/measurements/MUL_decode_latency.ipynb

MUL_decode_latency.ipynb

{
  "cells": [
    {
      "metadata": {
        "slideshow": {
          "slide_type": "-"
        }
      },
      "cell_type": "markdown",
      "source": "# Init"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "#importing Pandas\nimport pandas as pd\n#importing plotly and cufflinks in offline mode for dataframe-based plotting\nimport cufflinks as cf\nimport plotly.offline\ncf.go_offline()\ncf.set_config_file(offline=True, world_readable=True)",
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": "        <script type=\"text/javascript\">\n        window.PlotlyConfig = {MathJaxConfig: 'local'};\n        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n        if (typeof require !== 'undefined') {\n        require.undef(\"plotly\");\n        requirejs.config({\n            paths: {\n                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n            }\n        });\n        require(['plotly'], function(Plotly) {\n            window._Plotly = Plotly;\n        });\n        }\n        </script>\n        "
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": "        <script type=\"text/javascript\">\n        window.PlotlyConfig = {MathJaxConfig: 'local'};\n        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n        if (typeof require !== 'undefined') {\n        require.undef(\"plotly\");\n        requirejs.config({\n            paths: {\n                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n            }\n        });\n        require(['plotly'], function(Plotly) {\n            window._Plotly = Plotly;\n        });\n        }\n        </script>\n        "
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": "        <script type=\"text/javascript\">\n        window.PlotlyConfig = {MathJaxConfig: 'local'};\n        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n        if (typeof require !== 'undefined') {\n        require.undef(\"plotly\");\n        requirejs.config({\n            paths: {\n                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n            }\n        });\n        require(['plotly'], function(Plotly) {\n            window._Plotly = Plotly;\n        });\n        }\n        </script>\n        "
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import logzero",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "from logzero import logger\nlogger.setLevel(\"WARN\")",
      "execution_count": 3,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import os\nimport getpass\nimport tempfile\nimport subprocess",
      "execution_count": 4,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "from tqdm import tqdm",
      "execution_count": 5,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import numpy as np\nfrom matplotlib import pyplot as plt",
      "execution_count": 6,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "with open(os.path.expanduser(\"~/mydoom.txt\"), \"r\") as pwdfile:\n    password = pwdfile.read()",
      "execution_count": 7,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def nanoBench_sudo(command):\n    # insert kernel module\n    command = command.split()\n\n    cmd1 = subprocess.Popen(['echo',password], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n    cmd2 = subprocess.Popen(['sudo','-S'] + command, cwd=\"../nanoBench/\", stdin=cmd1.stdout, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n    #print(cmd1.stderr.read().decode())\n\n    #print(cmd1.stdout.read().decode())\n\n    print(cmd2.stderr.read().decode())\n\n    print(cmd2.stdout.read().decode())",
      "execution_count": 8,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# insert kernel module\nnanoBench_sudo(\"insmod ./kernel/nb.ko\")",
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": "[sudo] password for xren: insmod: ERROR: could not insert module ./kernel/nb.ko: File exists\n\n\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# disable HyperThreading\nnanoBench_sudo(\"./disable-HT.sh\")",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": "\n\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def attempt_round(f, tolerance=1/10000):\n    \"\"\"\n    Attempt to round float to integer with tolerance.\n    \n    Fixes cosmetic problem of e.g. 1000 displaying as 9999.999999999\n    \"\"\"\n    f = float(f)\n    if abs(f-round(f)) < tolerance:\n        return round(f)\n    else:\n        print(f\"attempt_round failed for {f}\")\n        return f",
      "execution_count": 11,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import sys",
      "execution_count": 12,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "sys.version",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 13,
          "data": {
            "text/plain": "'3.7.5 (default, Nov 20 2019, 09:21:52) \\n[GCC 9.2.1 20191008]'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "loop_count = 3000",
