{"id":108705,"date":"2026-09-22T12:56:44","date_gmt":"2026-09-22T04:56:44","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/108705.html"},"modified":"2026-09-22T12:56:44","modified_gmt":"2026-09-22T04:56:44","slug":"%e5%8d%95%e5%85%83%e4%ba%8c-%c2%b7-%e5%86%85%e5%ad%98%e5%a2%99%ef%bc%9a%e6%9c%ba%e5%99%a8%e7%9a%84%e6%97%b6%e9%97%b4%e8%8a%b1%e5%9c%a8%e5%93%aa","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/108705.html","title":{"rendered":"\u5355\u5143\u4e8c \u00b7 \u5185\u5b58\u5899\uff1a\u673a\u5668\u7684\u65f6\u95f4\u82b1\u5728\u54ea"},"content":{"rendered":"

\u5bf9\u5e94\u6559\u6750：[[Optimized C++ Proven Techniques for Heightened Performance.pdf|Optimized C++]] ch2\u300cComputer Behavior Affecting Optimization\u300d
\n\u672c\u5355\u5143\u56de\u7b54：\u4e00\u6bb5\u4ee3\u7801\u6162\u4e86，\u65f6\u95f4\u5230\u5e95\u82b1\u5728\u54ea？\u4e3a\u4ec0\u4e48\u591a\u6570\u65f6\u5019\u7b54\u6848\u90fd\u662f\u540c\u4e00\u4e2a？
\n\u524d\u7f6e：[[\u5355\u514301-\u65f6\u95f4\u7684\u5f62\u72b6：\u5ef6\u8fdf\u3001\u541e\u5410\u4e0e\u5c3e\u5ef6\u8fdf]]（\u5206\u4f4d\u6570\u3001\u566a\u58f0\u4e0b\u9650\u3001\u53d6\u6700\u5c0f\u503c\u3001\u73af\u5883\u56db\u5143\u7ec4）
\n\u7f16\u8bd1\u8bf4\u660e：\u793a\u4f8b\u7edf\u4e00 g++ -std=c++23 -O2 -Wall -Wextra，\u5b9e\u8dd1\u4e8e g++ 15.2（Ubuntu），AMD Ryzen 9 7940H（Zen 4，8 \u6838 16 \u7ebf\u7a0b，L1d 32KB\/\u6838，L2 1MB\/\u6838，L3 16MB）\u3002\u4ee3\u7801\u5728 \u8bb2\u4e49\/code\/ \u4e0b\u3002<\/p>\n

0. \u672c\u5355\u5143\u5730\u56fe<\/h3>\n

\u5355\u5143\u4e00\u6559\u4f60\u91cf\u51c6\u4e00\u4e2a\u6570\u3002\u5355\u5143\u4e8c\u56de\u7b54\u91cf\u5b8c\u4e4b\u540e\u6700\u5e38\u9047\u5230\u7684\u90a3\u4e2a\u95ee\u9898：\u8fd9\u4e2a\u6570\u4e3a\u4ec0\u4e48\u8fd9\u4e48\u5927\u3002<\/p>\n

\u7b2c\u4e00\u8bb2 \u4e00\u6b21 miss \u503c\u51e0\u767e\u6761\u6307\u4ee4 1 ns \u548c 100 ns \u4e4b\u95f4\u90a3\u6761\u7ebf
\n\u7b2c\u4e8c\u8bb2 \u7f13\u5b58\u9636\u68af：\u53f0\u9636\u843d\u5728\u54ea 1 \u2192 2 \u2192 3 \u2192 5 \u2192 10 \u2192 34 \u2192 90 \u2192 106 ns
\n\u7b2c\u4e09\u8bb2 \u642c\u8fd0\u91cf\u76f8\u540c，\u901f\u7387\u5dee\u56db\u500d \u987a\u5e8f 45.6 GB\/s，\u968f\u673a 11.5 GB\/s
\n\u7b2c\u56db\u8bb2 \u786c\u4ef6\u6309\u884c\u8bb0\u8d26 \u5143\u7d20\u4ece 4 \u5b57\u8282\u957f\u5230 64 \u5b57\u8282，\u6162 16 \u500d
\n\u7b2c\u4e94\u8bb2 \u6539\u904d\u5386\u987a\u5e8f，\u4e0d\u6539\u6570\u636e\u7ed3\u6784 \u5217\u4f18\u5148\u6162 20 \u500d，\u5206\u5757\u4e00\u6539\u5c31\u56de\u6765\u4e86<\/p>\n

\u56db\u6761\u7ed3\u8bba\u4f9d\u6b21\u6536\u7d27：<\/p>\n

  • \u8bbf\u5b58\u6bd4\u8ba1\u7b97\u8d35\u4e24\u4e09\u4e2a\u6570\u91cf\u7ea7\u3002<\/li>\n
  • \u8d35\u7684\u7a0b\u5ea6\u53d6\u51b3\u4e8e\u6570\u636e\u5728\u54ea\u4e00\u7ea7\u7f13\u5b58\u91cc，\u800c\u6570\u636e\u5728\u54ea\u4e00\u7ea7\u53d6\u51b3\u4e8e\u5de5\u4f5c\u96c6\u591a\u5927\u3002<\/li>\n
  • \u5de5\u4f5c\u96c6\u4e00\u6837\u5927\u65f6，\u4ee3\u4ef7\u53d6\u51b3\u4e8e\u8bbf\u95ee\u987a\u5e8f\u80fd\u4e0d\u80fd\u88ab\u786c\u4ef6\u731c\u4e2d\u3002<\/li>\n
  • \u987a\u5e8f\u4e00\u6837\u65f6，\u4ee3\u4ef7\u53d6\u51b3\u4e8e\u4e00\u6b21\u8bbf\u95ee\u7528\u6389\u591a\u5c11\u5b57\u8282\u7684\u7f13\u5b58\u884c\u3002<\/li>\n

