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