      "execution_count": 14,
      "outputs": []
    },
    {
      "metadata": {
        "scrolled": true,
        "trusted": true
      },
      "cell_type": "code",
      "source": "with tempfile.TemporaryDirectory(prefix=\"nb_measure_\") as td:\n    print(td+\"/ll\")",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": "/tmp/nb_measure_5gag230i/ll\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "import pandas as pd",
      "execution_count": 16,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Measure function"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def measure(\n    asm,\n    unroll_count,\n    loop_count = loop_count,\n    warm_up_count=100,\n    n_measurements=30,\n    per_block=False,\n    config = None,):\n    \n    if os.path.isfile(config):\n        with open(config) as f:\n            config = f.read()\n    \n    with tempfile.TemporaryDirectory(prefix=\"nb_measure_\") as td:\n        logger.debug(f\"Temp directory: {td}\")\n        \n        with open(td+\"/config.txt\", \"w\") as config_file:\n            config_file.write(config)\n        \n        with open(td+\"/code.nasm\", \"w\") as nasm_file:\n            nasm_file.write(\"BITS 64\\n\"+asm)\n            \n        subprocess.check_call(\n            [\n                \"nasm\",\n                \"-f\",\n                \"bin\",\n                nasm_file.name,\n                \"-o\",\n                td+\"/code.bin\"\n            ]\n        )\n        \n        with open(td+\"/code.bin\", \"rb\") as code_binary_file:\n            code_bytes = code_binary_file.read()\n            logger.debug(f\"Code length: {len(code_bytes)}\")\n\n        args = [\"-median\", \"-basic_mode\"]\n\n        kwargs = dict(\n            unroll_count = unroll_count,\n            loop_count = loop_count,\n            warm_up_count = warm_up_count,\n            n_measurements = n_measurements,\n            config = td + \"/config.txt\",\n            code = td+\"/code.bin\"\n        )\n\n\n        l_kwargs = []\n        for k, v in kwargs.items():\n            l_kwargs.append(\"-\"+k)\n            l_kwargs.append(str(v))\n\n\n\n        command = [\n            \"../nanoBench/kernel-nanoBench.sh\",\n            *l_kwargs,\n            *args]\n\n        cmd1 = subprocess.Popen(['echo',password], stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n        cmd2 = subprocess.Popen(['sudo','-S'] + command, cwd=\"../nanoBench/\", stdin=cmd1.stdout, stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n\n        output = cmd2.stdout.read().decode()\n\n        try:\n            d = dict(\n                i for i in map(lambda x: x.split(\": \"), output.split(\"\\n\"))\n                if len(i) == 2\n            )\n            \n            float(d[\"RDTSC\"])\n        except:\n            print(\"Error:\")\n            print(\"Sudo stderr:\" + cmd1.stderr.read().decode())\n\n            print(\"Nanobench stderr:\" +cmd2.stderr.read().decode())\n        \n        \n        \n        d = {k: float(v) for k,v in d.items()}\n\n        if not per_block:\n            d = {k: attempt_round(loop_count*unroll_count*v) for k,v in d.items()}\n\n        return d\n        return (d[\"IDQ.DSB_UOPS\"], d[\"IDQ.MITE_UOPS\"], d[\"DSB2MITE_SWITCHES.PENALTY_CYCLES\"])",
      "execution_count": 17,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## NOPs padded to length\nwith prefices"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def nop_66(length, assembler = \"nasm\"):\n    assert length >= 1\n    if assembler == \"gas\" or assembler == \"as\":\n        return \".byte \" + \"0x66, \" * (length - 1) + \"0x90\"\n    elif assembler == \"nasm\":\n        return \"db \" + \"66H, \" * (length - 1) + \"90H\"\n\ndef nop_3E(length):\n    assert length >= 1\n    return \".byte \" + \"0x3E, \" * (length - 1) + \"0x90\"",
      "execution_count": 18,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "nop_66(3)",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": "'db 66H, 66H, 90H'"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## MSR Setup"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "\n\ncfg1 = \"\"\"\n# Performance monitoring events for processors based on Skylake, Kaby Lake and Coffee Lake microarchitectures.\n# Applies to processors with DisplayFamily_DisplayModel of 06_4EH, 06_5EH, 06_8EH, and 06_9EH.\n# See Table 19-5 of Intel's \"System Programming Guide\" (Jan. 2019)\n\n\n79.08 IDQ.DSB_UOPS\n79.04 IDQ.MITE_UOPS\n79.18.CMSK=1 IDQ.ALL_DSB_CYCLES_ANY_UOPS\n87.01 ILD_STALL.LCP\n\"\"\"\n",
      "execution_count": 20,
      "outputs": []
    },
    {
      "metadata": {
        "slideshow": {
          "slide_type": "slide"
        }
      },
      "cell_type": "markdown",
      "source": "The assembly code to use"
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Only Mul instructions"
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "measure mul instructions to confirm that they decode into 3 uops."