    \u56db\u8bb2\u4e4b\u540e，\u4f60\u4f1a\u62ff\u5230\u4e00\u628a\u5c3a\u5b50：\u770b\u5230\u4e00\u6bb5\u6162\u4ee3\u7801，\u5148\u95ee\u5b83\u78b0\u4e86\u591a\u5c11\u6761 cache line\u3002 \u8fd9\u4e2a\u6570\u5b57\u80fd\u89e3\u91ca\u7684\u6027\u80fd\u95ee\u9898，\u6bd4\u6240\u6709\u5176\u4ed6\u5355\u4e00\u56e0\u7d20\u52a0\u8d77\u6765\u8fd8\u591a\u3002<\/p>\n

    \u672c\u5355\u5143\u7684\u6d4b\u91cf\u6761\u4ef6：\u56db\u4e2a\u5b9e\u9a8c\u90fd\u5bf9\u8bbf\u5b58\u654f\u611f，\u4e0b\u9762\u7684\u6570\u5b57\u5168\u90e8\u7528 taskset -c 15 \u7ed1\u6838\u8dd1\u51fa\u3002\u7b2c\u4e00\u8bb2\u4f1a\u89e3\u91ca\u4e3a\u4ec0\u4e48\u5fc5\u987b\u8fd9\u4e48\u505a，\u4ee5\u53ca\u4e0d\u7ed1\u6838\u4f1a\u9519\u6210\u4ec0\u4e48\u6837\u3002<\/p>\n

    \u9664\u8ba1\u65f6\u4e4b\u5916，\u672c\u5355\u5143\u8fd8\u4f1a\u7528\u5230\u4e24\u7c7b\u8ba1\u6570\u5668：perf stat \u8bfb\u786c\u4ef6\u4e8b\u4ef6，valgrind –tool=cachegrind \u628a miss \u5f52\u5230\u51fd\u6570\u548c\u6e90\u7801\u884c\u3002\u4e24\u8005\u5404\u6709\u4e00\u6b21\u6027\u7684\u51c6\u5907\u52a8\u4f5c，\u89c1 B \u7ebf\u300c\u5148\u8bf4\u5de5\u5177\u300d\u3002\u8ba1\u6570\u5668\u8981\u914d\u7740\u8ba1\u65f6\u8bfb\u2014\u2014\u5b83\u6570\u7684\u662f\u642c\u8fd0\u91cf，\u4e0d\u544a\u8bc9\u4f60\u65f6\u95f4，\u800c\u8fd9\u4e00\u5355\u5143\u6240\u6709\u7684\u4ee3\u4ef7\u6700\u7ec8\u90fd\u8981\u843d\u56de\u65f6\u95f4\u4e0a\u3002<\/p>\n

    \u7b2c\u4e00\u8bb2 \u4e00\u6b21 miss \u503c\u51e0\u767e\u6761\u6307\u4ee4<\/h3>\n

    \u662f\u4ec0\u4e48<\/h4>\n

    CPU \u505a\u4e00\u6b21\u6574\u6570\u52a0\u6cd5，\u5728\u73b0\u4ee3 x86 \u4e0a\u5927\u7ea6 0.25 \u7eb3\u79d2\u3002\u4ece\u4e3b\u5b58\u53d6\u4e00\u4e2a\u6570，\u5927\u7ea6 100 \u7eb3\u79d2\u3002\u8fd9\u4e24\u4e2a\u6570\u5b57\u5dee 400 \u500d\u3002<\/p>\n

    \u628a\u5b83\u6362\u6210\u300cCPU \u80fd\u5728\u8fd9\u6bb5\u65f6\u95f4\u91cc\u5e72\u591a\u5c11\u6d3b\u300d，\u5c31\u662f\u5185\u5b58\u5899\u8fd9\u4e2a\u8bf4\u6cd5\u7684\u6765\u5386：\u4e00\u6b21\u4e3b\u5b58 miss \u7684\u65f6\u95f4\u91cc，CPU \u672c\u6765\u80fd\u7b97\u5b8c\u51e0\u767e\u6761\u6307\u4ee4\u3002 \u53ea\u8981\u6709\u4e00\u6761\u6307\u4ee4\u5728\u7b49\u4e3b\u5b58，\u540e\u9762\u51e0\u767e\u6761\u6307\u4ee4\u7684\u4f4d\u7f6e\u5c31\u7a7a\u7740\u3002<\/p>\n

    \u8fd9\u6761\u7ed3\u8bba\u628a\u6027\u80fd\u4f18\u5316\u7684\u7b2c\u4e00\u4e2a\u95ee\u9898\u6362\u6389\u4e86\u3002\u539f\u6765\u7684\u95ee\u9898\u662f\u300c\u8fd9\u6bb5\u4ee3\u7801\u6267\u884c\u4e86\u591a\u5c11\u6761\u6307\u4ee4\u300d，\u73b0\u5728\u7684\u95ee\u9898\u662f\u300c\u8fd9\u6bb5\u4ee3\u7801\u78b0\u4e86\u591a\u5c11\u6761\u4e0d\u5728\u7f13\u5b58\u91cc\u7684\u6570\u636e\u300d\u3002\u524d\u8005\u662f\u7f16\u8bd1\u5668\u7684\u4e8b，\u540e\u8005\u662f\u4f60\u7684\u4e8b\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u5dee\u8ddd\u4f1a\u62c9\u5f00\u5230\u51e0\u767e\u500d<\/h4>\n

