scripts/cpu-x86-uarch-abi.py

   1 #!/usr/bin/python3
   2 #
   3 # SPDX-License-Identifier: GPL-2.0-or-later
   4 #
   5 # A script to generate a CSV file showing the x86_64 ABI
   6 # compatibility levels for each CPU model.
   7 #
   8
   9 from qemu import qmp
  10 import sys
  11
  12 if len(sys.argv) != 1:
  13     print("syntax: %s QMP-SOCK\n\n" % __file__ +
  14           "Where QMP-SOCK points to a QEMU process such as\n\n" +
  15           " # qemu-system-x86_64 -qmp unix:/tmp/qmp,server,nowait " +
  16           "-display none -accel kvm", file=sys.stderr)
  17     sys.exit(1)
  18
  19 # Mandatory CPUID features for each microarch ABI level
  20 levels = [
  21     [ # x86-64 baseline
  22         "cmov",
  23         "cx8",
  24         "fpu",
  25         "fxsr",
  26         "mmx",
  27         "syscall",
  28         "sse",
  29         "sse2",
  30     ],
  31     [ # x86-64-v2
  32         "cx16",
  33         "lahf-lm",
  34         "popcnt",
  35         "pni",
  36         "sse4.1",
  37         "sse4.2",
  38         "ssse3",
  39     ],
  40     [ # x86-64-v3
  41         "avx",
  42         "avx2",
  43         "bmi1",
  44         "bmi2",
  45         "f16c",
  46         "fma",
  47         "abm",
  48         "movbe",
  49     ],
  50     [ # x86-64-v4
  51         "avx512f",
  52         "avx512bw",
  53         "avx512cd",
  54         "avx512dq",
  55         "avx512vl",
  56     ],
  57 ]
  58
  59 # Assumes externally launched process such as
  60 #
  61 #   qemu-system-x86_64 -qmp unix:/tmp/qmp,server,nowait -display none -accel kvm
  62 #
  63 # Note different results will be obtained with TCG, as
  64 # TCG masks out certain features otherwise present in
  65 # the CPU model definitions, as does KVM.
  66
  67
  68 sock = sys.argv[1]
  69 cmd = sys.argv[2]
  70 shell = qmp.QEMUMonitorProtocol(sock)
  71 shell.connect()
  72
  73 models = shell.cmd("query-cpu-definitions")
  74
  75 # These QMP props don't correspond to CPUID fatures
  76 # so ignore them
  77 skip = [
  78     "family",
  79     "min-level",
  80     "min-xlevel",
  81     "vendor",
  82     "model",
  83     "model-id",
  84     "stepping",
  85 ]
  86
  87 names = []
  88
  89 for model in models["return"]:
  90     if "alias-of" in model:
  91         continue
  92     names.append(model["name"])
  93
  94 models = {}
  95
  96 for name in sorted(names):
  97     cpu = shell.cmd("query-cpu-model-expansion",
  98                      { "type": "static",
  99                        "model": { "name": name }})
 100
 101     got = {}
 102     for (feature, present) in cpu["return"]["model"]["props"].items():
 103         if present and feature not in skip:
 104             got[feature] = True
 105
 106     if name in ["host", "max", "base"]:
 107         continue
 108
 109     models[name] = {
 110         # Dict of all present features in this CPU model
 111         "features": got,
 112
 113         # Whether each x86-64 ABI level is satisfied
 114         "levels": [False, False, False, False],
 115
 116         # Number of extra CPUID features compared to the x86-64 ABI level
 117         "distance":[-1, -1, -1, -1],
 118
 119         # CPUID features present in model, but not in ABI level
 120         "delta":[[], [], [], []],
 121
 122         # CPUID features in ABI level but not present in model
 123         "missing": [[], [], [], []],
 124     }
 125
 126
 127 # Calculate whether the CPU models satisfy each ABI level
 128 for name in models.keys():
 129     for level in range(len(levels)):
 130         got = set(models[name]["features"])
 131         want = set(levels[level])
 132         missing = want - got
 133         match = True
 134         if len(missing) > 0:
 135             match = False
 136         models[name]["levels"][level] = match
 137         models[name]["missing"][level] = missing
 138
 139 # Cache list of CPU models satisfying each ABI level
 140 abi_models = [
 141     [],
 142     [],
 143     [],
 144     [],
 145 ]
 146
 147 for name in models.keys():
 148     for level in range(len(levels)):
 149         if models[name]["levels"][level]:
 150             abi_models[level].append(name)
 151
 152
 153 for level in range(len(abi_models)):
 154     # Find the union of features in all CPU models satisfying this ABI
 155     allfeatures = {}
 156     for name in abi_models[level]:
 157         for feat in models[name]["features"]:
 158             allfeatures[feat] = True
 159
 160     # Find the intersection of features in all CPU models satisfying this ABI
 161     commonfeatures = []
 162     for feat in allfeatures:
 163         present = True
 164         for name in models.keys():
 165             if not models[name]["levels"][level]:
 166                 continue
 167             if feat not in models[name]["features"]:
 168                 present = False
 169         if present:
 170             commonfeatures.append(feat)
 171
 172     # Determine how many extra features are present compared to the lowest
 173     # common denominator
 174     for name in models.keys():
 175         if not models[name]["levels"][level]:
 176             continue
 177
 178         delta = set(models[name]["features"].keys()) - set(commonfeatures)
 179         models[name]["distance"][level] = len(delta)
 180         models[name]["delta"][level] = delta
 181
 182 def print_uarch_abi_csv():
 183     print("# Automatically generated from '%s'" % __file__)
 184     print("Model,baseline,v2,v3,v4")
 185     for name in models.keys():
 186         print(name, end="")
 187         for level in range(len(levels)):
 188             if models[name]["levels"][level]:
 189                 print(",✅", end="")
 190             else:
 191                 print(",", end="")
 192         print()
 193
 194 print_uarch_abi_csv()