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "d = measure(\n        \"MUL RAX\",\n        unroll_count=100,\n        per_block=1,\n        config=cfg1,\n        loop_count=300, warm_up_count=50)\nd",
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 21,
          "data": {
            "text/plain": "{'RDTSC': 2.31,\n 'Instructions retired': 1.02,\n 'Core cycles': 3.01,\n 'Reference cycles': 2.31,\n 'IDQ.DSB_UOPS': 0.0,\n 'IDQ.MITE_UOPS': 2.01,\n 'IDQ.ALL_DSB_CYCLES_ANY_UOPS': 0.0,\n 'ILD_STALL.LCP': 0.0}"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "d = measure(\n        \"MUL RAX\",\n        unroll_count=100,\n        per_block=1,\n        config=cfg1,\n        loop_count=300, warm_up_count=50)\nd",
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 22,
          "data": {
            "text/plain": "{'RDTSC': 2.23,\n 'Instructions retired': 1.02,\n 'Core cycles': 3.02,\n 'Reference cycles': 2.23,\n 'IDQ.DSB_UOPS': 0.0,\n 'IDQ.MITE_UOPS': 2.01,\n 'IDQ.ALL_DSB_CYCLES_ANY_UOPS': 0.0,\n 'ILD_STALL.LCP': 0.0}"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Measuring & Graphing"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def jumpaddr(n, opcode_length):\n    addr_length = 4\n    jump_addr = n * 32 - (opcode_length + addr_length)\n    jump_bytes = [0]*4 # 4-byte address\n    for i in range(4):\n        jump_bytes[i] = jump_addr // (0x100 ** i) % 0x100\n    tobyte = lambda x: \"{0:#0{1}x}\".format(x,4)\n    \n    \n    return \", \".join(list(map(tobyte,jump_bytes)))",
      "execution_count": 23,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def jumpblock(n):\n    jumpins = \"db 0xE9, \"+jumpaddr(n,opcode_length=1)\n    return f\"\"\"\n    {jumpins}\n    {nop_66(12)}\n    {nop_66(15)}\n\"\"\"",
      "execution_count": 24,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def jumpblock_66(n):\n    prefix = \"0x66, \"*10 # 10 byte prefix + 1 byte jump op + 4 byte jump addr = 15 byte max ins length\n    jumpins = \"db \" + prefix+ \"0xE9, \"+jumpaddr(n, opcode_length=11)\n    return f\"\"\"\n    {jumpins}\n    {nop_66(15)}\n    {nop_66(2)}\n\"\"\"",
      "execution_count": 25,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def jumpblock_mul32(n):\n    prefix = \"0xF7, 0xE0, \"\n    jumpins = \"db \" + prefix+ \"0xE9, \"+jumpaddr(n, opcode_length=3)\n    return f\"\"\"\n    \n    {jumpins}\n    {nop_66(15)}\n    {nop_66(10)}\n\"\"\" # 2+1+4+15+10=32",
      "execution_count": 26,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "nopblock =f\"\"\"\n    {nop_66(5)}\n    {nop_66(12)}\n    {nop_66(15)}\n\"\"\"",
      "execution_count": 27,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def suffix_keys(d, suffix):\n    return {\"\".join((k,suffix)):v for k,v in d.items()}",
      "execution_count": 28,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "\n\ncfg_dsb_uops_only = \"\"\"\n79.08 IDQ.DSB_UOPS\n\"\"\"\n\ndef diff(body, spacer, body_rpt):\n    d_0 = measure(\n        body*body_rpt +body*body_rpt,\n        unroll_count=1,\n        per_block=1,\n        config=cfg1,\n        loop_count=3000)\n    d_0 = suffix_keys(d_0, \"_0\")\n    \n    d_1 = measure(\n        body*body_rpt + spacer + body*body_rpt,\n        unroll_count=1,\n        per_block=1,\n        config=cfg1,\n        loop_count=3000)\n    d_1 = suffix_keys(d_1, \"_1\")\n    \n    d = {**d_0, **d_1}\n    \n    d[\"BODY_RPT\"] = body_rpt\n    return d",