    \u4e24\u4ef6\u4e8b\u7684\u7269\u7406\u539f\u7406\u4e0d\u4e00\u6837\u3002<\/p>\n

    CPU \u91cc\u8dd1\u7684\u662f\u6676\u4f53\u7ba1\u5f00\u5173，\u5f00\u5173\u4e00\u6b21\u7684\u80fd\u91cf\u5c0f\u3001\u8ddd\u79bb\u77ed\u3001\u6ca1\u6709\u673a\u68b0\u8fc7\u7a0b，\u6240\u4ee5\u4e3b\u9891\u80fd\u4ece\u51e0\u5146\u8d6b\u4e00\u8def\u63a8\u5230\u51e0\u5409\u8d6b\u3002DRAM \u91cc\u5b58\u7684\u662f\u7535\u5bb9\u4e0a\u7684\u7535\u8377，\u8bfb\u4e00\u6b21\u8981\u628a\u7535\u8377\u5f15\u51fa\u6765\u6bd4\u8f83，\u5199\u4e00\u6b21\u8981\u628a\u7535\u5bb9\u5145\u6ee1\u3002\u8fd9\u4e2a\u8fc7\u7a0b\u6709\u786e\u5b9a\u7684\u7269\u7406\u4e0b\u9650，\u4e0d\u662f\u5de5\u827a\u95ee\u9898\u3002<\/p>\n

    \u4ee3\u4ef7\u4f53\u73b0\u5728\u65f6\u5e8f\u4e0a：\u4e00\u6b21 DRAM \u8bbf\u95ee\u8981\u5148\u6fc0\u6d3b\u4e00\u6574\u884c（RAS），\u518d\u9009\u4e2d\u5217（CAS），\u7b49\u6570\u636e\u8bfb\u51fa，\u7136\u540e\u9884\u5145\u7535\u51c6\u5907\u4e0b\u4e00\u6b21\u3002\u6574\u4e2a\u6d41\u7a0b\u8d70\u5b8c\u662f\u51e0\u5341\u7eb3\u79d2，\u800c\u8fd9\u6bb5\u65f6\u95f4 CPU \u80fd\u8dd1\u51e0\u767e\u4e2a\u5468\u671f\u3002<\/p>\n

    \u7f13\u5b58\u7684\u5b58\u5728\u5c31\u662f\u4e3a\u4e86\u628a\u8fd9\u6761\u6162\u8def\u5f84\u6321\u4f4f\u3002CPU \u91cc\u653e\u51e0\u7ea7\u5bb9\u91cf\u9012\u589e\u3001\u901f\u5ea6\u9012\u51cf\u7684\u5b58\u50a8，\u8ba9\u5927\u591a\u6570\u8bbf\u95ee\u5728\u524d\u51e0\u7ea7\u5c31\u7ed3\u675f，\u53ea\u6709\u6321\u4e0d\u4f4f\u7684\u90a3\u4e9b\u624d\u843d\u5230\u4e3b\u5b58\u3002\u6240\u4ee5\u300c\u6162\u300d\u4e0d\u662f\u5747\u5300\u7684\u6162，\u662f\u5206\u7ea7\u7684\u6162\u2014\u2014\u5206\u7ea7\u7684\u7ed3\u679c\u5c31\u662f\u7b2c\u4e8c\u8bb2\u90a3\u6761\u9636\u68af\u3002<\/p>\n

    \u4ee3\u7801\u9010\u884c<\/h4>\n

    \u8bb2\u4e49\/code\/exp06_cache_ladder.cpp\u3002\u7528\u6307\u9488\u8ffd\u9010\u6d4b\u51fa\u56db\u7ea7\u8bbf\u5b58\u5404\u8981\u591a\u5c11\u7eb3\u79d2\u3002<\/p>\n

    \/\/ \u6784\u9020\u8986\u76d6\u5168\u90e8 N \u4e2a\u5143\u7d20\u7684\u968f\u673a\u5355\u73af<\/span>
    \nstd::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span> make_cycle<\/span>(<\/span>std::<\/span>size_t n,<\/span> std::<\/span>uint32_t<\/span> seed)<\/span> {<\/span>
    \n std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span> perm<\/span>(<\/span>n)<\/span>;<\/span>
    \n std::<\/span>iota<\/span>(<\/span>perm.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> perm.<\/span>end<\/span>(<\/span>)<\/span>,<\/span> 0u<\/span>)<\/span>;<\/span>
    \n std::<\/span>mt19937 rng<\/span>(<\/span>seed)<\/span>;<\/span>
    \n std::<\/span>shuffle<\/span>(<\/span>perm.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> perm.<\/span>end<\/span>(<\/span>)<\/span>,<\/span> rng)<\/span>;<\/span><\/p>\n

    std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span> next<\/span>(<\/span>n)<\/span>;<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t k =<\/span> 0<\/span>;<\/span> k <<\/span> n;<\/span> ++<\/span>k)<\/span> next[<\/span>perm[<\/span>k]<\/span>]<\/span> =<\/span> perm[<\/span>(<\/span>k +<\/span> 1<\/span>)<\/span> %<\/span> n]<\/span>;<\/span>
    \n return<\/span> next;<\/span>
    \n}<\/span><\/p>\n

    \u628a 0..n-1 \u6253\u4e71\u5f97\u5230\u4e00\u4e2a\u6392\u5217，\u7136\u540e\u8ba9 next[perm[k]] \u6307\u5411 perm[k+1]\u3002\u8fd9\u6837\u4ece\u4efb\u610f\u4e00\u70b9\u51fa\u53d1，\u6cbf\u7740 next \u4e00\u76f4\u8d70\u4f1a\u4e0d\u91cd\u4e0d\u6f0f\u5730\u7ecf\u8fc7\u6240\u6709\u5143\u7d20，\u6700\u540e\u56de\u5230\u8d77\u70b9\u2014\u2014\u4e00\u4e2a\u8986\u76d6\u5168\u6570\u7ec4\u7684\u5355\u73af\u3002<\/p>\n

    double<\/span> chase_ns<\/span>(<\/span>const<\/span> std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span>&<\/span> next,<\/span> std::<\/span>size_t steps)<\/span> {<\/span>
    \n std::<\/span>uint32_t<\/span> cur =<\/span> 0<\/span>;<\/span>
    \n \/\/ \u9884\u70ed：\u628a\u5de5\u4f5c\u96c6\u5c3d\u91cf\u8bfb\u8fdb\u7f13\u5b58，\u8ba9\u7ed3\u679c\u53cd\u6620\u7a33\u6001\u800c\u4e0d\u662f\u51b7\u542f\u52a8<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> steps \/<\/span> 4<\/span>;<\/span> ++<\/span>i)<\/span> cur =<\/span> next[<\/span>cur]<\/span>;<\/span><\/p>\n

