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![Daniel P. Berrangé](/assets/img/avatar_default.png)
The RST doc include can't be made to skip the comment indicating the CPU CSV file is auto-generated when importing it. This comment line was previously manually removed from the generated output that was committed. Signed-off-by: Daniel P. Berrangé <berrange@redhat.com>
193 lines
4.7 KiB
Python
193 lines
4.7 KiB
Python
#!/usr/bin/python3
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#
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# SPDX-License-Identifier: GPL-2.0-or-later
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#
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# A script to generate a CSV file showing the x86_64 ABI
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# compatibility levels for each CPU model.
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#
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from qemu.qmp.legacy import QEMUMonitorProtocol
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import sys
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if len(sys.argv) != 2:
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print("syntax: %s QMP-SOCK\n\n" % __file__ +
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"Where QMP-SOCK points to a QEMU process such as\n\n" +
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" # qemu-system-x86_64 -qmp unix:/tmp/qmp,server,nowait " +
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"-display none -accel kvm", file=sys.stderr)
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sys.exit(1)
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# Mandatory CPUID features for each microarch ABI level
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levels = [
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[ # x86-64 baseline
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"cmov",
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"cx8",
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"fpu",
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"fxsr",
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"mmx",
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"syscall",
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"sse",
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"sse2",
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],
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[ # x86-64-v2
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"cx16",
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"lahf-lm",
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"popcnt",
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"pni",
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"sse4.1",
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"sse4.2",
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"ssse3",
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],
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[ # x86-64-v3
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"avx",
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"avx2",
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"bmi1",
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"bmi2",
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"f16c",
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"fma",
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"abm",
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"movbe",
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],
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[ # x86-64-v4
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"avx512f",
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"avx512bw",
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"avx512cd",
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"avx512dq",
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"avx512vl",
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],
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]
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# Assumes externally launched process such as
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#
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# qemu-system-x86_64 -qmp unix:/tmp/qmp,server,nowait -display none -accel kvm
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#
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# Note different results will be obtained with TCG, as
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# TCG masks out certain features otherwise present in
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# the CPU model definitions, as does KVM.
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sock = sys.argv[1]
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shell = QEMUMonitorProtocol(sock)
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shell.connect()
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models = shell.cmd("query-cpu-definitions")
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# These QMP props don't correspond to CPUID fatures
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# so ignore them
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skip = [
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"family",
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"min-level",
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"min-xlevel",
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"vendor",
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"model",
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"model-id",
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"stepping",
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]
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names = []
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for model in models:
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if "alias-of" in model:
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continue
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names.append(model["name"])
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models = {}
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for name in sorted(names):
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cpu = shell.cmd("query-cpu-model-expansion",
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type="static",
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model={ "name": name })
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got = {}
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for (feature, present) in cpu["model"]["props"].items():
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if present and feature not in skip:
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got[feature] = True
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if name in ["host", "max", "base"]:
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continue
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models[name] = {
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# Dict of all present features in this CPU model
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"features": got,
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# Whether each x86-64 ABI level is satisfied
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"levels": [False, False, False, False],
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# Number of extra CPUID features compared to the x86-64 ABI level
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"distance":[-1, -1, -1, -1],
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# CPUID features present in model, but not in ABI level
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"delta":[[], [], [], []],
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# CPUID features in ABI level but not present in model
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"missing": [[], [], [], []],
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}
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# Calculate whether the CPU models satisfy each ABI level
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for name in models.keys():
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for level in range(len(levels)):
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got = set(models[name]["features"])
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want = set(levels[level])
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missing = want - got
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match = True
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if len(missing) > 0:
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match = False
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models[name]["levels"][level] = match
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models[name]["missing"][level] = missing
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# Cache list of CPU models satisfying each ABI level
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abi_models = [
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[],
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[],
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[],
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[],
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]
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for name in models.keys():
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for level in range(len(levels)):
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if models[name]["levels"][level]:
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abi_models[level].append(name)
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for level in range(len(abi_models)):
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# Find the union of features in all CPU models satisfying this ABI
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allfeatures = {}
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for name in abi_models[level]:
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for feat in models[name]["features"]:
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allfeatures[feat] = True
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# Find the intersection of features in all CPU models satisfying this ABI
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commonfeatures = []
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for feat in allfeatures:
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present = True
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for name in models.keys():
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if not models[name]["levels"][level]:
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continue
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if feat not in models[name]["features"]:
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present = False
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if present:
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commonfeatures.append(feat)
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# Determine how many extra features are present compared to the lowest
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# common denominator
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for name in models.keys():
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if not models[name]["levels"][level]:
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continue
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delta = set(models[name]["features"].keys()) - set(commonfeatures)
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models[name]["distance"][level] = len(delta)
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models[name]["delta"][level] = delta
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def print_uarch_abi_csv():
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print("Model,baseline,v2,v3,v4")
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for name in models.keys():
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print(name, end="")
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for level in range(len(levels)):
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if models[name]["levels"][level]:
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print(",✅", end="")
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else:
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print(",", end="")
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print()
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print_uarch_abi_csv()
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