      "execution_count": 29,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def difftable(body, spacer, rpt_max, even_rpt_only=False):\n    rpt_range = range(0,rpt_max, 2 if even_rpt_only else 1)\n    df = (diff(body, spacer, i) for i in tqdm(rpt_range))\n    df = pd.DataFrame.from_records(df)\n    return df\n        ",
      "execution_count": 30,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "def comparison_graph(df, name):\n    df1= pd.DataFrame()\n    df1[\"BODY_RPT\"] = df[\"BODY_RPT\"]\n    df1=df1.set_index(\"BODY_RPT\",drop=True)\n    df1[\"v0\"] = df[f\"{name}_0\"]\n    df1[\"v1\"] = df[f\"{name}_1\"]\n    df1.iplot()",
      "execution_count": 31,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Test on one-set zebras"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "\n\nasm1 = jumpblock(32)*32\ndf1=difftable(asm1, nopblock, 8, even_rpt_only=False)\ndf1\n",
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": "100%|██████████| 8/8 [00:00<00:00, 11.32it/s]\n",
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "execution_count": 32,
          "data": {
            "text/plain": "   RDTSC_0  Instructions retired_0  Core cycles_0  Reference cycles_0  \\\n0     0.65                     2.0           1.01                0.66   \n1     2.50                     4.0           3.01                2.52   \n2     5.26                     6.0           6.32                5.26   \n3     7.56                     8.0          10.98                7.55   \n4    10.32                    10.0          14.98               10.35   \n5    13.09                    12.0          20.97               13.09   \n6    16.20                    14.0          25.97               16.21   \n7    18.70                    16.0          29.97               18.70   \n\n   IDQ.DSB_UOPS_0  IDQ.MITE_UOPS_0  IDQ.ALL_DSB_CYCLES_ANY_UOPS_0  \\\n0            1.01             1.01                           1.01   \n1            3.01             3.01                           3.01   \n2            5.00             6.00                           5.00   \n3            7.00            10.99                           7.00   \n4            7.58            13.57                           7.58   \n5            7.35            17.34                           7.35   \n6            6.32            19.29                           6.32   \n7            5.72            20.70                           5.72   \n\n   ILD_STALL.LCP_0  RDTSC_1  Instructions retired_1  Core cycles_1  \\\n0              0.0     1.43                     5.0           2.00   \n1              0.0     3.33                     7.0           4.00   \n2              0.0     4.13                     9.0           6.00   \n3              0.0     5.51                    11.0           8.00   \n4              0.0     6.24                    13.0          10.00   \n5              0.0     8.11                    15.0          13.00   \n6              0.0    10.61                    17.0          16.99   \n7              0.0    14.34                    19.0          22.99   \n\n   Reference cycles_1  IDQ.DSB_UOPS_1  IDQ.MITE_UOPS_1  \\\n0                1.41            4.01             1.01   \n1                3.35            6.01             3.02   \n2                4.15            8.00             6.33   \n3                5.53           10.01             7.01   \n4                6.25           12.00            11.00   \n5                8.11           14.00            14.00   \n6               10.60           16.00            20.99   \n7               14.36           18.00            23.00   \n\n   IDQ.ALL_DSB_CYCLES_ANY_UOPS_1  ILD_STALL.LCP_1  BODY_RPT  \n0                            1.0              0.0         0  \n1                            3.0              0.0         1  \n2                            5.0              0.0         2  \n3                            7.0              0.0         3  \n4                            9.0              0.0         4  \n5                           11.0              0.0         5  \n6                           13.0              0.0         6  \n7                           15.0              0.0         7  ",