    auto<\/span> t0 =<\/span> clk::<\/span>now<\/span>(<\/span>)<\/span>;<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> steps;<\/span> ++<\/span>i)<\/span> cur =<\/span> next[<\/span>cur]<\/span>;<\/span>
    \n auto<\/span> t1 =<\/span> clk::<\/span>now<\/span>(<\/span>)<\/span>;<\/span><\/p>\n

    volatile<\/span> std::<\/span>uint32_t<\/span> sink =<\/span> cur;<\/span> \/\/ \u9632\u6b62\u6574\u6bb5\u88ab\u4f18\u5316\u6389<\/span>
    \n (<\/span>void<\/span>)<\/span>sink;<\/span>
    \n return<\/span> std::<\/span>chrono::<\/span>duration<\/span><<\/span>double<\/span>,<\/span> std::<\/span>nano><\/span><\/span><\/span>(<\/span>t1 –<\/span> t0)<\/span>.<\/span>count<\/span>(<\/span>)<\/span> \/<\/span> static_cast<\/span><<\/span>double<\/span>><\/span><\/span><\/span>(<\/span>steps)<\/span>;<\/span>
    \n}<\/span><\/p>\n

    \u4e3a\u4ec0\u4e48\u7528\u6307\u9488\u8ffd\u9010\u800c\u4e0d\u662f\u6570\u7ec4\u904d\u5386\u3002 \u8fd9\u4e00\u6b65\u662f\u6574\u4e2a\u5b9e\u9a8c\u6210\u7acb\u7684\u524d\u63d0\u3002<\/p>\n

    \u6570\u7ec4\u987a\u5e8f\u904d\u5386\u662f\u53ef\u4ee5\u88ab\u9884\u53d6\u7684\u3002CPU \u770b\u5230\u4f60\u5728\u6309 p+1, p+2, p+3 \u8d70，\u5c31\u4f1a\u63d0\u524d\u628a\u540e\u9762\u51e0\u6761 cache line \u62c9\u8fdb\u6765\u3002\u7b49\u4f60\u8d70\u5230\u90a3\u4e00\u6b65\u65f6\u6570\u636e\u5df2\u7ecf\u5728\u7f13\u5b58\u91cc\u4e86，\u8fd9\u4e00\u6b21\u8bbf\u95ee\u91cf\u5230\u7684\u662f\u9884\u53d6\u5668\u7559\u4e0b\u4e86\u591a\u5c11\u63d0\u524d\u91cf，\u79bb\u8bbf\u5b58\u7684\u771f\u5b9e\u5ef6\u8fdf\u5df2\u7ecf\u5f88\u8fdc\u3002<\/p>\n

    \u6307\u9488\u8ffd\u9010\u7684\u6bcf\u4e00\u6b65\u5730\u5740\u4f9d\u8d56\u4e0a\u4e00\u6b65\u7684\u7ed3\u679c\u3002next[cur] \u91cc\u7684 cur \u662f\u4e0a\u4e00\u6b65\u8bfb\u51fa\u6765\u7684\u503c，\u786c\u4ef6\u5728\u8bfb\u5230\u4e4b\u524d\u6839\u672c\u4e0d\u77e5\u9053\u4e0b\u4e00\u4e2a\u5730\u5740\u5728\u54ea，\u9884\u53d6\u5668\u6ca1\u6709\u53ef\u9884\u6d4b\u7684\u8f93\u5165\u3002\u94fe\u6761\u4e0a\u7684\u6bcf\u4e00\u6b65\u90fd\u5fc5\u987b\u8001\u8001\u5b9e\u5b9e\u7b49\u3002<\/p>\n

    \u9884\u70ed\u90a3\u4e00\u884c\u662f\u4e3a\u4e86\u628a\u5de5\u4f5c\u96c6\u5148\u8bfb\u8fdb\u7f13\u5b58，\u8ba9\u8ba1\u65f6\u53cd\u6620\u7a33\u6001\u3002\u5355\u5143\u4e00\u7b2c\u56db\u8bb2\u91cf\u8fc7：\u4e0d\u9884\u70ed\u7684\u8bdd，\u7b2c\u4e00\u8f6e\u7684\u8bfb\u6570\u88ab\u51b7\u542f\u52a8\u6c61\u67d3，\u800c\u5de5\u4f5c\u96c6\u8d8a\u5927\u6c61\u67d3\u8d8a\u4e25\u91cd\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u9664\u4ee5 steps\u3002 \u5f97\u5230\u7684\u662f\u6bcf\u6b65\u7eb3\u79d2\u6570，\u4e5f\u5c31\u662f\u8be5\u5de5\u4f5c\u96c6\u4e0b\u7684\u8bbf\u5b58\u5ef6\u8fdf\u3002\u8fd9\u662f\u5168\u4e66\u7b2c\u4e00\u4e2a\u300c\u644a\u5230\u5355\u4f4d\u300d\u7684\u4f8b\u5b50\u2014\u2014\u4e0d\u644a\u5230\u5355\u4f4d，\u4e0d\u540c\u89c4\u6a21\u7684\u7ed3\u679c\u6ca1\u6cd5\u6bd4\u3002<\/p>\n

    \u4ee3\u7801\u8fd0\u884c\u7ed3\u679c<\/h4>\n

    $ taskset -c 15 .\/exp06_cache_ladder # \u8dd1\u4e09\u8f6e，\u6bcf\u4e00\u6863\u53d6\u6700\u5c0f\u503c<\/p>\n

