
|
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populate_simulation_directories(simulations, out_dir, override=True)
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with ThreadPool(jobs) as thread_pool:
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for _ in tqdm(
|
||||
thread_pool.imap_unordered(calculate_simulation_metrics, simulations),
|
||||
total=len(simulations),
|
||||
):
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pass
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return generate_dataframe(simulations, out_dir)
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||||
|
||||
|
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def run_simulations(simulations: list[Simulation], options: Options) -> pd.DataFrame:
|
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if len(simulations) == 0:
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print("Must specify at least one simulation configuration!")
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sys.exit(-1)
|
||||
|
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if options.base_config is None:
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print("Must specify a base config")
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sys.exit(-1)
|
||||
|
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print("Create simulation directories...")
|
||||
populate_simulation_directories(simulations, options.out_dir, options.override)
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||||
|
||||
print("Run simulations...")
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with ThreadPool(options.jobs) as thread_pool:
|
||||
args = list(
|
||||
WorkItem(
|
||||
options.dramsys, simulation, options.base_config, options.resource_dir
|
||||
)
|
||||
for simulation in simulations
|
||||
)
|
||||
|
||||
for _ in tqdm(thread_pool.imap_unordered(simulate, args), total=len(args)):
|
||||
pass
|
||||
|
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print("Calculate metrics...")
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return calculate_metrics(simulations, options.out_dir, options.jobs)
|
||||
|
||||
|
||||
def get_options_from_args() -> Options:
|
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parser = argparse.ArgumentParser(description="DRAMSys simulation utility")
|
||||
parser.add_argument("dramsys", type=Path, help="path to the DRAMSys executable")
|
||||
parser.add_argument(
|
||||
"--simulate",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="run the simulations generating simulation artifacts",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--metrics",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="calculate the metrics from existing simulation artifacts",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-f",
|
||||
"--force",
|
||||
default=False,
|
||||
action="store_true",
|
||||
help="force override existing simulation artifacts",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--out-dir",
|
||||
type=Path,
|
||||
default="out",
|
||||
help="path to the output directory",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--base-config",
|
||||
type=Path,
|
||||
help="path to the base configuration file",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--resource-dir",
|
||||
type=Path,
|
||||
help="path to the resource directory",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-j",
|
||||
"--jobs",
|
||||
metavar="N",
|
||||
type=int,
|
||||
default=None,
|
||||
help="run N jobs in parallel",
|
||||
)
|
||||
|
||||
arguments = parser.parse_args()
|
||||
return Options(
|
||||
arguments.dramsys,
|
||||
arguments.force,
|
||||
arguments.out_dir,
|
||||
arguments.simulate,
|
||||
arguments.metrics,
|
||||
arguments.base_config,
|
||||
arguments.resource_dir,
|
||||
arguments.jobs,
|
||||
)
|
||||
|
||||
|
||||
def simulation_results(
|
||||
options: Options,
|
||||
simulations: list[Simulation],
|
||||
) -> pd.DataFrame:
|
||||
if options.simulate:
|
||||
return run_simulations(simulations, options)
|
||||
|
||||
if options.metrics:
|
||||
return calculate_metrics(simulations, options.out_dir, options.jobs)
|
||||
|
||||
print("Summarizing simulation results in statistics.csv...")
|
||||
|
||||
statistics_file = f"{options.out_dir}/statistics.csv"
|
||||
if not os.path.isfile(statistics_file):
|
||||
print("Run the simulations first to generate simulation artifacts")
|
||||
sys.exit(-1)
|
||||
|
||||
return pd.read_csv(f"{options.out_dir}/statistics.csv", sep=";")
|
||||
Reference in New Issue
Block a user