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>RDTSC_0</th>\n      <th>Instructions retired_0</th>\n      <th>Core cycles_0</th>\n      <th>Reference cycles_0</th>\n      <th>IDQ.DSB_UOPS_0</th>\n      <th>IDQ.MITE_UOPS_0</th>\n      <th>IDQ.ALL_DSB_CYCLES_ANY_UOPS_0</th>\n      <th>ILD_STALL.LCP_0</th>\n      <th>RDTSC_1</th>\n      <th>Instructions retired_1</th>\n      <th>Core cycles_1</th>\n      <th>Reference cycles_1</th>\n      <th>IDQ.DSB_UOPS_1</th>\n      <th>IDQ.MITE_UOPS_1</th>\n      <th>IDQ.ALL_DSB_CYCLES_ANY_UOPS_1</th>\n      <th>ILD_STALL.LCP_1</th>\n      <th>BODY_RPT</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.65</td>\n      <td>2.0</td>\n      <td>1.01</td>\n      <td>0.66</td>\n      <td>1.01</td>\n      <td>1.01</td>\n      <td>1.01</td>\n      <td>0.0</td>\n      <td>1.43</td>\n      <td>5.0</td>\n      <td>2.00</td>\n      <td>1.41</td>\n      <td>4.01</td>\n      <td>1.01</td>\n      <td>1.0</td>\n      <td>0.0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2.50</td>\n      <td>4.0</td>\n      <td>3.01</td>\n      <td>2.52</td>\n      <td>3.01</td>\n      <td>3.01</td>\n      <td>3.01</td>\n      <td>0.0</td>\n      <td>3.33</td>\n      <td>7.0</td>\n      <td>4.00</td>\n      <td>3.35</td>\n      <td>6.01</td>\n      <td>3.02</td>\n      <td>3.0</td>\n      <td>0.0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>5.26</td>\n      <td>6.0</td>\n      <td>6.32</td>\n      <td>5.26</td>\n      <td>5.00</td>\n      <td>6.00</td>\n      <td>5.00</td>\n      <td>0.0</td>\n      <td>4.13</td>\n      <td>9.0</td>\n      <td>6.00</td>\n      <td>4.15</td>\n      <td>8.00</td>\n      <td>6.33</td>\n      <td>5.0</td>\n      <td>0.0</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>7.56</td>\n      <td>8.0</td>\n      <td>10.98</td>\n      <td>7.55</td>\n      <td>7.00</td>\n      <td>10.99</td>\n      <td>7.00</td>\n      <td>0.0</td>\n      <td>5.51</td>\n      <td>11.0</td>\n      <td>8.00</td>\n      <td>5.53</td>\n      <td>10.01</td>\n      <td>7.01</td>\n      <td>7.0</td>\n      <td>0.0</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>10.32</td>\n      <td>10.0</td>\n      <td>14.98</td>\n      <td>10.35</td>\n      <td>7.58</td>\n      <td>13.57</td>\n      <td>7.58</td>\n      <td>0.0</td>\n      <td>6.24</td>\n      <td>13.0</td>\n      <td>10.00</td>\n      <td>6.25</td>\n      <td>12.00</td>\n      <td>11.00</td>\n      <td>9.0</td>\n      <td>0.0</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>13.09</td>\n      <td>12.0</td>\n      <td>20.97</td>\n      <td>13.09</td>\n      <td>7.35</td>\n      <td>17.34</td>\n      <td>7.35</td>\n      <td>0.0</td>\n      <td>8.11</td>\n      <td>15.0</td>\n      <td>13.00</td>\n      <td>8.11</td>\n      <td>14.00</td>\n      <td>14.00</td>\n      <td>11.0</td>\n      <td>0.0</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>16.20</td>\n      <td>14.0</td>\n      <td>25.97</td>\n      <td>16.21</td>\n      <td>6.32</td>\n      <td>19.29</td>\n      <td>6.32</td>\n      <td>0.0</td>\n      <td>10.61</td>\n      <td>17.0</td>\n      <td>16.99</td>\n      <td>10.60</td>\n      <td>16.00</td>\n      <td>20.99</td>\n      <td>13.0</td>\n      <td>0.0</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>18.70</td>\n      <td>16.0</td>\n      <td>29.97</td>\n      <td>18.70</td>\n      <td>5.72</td>\n      <td>20.70</td>\n      <td>5.72</td>\n      <td>0.0</td>\n      <td>14.34</td>\n      <td>19.0</td>\n      <td>22.99</td>\n      <td>14.36</td>\n      <td>18.00</td>\n      <td>23.00</td>\n      <td>15.0</td>\n      <td>0.0</td>\n      <td>7</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "asm2 = jumpblock_mul32(32)*32\ndf2=difftable(asm2, nopblock, 8, even_rpt_only=False)\ndf2",
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": "100%|██████████| 8/8 [00:00<00:00, 10.77it/s]\n",
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "execution_count": 33,
          "data": {
            "text/plain": "   RDTSC_0  Instructions retired_0  Core cycles_0  Reference cycles_0  \\\n0     0.65                     2.0           1.01                0.66   \n1     6.29                     6.0           8.50                6.28   \n2    12.96                    10.0          16.88               12.95   \n3    15.74                    14.0          25.24               15.74   \n4    21.76                    18.0          33.79               21.77   \n5    26.32                    22.0          42.18               26.31   \n6    31.30                    26.0          50.16               31.29   \n7    36.69                    30.0          58.80               36.69   \n\n   IDQ.DSB_UOPS_0  IDQ.MITE_UOPS_0  IDQ.ALL_DSB_CYCLES_ANY_UOPS_0  \\\n0            1.01             1.01                           1.01   \n1            9.01             8.50                           3.00   \n2           17.02            16.88                           5.00   \n3           25.02            25.24                           7.00   \n4           26.71            31.85                           7.27   \n5           26.86            38.35                           7.16   \n6           27.34            44.37                           7.20   \n7           27.71            51.02                           7.28   \n\n   ILD_STALL.LCP_0  RDTSC_1  Instructions retired_1  Core cycles_1  \\\n0              0.0     1.38                     5.0           2.00   \n1              0.0     6.34                     9.0           8.57   \n2              0.0    11.28                    13.0          16.95   \n3              0.0    15.87                    17.0          25.45   \n4              0.0    21.03                    21.0          33.71   \n5              0.0    26.41                    25.0          42.33   \n6              0.0    31.37                    29.0          50.26   \n7              0.0    35.67                    33.0          58.94   \n\n   Reference cycles_1  IDQ.DSB_UOPS_1  IDQ.MITE_UOPS_1  \\\n0                1.38            4.01             1.01   \n1                6.34           12.02             8.57   \n2               11.29           20.01            16.98   \n3               15.88           28.02            25.49   \n4               21.03           36.02            33.73   \n5               26.42           44.02            42.45   \n6               31.37           52.01            50.32   \n7               35.69           60.00            58.93   \n\n   IDQ.ALL_DSB_CYCLES_ANY_UOPS_1  ILD_STALL.LCP_1  BODY_RPT  \n0                           1.00              0.0         0  \n1                           3.01              0.0         1  \n2                           5.00              0.0         2  \n3                           7.01              0.0         3  \n4                           9.01              0.0         4  \n5                          11.01              0.0         5  \n6                          13.00              0.0         6  \n7                          15.00              0.0         7  ",