    \u5de5\u4f5c\u96c6 \u5143\u7d20\u6570 \u6bcf\u6b65\u5ef6\u8fdf \u76f8\u5bf9 L1
    \n 16 KB 4096 1.04 ns 1.00x
    \n 64 KB 16384 2.14 ns 2.06x
    \n 256 KB 65536 2.94 ns 2.83x
    \n 512 KB 131072 3.83 ns 3.68x
    \n 1 MB 262144 5.36 ns 5.15x
    \n 4 MB 1048576 10.22 ns 9.83x
    \n 8 MB 2097152 11.86 ns 11.40x
    \n 16 MB 4194304 34.09 ns 32.78x
    \n 32 MB 8388608 67.14 ns 64.56x
    \n 64 MB 16777216 90.01 ns 86.55x
    \n 256 MB 67108864 106.39 ns 102.30x<\/p>\n

    \u4e24\u7aef\u5dee 102 \u500d，\u4e2d\u95f4\u7684\u8fc7\u6e21\u4e0d\u5e73\u6ed1\u2014\u2014\u6709\u53f0\u9636\u3002<\/p>\n

    \u5e38\u89c1\u5751<\/h4>\n

    \u5751\u4e00：\u5728\u6ca1\u7ed1\u6838\u3001\u673a\u5668\u53c8\u5728\u5fd9\u7684\u65f6\u5019\u8dd1\u3002 \u8fd9\u662f\u6700\u5bb9\u6613\u8e29\u7684\u4e00\u4e2a，\u56e0\u4e3a\u5b83\u4e0d\u62a5\u9519，\u53ea\u662f\u7ed9\u4f60\u4e00\u7ec4\u770b\u8d77\u6765\u6b63\u5e38\u5176\u5b9e\u9519\u5f97\u79bb\u8c31\u7684\u6570\u3002<\/p>\n

    \u540c\u4e00\u4efd exp06，\u5728\u8fd9\u53f0\u673a\u5668\u684c\u9762\u7a7a\u95f2\u4f46\u8d1f\u8f7d\u7ea6 3 \u7684\u65f6\u5019\u8dd1，512KB \u4e00\u6863\u62a5\u51fa 30.44 ns，4MB \u4e00\u6863\u62a5\u51fa 113.18 ns\u2014\u2014\u5206\u522b\u6bd4\u7ed1\u6838\u540e\u7684\u503c\u9ad8 8 \u500d\u548c 11 \u500d\u3002\u800c 16KB\u300164KB\u3001256MB \u4e09\u6863\u51e0\u4e4e\u6ca1\u53d7\u5f71\u54cd\u3002<\/p>\n

    \u539f\u56e0\u662f\u5c0f\u5de5\u4f5c\u96c6\u672c\u6765\u5c31\u5f85\u5728 L1\/L2 \u91cc，\u522b\u7684\u8fdb\u7a0b\u62a2\u6838\u53ea\u5f71\u54cd\u8c03\u5ea6\u4e0d\u5f71\u54cd\u7f13\u5b58；256MB \u672c\u6765\u5c31\u6bcf\u4e00\u6863\u90fd miss，\u591a\u51e0\u4e2a\u4e5f\u65e0\u6240\u8c13\u3002\u53d7\u5f71\u54cd\u7684\u6070\u597d\u662f\u4e2d\u95f4\u90a3\u51e0\u6863，\u4e5f\u5c31\u662f\u4f60\u6700\u5173\u5fc3\u7684\u90a3\u51e0\u6863\u3002\u5224\u65ad\u4e00\u4efd\u9636\u68af\u6570\u636e\u53ef\u4e0d\u53ef\u4fe1，\u5148\u770b\u5b83\u662f\u5426\u5355\u8c03\u3001\u662f\u5426\u5e73\u6ed1\u3002<\/p>\n

    taskset -c 15 .\/exp06_cache_ladder \u80fd\u628a\u5927\u90e8\u5206\u5e72\u6270\u6321\u6389\u3002<\/p>\n

    \u5751\u4e8c：\u53ea\u8dd1\u4e00\u8f6e\u3002 \u5355\u5143\u4e00\u7b2c\u56db\u8bb2\u91cf\u5230\u5355\u8f6e\u8bfb\u6570\u6296\u52a8\u7ea6 11%，\u672c\u673a\u8fd9\u6b21\u7684\u5b9e\u6d4b\u66f4\u6781\u7aef：8MB \u90a3\u4e00\u6863\u5728\u4e09\u8f6e\u91cc\u4ece 11.86 ns \u8df3\u5230 31.95 ns，\u5dee 2.7 \u500d\u3002\u7ed1\u6838\u4e5f\u538b\u4e0d\u4f4f，\u56e0\u4e3a\u8fd9\u4e00\u6863\u6b63\u597d\u538b\u5728 L3 \u5bb9\u91cf（16MB）\u4e0a，\u7f13\u5b58\u91cc\u591a\u653e\u4e00\u70b9\u5c11\u653e\u4e00\u70b9，\u7ed3\u679c\u5c31\u6362\u4e00\u4e2a\u6837\u3002<\/p>\n

    \u5904\u7406\u529e\u6cd5\u8fd8\u662f\u5355\u5143\u4e00\u90a3\u6761：\u591a\u8f6e\u53d6\u6700\u5c0f\u3002\u62a5\u6570\u7684\u65f6\u5019\u628a\u300c\u53d6\u4e86\u51e0\u8f6e\u300d\u4e00\u8d77\u62a5\u4e0a，\u8fd9\u662f\u5355\u5143\u4e00\u73af\u5883\u56db\u5143\u7ec4\u7684\u4e00\u90e8\u5206\u3002<\/p>\n

    \u5751\u4e09：\u628a\u6307\u9488\u8ffd\u9010\u7684\u7ed3\u8bba\u76f4\u63a5\u5957\u5230\u6570\u7ec4\u904d\u5386\u4e0a\u3002 \u6307\u9488\u8ffd\u9010\u91cf\u7684\u662f\u5ef6\u8fdf\u2014\u2014\u4e00\u6b65\u7b49\u4e00\u6b65，\u4e32\u884c\u3002\u6570\u7ec4\u904d\u5386\u901a\u5e38\u91cf\u7684\u662f\u541e\u5410\u2014\u2014\u5f88\u591a\u6b21\u8bbf\u95ee\u540c\u65f6\u5728\u98de\u3002\u8fd9\u4e24\u4e2a\u6570\u80fd\u5dee 20 \u500d，\u7b2c\u4e09\u8bb2\u4f1a\u628a\u8fd9\u4e2a\u5dee\u522b\u91cf\u51fa\u6765\u3002<\/p>\n

    \u6559\u6750\u6307\u5f15<\/h4>\n

    Guntheroth ch2\u3002\u8fd9\u4e00\u7ae0\u7ed9\u51fa\u5168\u4e66\u7684\u673a\u5668\u6a21\u578b，\u540e\u9762\u6bcf\u4e00\u7ae0\u7684\u4f18\u5316\u624b\u6cd5\u90fd\u80fd\u8ffd\u5230\u8fd9\u4e00\u7ae0\u7684\u67d0\u4e00\u6761\u4e0a\u3002<\/p>\n

    \u7b2c\u4e8c\u8bb2 \u7f13\u5b58\u9636\u68af：\u53f0\u9636\u843d\u5728\u54ea<\/h3>\n

    \u662f\u4ec0\u4e48<\/h4>\n

    \u4e0a\u4e00\u8bb2\u90a3\u5f20\u8868\u6709 11 \u884c\u3002\u628a\u5b83\u4eec\u6309\u53f0\u9636\u5206\u7ec4，\u5f97\u5230\u56db\u7ea7：<\/p>\n\n\u5c42\u7ea7\u672c\u673a\u6807\u79f0\u9636\u68af\u4e0a\u7684\u4f4d\u7f6e\u6bcf\u6b65\u5ef6\u8fdf<\/tr>\n\n\n\n\n\n
    L1d<\/td>\n32 KB\/\u6838<\/td>\n16 KB ~ 64 KB<\/td>\n1.04 ~ 2.14 ns<\/td>\n<\/tr>\n
    L2<\/td>\n1 MB\/\u6838<\/td>\n256 KB ~ 1 MB<\/td>\n2.94 ~ 5.36 ns<\/td>\n<\/tr>\n
    L3<\/td>\n16 MB（8 \u6838\u5171\u4eab）<\/td>\n4 MB ~ 16 MB<\/td>\n10.22 ~ 34.09 ns<\/td>\n<\/tr>\n
    \u4e3b\u5b58<\/td>\n\u2014<\/td>\n32 MB \u4ee5\u4e0a<\/td>\n67.14 ~ 106.39 ns<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4ece L1 \u5230\u4e3b\u5b58，\u5ef6\u8fdf\u6da8\u4e86 100 \u500d\u3002\u8fd9\u5c31\u662f\u300c\u6570\u636e\u5728\u54ea\u4e00\u7ea7\u300d\u8fd9\u4e2a\u95ee\u9898\u7684\u5168\u90e8\u4ef7\u503c\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u53f0\u9636\u843d\u5728\u8fd9\u4e9b\u4f4d\u7f6e<\/h4>\n

    \u53f0\u9636\u7684\u8fb9\u754c\u5c31\u662f\u6bcf\u4e00\u7ea7\u7684\u5bb9\u91cf\u3002\u5de5\u4f5c\u96c6\u4e00\u65e6\u8d85\u8fc7\u67d0\u4e00\u7ea7\u7684\u5bb9\u91cf，\u90a3\u4e00\u7ea7\u5c31\u88c5\u4e0d\u4e0b\u4e86，\u8bbf\u95ee\u5f00\u59cb\u5f80\u4e0b\u4e00\u7ea7\u6389，\u5ef6\u8fdf\u8df3\u4e00\u6863\u3002<\/p>\n

    \u4e09\u5904\u7ec6\u8282\u503c\u5f97\u62c6\u5f00\u3002<\/p>\n

    \u4e00\u3001L1 \u90a3\u4e00\u6863\u4e3a\u4ec0\u4e48\u4ece 1ns \u6da8\u5230 2ns \u5c31\u6709\u53f0\u9636\u3002 16KB \u5b8c\u5168\u88c5\u8fdb 32KB \u7684 L1，\u6bcf\u6b21\u8bbf\u95ee\u90fd\u662f L1 \u547d\u4e2d，1.04 ns \u7ea6\u7b49\u4e8e\u56db\u4e2a\u5468\u671f\u2014\u2014L1 \u7684\u8bbf\u95ee\u5ef6\u8fdf\u91cf\u7ea7\u3002\u5230 64KB \u65f6\u5df2\u7ecf\u8d85\u51fa L1 \u5bb9\u91cf，\u4e00\u90e8\u5206\u8bbf\u95ee\u6389\u5230 L2，\u5e73\u5747\u503c\u88ab\u62c9\u9ad8\u5230 2.14 ns\u3002\u8fd9\u4e0d\u662f\u300cL1 \u53d8\u6162\u4e86\u300d，\u662f\u300c\u4e00\u90e8\u5206\u8bbf\u95ee\u4e0d\u518d\u662f L1 \u4e86\u300d\u3002\u9636\u68af\u4e0a\u6bcf\u4e00\u4e2a\u70b9\u90fd\u662f\u6df7\u5408\u5e73\u5747\u503c，\u53ea\u4e0d\u8fc7\u5728\u53f0\u9636\u9644\u8fd1\u6df7\u5408\u6bd4\u4f8b\u53d8\u4e86\u3002<\/p>\n