            "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>RDTSC_0</th>\n      <th>Instructions retired_0</th>\n      <th>Core cycles_0</th>\n      <th>Reference cycles_0</th>\n      <th>IDQ.DSB_UOPS_0</th>\n      <th>IDQ.MITE_UOPS_0</th>\n      <th>IDQ.ALL_DSB_CYCLES_ANY_UOPS_0</th>\n      <th>ILD_STALL.LCP_0</th>\n      <th>RDTSC_1</th>\n      <th>Instructions retired_1</th>\n      <th>Core cycles_1</th>\n      <th>Reference cycles_1</th>\n      <th>IDQ.DSB_UOPS_1</th>\n      <th>IDQ.MITE_UOPS_1</th>\n      <th>IDQ.ALL_DSB_CYCLES_ANY_UOPS_1</th>\n      <th>ILD_STALL.LCP_1</th>\n      <th>BODY_RPT</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0.65</td>\n      <td>2.0</td>\n      <td>1.01</td>\n      <td>0.66</td>\n      <td>1.01</td>\n      <td>1.01</td>\n      <td>1.01</td>\n      <td>0.0</td>\n      <td>1.38</td>\n      <td>5.0</td>\n      <td>2.00</td>\n      <td>1.38</td>\n      <td>4.01</td>\n      <td>1.01</td>\n      <td>1.00</td>\n      <td>0.0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>6.29</td>\n      <td>6.0</td>\n      <td>8.50</td>\n      <td>6.28</td>\n      <td>9.01</td>\n      <td>8.50</td>\n      <td>3.00</td>\n      <td>0.0</td>\n      <td>6.34</td>\n      <td>9.0</td>\n      <td>8.57</td>\n      <td>6.34</td>\n      <td>12.02</td>\n      <td>8.57</td>\n      <td>3.01</td>\n      <td>0.0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>12.96</td>\n      <td>10.0</td>\n      <td>16.88</td>\n      <td>12.95</td>\n      <td>17.02</td>\n      <td>16.88</td>\n      <td>5.00</td>\n      <td>0.0</td>\n      <td>11.28</td>\n      <td>13.0</td>\n      <td>16.95</td>\n      <td>11.29</td>\n      <td>20.01</td>\n      <td>16.98</td>\n      <td>5.00</td>\n      <td>0.0</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>15.74</td>\n      <td>14.0</td>\n      <td>25.24</td>\n      <td>15.74</td>\n      <td>25.02</td>\n      <td>25.24</td>\n      <td>7.00</td>\n      <td>0.0</td>\n      <td>15.87</td>\n      <td>17.0</td>\n      <td>25.45</td>\n      <td>15.88</td>\n      <td>28.02</td>\n      <td>25.49</td>\n      <td>7.01</td>\n      <td>0.0</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>21.76</td>\n      <td>18.0</td>\n      <td>33.79</td>\n      <td>21.77</td>\n      <td>26.71</td>\n      <td>31.85</td>\n      <td>7.27</td>\n      <td>0.0</td>\n      <td>21.03</td>\n      <td>21.0</td>\n      <td>33.71</td>\n      <td>21.03</td>\n      <td>36.02</td>\n      <td>33.73</td>\n      <td>9.01</td>\n      <td>0.0</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>26.32</td>\n      <td>22.0</td>\n      <td>42.18</td>\n      <td>26.31</td>\n      <td>26.86</td>\n      <td>38.35</td>\n      <td>7.16</td>\n      <td>0.0</td>\n      <td>26.41</td>\n      <td>25.0</td>\n      <td>42.33</td>\n      <td>26.42</td>\n      <td>44.02</td>\n      <td>42.45</td>\n      <td>11.01</td>\n      <td>0.0</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>31.30</td>\n      <td>26.0</td>\n      <td>50.16</td>\n      <td>31.29</td>\n      <td>27.34</td>\n      <td>44.37</td>\n      <td>7.20</td>\n      <td>0.0</td>\n      <td>31.37</td>\n      <td>29.0</td>\n      <td>50.26</td>\n      <td>31.37</td>\n      <td>52.01</td>\n      <td>50.32</td>\n      <td>13.00</td>\n      <td>0.0</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>36.69</td>\n      <td>30.0</td>\n      <td>58.80</td>\n      <td>36.69</td>\n      <td>27.71</td>\n      <td>51.02</td>\n      <td>7.28</td>\n      <td>0.0</td>\n      <td>35.67</td>\n      <td>33.0</td>\n      <td>58.94</td>\n      <td>35.69</td>\n      <td>60.00</td>\n      <td>58.93</td>\n      <td>15.00</td>\n      <td>0.0</td>\n      <td>7</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "df1.loc[5].sort_index()",
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 34,
          "data": {
            "text/plain": "BODY_RPT                          5.00\nCore cycles_0                    20.97\nCore cycles_1                    13.00\nIDQ.ALL_DSB_CYCLES_ANY_UOPS_0     7.35\nIDQ.ALL_DSB_CYCLES_ANY_UOPS_1    11.00\nIDQ.DSB_UOPS_0                    7.35\nIDQ.DSB_UOPS_1                   14.00\nIDQ.MITE_UOPS_0                  17.34\nIDQ.MITE_UOPS_1                  14.00\nILD_STALL.LCP_0                   0.00\nILD_STALL.LCP_1                   0.00\nInstructions retired_0           12.00\nInstructions retired_1           15.00\nRDTSC_0                          13.09\nRDTSC_1                           8.11\nReference cycles_0               13.09\nReference cycles_1                8.11\nName: 5, dtype: float64"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "df2.loc[5].sort_index()",
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 35,
          "data": {
            "text/plain": "BODY_RPT                          5.00\nCore cycles_0                    42.18\nCore cycles_1                    42.33\nIDQ.ALL_DSB_CYCLES_ANY_UOPS_0     7.16\nIDQ.ALL_DSB_CYCLES_ANY_UOPS_1    11.01\nIDQ.DSB_UOPS_0                   26.86\nIDQ.DSB_UOPS_1                   44.02\nIDQ.MITE_UOPS_0                  38.35\nIDQ.MITE_UOPS_1                  42.45\nILD_STALL.LCP_0                   0.00\nILD_STALL.LCP_1                   0.00\nInstructions retired_0           22.00\nInstructions retired_1           25.00\nRDTSC_0                          26.32\nRDTSC_1                          26.41\nReference cycles_0               26.31\nReference cycles_1               26.42\nName: 5, dtype: float64"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "scrolled": false
      },
      "cell_type": "markdown",
      "source": "## MITE_UOPS"
    },
    {
      "metadata": {
        "scrolled": false,
        "trusted": true
      },
      "cell_type": "code",
      "source": "comparison_graph(df1, \"IDQ.MITE_UOPS\")",
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
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    {
      "metadata": {},
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      "source": "## RDTSC"
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    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Testing on 16-set zebras (all odd / even sets)"
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "asm1 = jumpblock(2)*2\ndf1=difftable(asm1, nopblock, 128, even_rpt_only=False)",
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": "100%|██████████| 128/128 [00:22<00:00,  5.58it/s]\n",
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "asm2 = jumpblock_mul32(2)*2\ndf2=difftable(asm2, nopblock, 128, even_rpt_only=False)",
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": "100%|██████████| 128/128 [00:40<00:00,  3.16it/s]\n",
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## MITE_UOPS"
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      "source": "comparison_graph(df1, \"IDQ.DSB_UOPS\")",
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