    \u4e8c\u3001L2 \u5230 L3 \u90a3\u4e00\u6bb5\u4e3a\u4ec0\u4e48\u662f\u6e10\u53d8\u7684\u3002 1 MB \u662f 5.36 ns，4 MB \u662f 10.22 ns，8 MB \u662f 11.86 ns\u2014\u2014\u6da8\u5f97\u4e0d\u5feb\u3002\u56e0\u4e3a\u672c\u673a\u7684 L2 \u662f\u6bcf\u6838 1MB，L3 \u662f 8 \u6838\u5171\u4eab 16MB\u30021MB \u7684\u5de5\u4f5c\u96c6\u521a\u8d85\u51fa L2 \u65f6，L3 \u8fd8\u80fd\u8f7b\u677e\u515c\u4f4f，\u4ee3\u4ef7\u4ece L2 \u7684 5 ns \u6da8\u5230 L3 \u7684 10 ns，\u53ea\u7ffb\u4e00\u500d\u3002<\/p>\n

    \u4e09\u300116 MB \u5230 32 MB \u90a3\u4e00\u6b65\u4e3a\u4ec0\u4e48\u6700\u9661\u3002 16 MB \u662f 34.09 ns，32 MB \u662f 67.14 ns，\u7ffb\u4e00\u500d\u3002\u56e0\u4e3a 16MB \u6b63\u597d\u7b49\u4e8e L3 \u7684\u5bb9\u91cf\u2014\u2014\u5de5\u4f5c\u96c6\u5728 16MB \u65f6 L3 \u5df2\u7ecf\u653e\u4e0d\u4e0b\u5168\u90e8\u6570\u636e，\u4f46\u8fd8\u653e\u5f97\u4e0b\u5f88\u5927\u4e00\u90e8\u5206；\u5230 32MB \u65f6\u5927\u534a\u8bbf\u95ee\u90fd\u8981\u843d\u5230\u4e3b\u5b58\u3002L3 \u5230\u4e3b\u5b58\u8fd9\u4e00\u6b65\u8de8\u7684\u662f\u4ece\u4e09\u5341\u51e0\u7eb3\u79d2\u5230 90 ns，\u7ea6\u4e09\u500d\u3002<\/p>\n

    16MB \u90a3\u4e00\u6863\u7684\u6570\u503c\u672c\u8eab\u662f\u5168\u8868\u6700\u4e0d\u53ef\u590d\u73b0\u7684（\u89c1 A \u7ebf\u4efb\u52a1\u91cc\u90a3\u5f20\u504f\u5dee\u8868），\u4f46\u8fd9\u4e00\u6b65\u7684\u9661\u5ced\u4e0d\u4f9d\u8d56\u5b83\u7684\u7cbe\u786e\u503c：32MB \u90a3\u4e00\u6863\u8fdc\u8d85 L3 \u5bb9\u91cf，\u65e0\u8bba 16MB \u53d6 27 \u8fd8\u662f 34，\u843d\u5dee\u90fd\u662f\u4e24\u500d\u4ee5\u4e0a\u3002<\/p>\n

    \u4e0a\u9762\u8fd9\u5f20\u8868\u91cc，\u6bcf\u4e00\u6863\u7684\u300c\u5ef6\u8fdf\u300d\u90fd\u4e0d\u662f\u5355\u4e00\u6765\u6e90\u7684\u5ef6\u8fdf\u3002\u5b83\u662f\u300c\u8fd9\u4e00\u6863\u91cc\u6709\u591a\u5c11\u6bd4\u4f8b\u7684\u8bbf\u95ee\u843d\u5728\u54ea\u4e00\u7ea7\u300d\u7684\u52a0\u6743\u548c\u3002 \u53f0\u9636\u4e0d\u662f\u5728\u67d0\u4e00\u7ea7\u5185\u90e8\u91cf\u51fa\u6765\u7684，\u662f\u5728\u4e24\u7ea7\u7684\u4ea4\u754c\u5904\u91cf\u51fa\u6765\u7684\u3002<\/p>\n

    \u4ee3\u7801\u9010\u884c<\/h4>\n

    \u6838\u5fc3\u5faa\u73af\u5c31\u662f\u4e0a\u4e00\u8bb2\u90a3\u6bb5 chase_ns\u3002\u8fd9\u91cc\u8865\u4e24\u70b9\u5916\u56f4\u4ee3\u7801\u3002<\/p>\n

    const<\/span> std::<\/span>size_t sizes_kb[<\/span>]<\/span> =<\/span> {<\/span>16<\/span>,<\/span> 64<\/span>,<\/span> 256<\/span>,<\/span> 512<\/span>,<\/span> 1024<\/span>,<\/span> 4096<\/span>,<\/span> 8192<\/span>,<\/span> 16384<\/span>,<\/span> 32768<\/span>,<\/span> 65536<\/span>,<\/span> 262144<\/span>}<\/span>;<\/span><\/p>\n

    for<\/span> (<\/span>std::<\/span>size_t kb :<\/span> sizes_kb)<\/span> {<\/span>
    \n const<\/span> std::<\/span>size_t bytes =<\/span> kb *<\/span> 1024<\/span>;<\/span>
    \n const<\/span> std::<\/span>size_t n =<\/span> bytes \/<\/span> sizeof<\/span>(<\/span>std::<\/span>uint32_t<\/span>)<\/span>;<\/span><\/p>\n

    auto<\/span> next =<\/span> make_cycle<\/span>(<\/span>n,<\/span> 20260911<\/span>)<\/span>;<\/span>
    \n const<\/span> std::<\/span>size_t steps =<\/span> n *<\/span> STEPS_PER_NODE;<\/span><\/p>\n

    \/\/ \u53d6\u591a\u8f6e\u6700\u5c0f，\u907f\u5f00\u5e72\u6270（\u5355\u5143\u56db\u7684\u6559\u8bad）<\/span>
    \n double<\/span> best =<\/span> 1e18<\/span>;<\/span>
    \n for<\/span> (<\/span>int<\/span> r =<\/span> 0<\/span>;<\/span> r <<\/span> 5<\/span>;<\/span> ++<\/span>r)<\/span> best =<\/span> std::<\/span>min<\/span>(<\/span>best,<\/span> chase_ns<\/span>(<\/span>next,<\/span> steps)<\/span>)<\/span>;<\/span>
    \n \/\/…<\/span>
    \n}<\/span><\/p>\n

    \u626b\u63cf\u70b9\u6309 4 \u500d\u9012\u589e：16\u300164\u3001256\u30011024\u2026\u2026 \u8fd9\u4e2a\u6bd4\u4f8b\u662f\u7528\u6765\u770b\u53f0\u9636\u7684，\u4e0d\u662f\u7528\u6765\u770b\u7ec6\u8282\u7684\u3002\u8981\u5b9a\u4f4d\u4e00\u6761\u5177\u4f53\u8fb9\u754c，\u5f97\u5728\u53f0\u9636\u9644\u8fd1\u628a\u95f4\u9694\u52a0\u5bc6\u3002<\/p>\n

    \u6bcf\u4e00\u6b65\u8d70 n * 3 \u6b21\u2014\u2014\u4e09\u5708\u3002\u8d70\u4e00\u5708\u7684\u8bdd，\u73af\u4e0a\u7684\u6bcf\u4e2a\u5143\u7d20\u53ea\u78b0\u4e00\u6b21，\u91cf\u5230\u7684\u4e1c\u897f\u53d7\u8d77\u59cb\u4f4d\u7f6e\u5f71\u54cd；\u8d70\u4e09\u5708\u80fd\u644a\u6389\u3002\u8fd9\u4e2a\u500d\u6570\u5199\u5728 STEPS_PER_NODE \u91cc，\u6539\u5b83\u8981\u540c\u6b65\u6539\u6240\u6709\u5bf9\u7167\u6570\u636e\u3002<\/p>\n

    \u6bcf\u6863\u5404\u5efa\u4e00\u4efd next \u6570\u7ec4，\u4e0d\u590d\u7528\u3002\u56e0\u4e3a\u4e0d\u540c\u89c4\u6a21\u8981\u7684\u662f\u4e0d\u540c\u7684\u73af，\u6362\u89c4\u6a21\u5c31\u5f97\u91cd\u5efa\u3002\u5efa\u6570\u7ec4\u7684\u65f6\u95f4\u4e0d\u8ba1\u5165（\u5728\u8ba1\u65f6\u5faa\u73af\u5916\u9762）\u3002<\/p>\n

    \u4ee3\u7801\u8fd0\u884c\u7ed3\u679c<\/h4>\n

    \u89c1\u4e0a\u4e00\u8bb2\u90a3\u5f20\u8868\u3002\u8fd9\u91cc\u6362\u4e00\u4e2a\u89d2\u5ea6\u8bfb\u5b83\u2014\u2014\u628a\u76f8\u5bf9\u500d\u6570\u6309\u53f0\u9636\u5206\u7ec4：<\/p>\n

    L1 \u2192 L2 2.06x \u2192 2.83x \u6da8 1.4 \u500d
    \nL2 \u2192 L3 5.15x \u2192 32.78x \u6da8 6.4 \u500d
    \nL3 \u2192 \u4e3b\u5b58 32.78x \u2192 102.30x \u6da8 3.1 \u500d<\/p>\n

    \u4ece L2 \u5230 L3 \u8fd9\u4e00\u6bb5\u6da8\u5e45\u6700\u5927（6.4 \u500d），\u56e0\u4e3a\u672c\u673a\u7684 L2 \u6bcf\u6838 1MB \u800c L3 \u5171\u4eab 16MB，\u4e2d\u95f4\u8de8\u7684\u5bb9\u91cf\u533a\u95f4\u6700\u5bbd\u3002<\/p>\n

    \u5e38\u89c1\u5751<\/h4>\n

    \u5751\u4e00：\u628a\u6807\u79f0\u5bb9\u91cf\u5f53\u6210\u7cbe\u786e\u8fb9\u754c\u3002 \u4e0a\u8868\u5199\u7684\u300cL1d 32KB\/\u6838\u300d，\u4f46\u53f0\u9636\u51fa\u73b0\u5728 16KB \u5230 64KB \u4e4b\u95f4，\u4e0d\u5728 32KB \u8fd9\u4e2a\u70b9\u4e0a\u3002\u539f\u56e0\u6709\u4e09：\u7f13\u5b58\u662f\u7ec4\u76f8\u8054\u7684，\u4e0d\u662f\u5168\u76f8\u8054；L1 \u91cc\u8fd8\u8981\u653e\u6307\u4ee4\u548c\u5404\u79cd\u8868；\u5de5\u4f5c\u96c6\u7684\u5b9e\u9645\u5360\u7528\u91cf\u6bd4\u6570\u7ec4\u672c\u8eab\u5927\u3002<\/p>\n

    \u62a5\u8fb9\u754c\u7684\u65f6\u5019\u62a5\u533a\u95f4，\u522b\u62a5\u70b9\u3002<\/p>\n

    \u5751\u4e8c：\u62ff\u8fd9\u53f0\u673a\u5668\u7684\u7eb3\u79d2\u6570\u53bb\u5957\u522b\u7684\u673a\u5668\u3002 L1 \u5ef6\u8fdf 1 ns \u662f\u8fd9\u4e00\u4ee3 Zen 4 \u7684\u6570\u503c，\u6362\u6210\u522b\u7684\u67b6\u6784\u4f1a\u53d8\u3002\u53ef\u4ee5\u642c\u8d70\u7684\u662f\u53f0\u9636\u7684\u5f62\u72b6\u2014\u2014\u56db\u7ea7\u3001\u5bb9\u91cf\u9012\u589e\u3001\u5ef6\u8fdf\u9012\u589e\u2014\u2014\u5177\u4f53\u7684\u7eb3\u79d2\u6570\u5fc5\u987b\u91cd\u6d4b\u3002\u8fd9\u662f\u5355\u5143\u4e00\u73af\u5883\u56db\u5143\u7ec4\u7684\u76f4\u63a5\u540e\u679c\u3002<\/p>\n

    \u5751\u4e09：\u5fd8\u4e86\u770b\u5171\u4eab L3\u3002 \u672c\u673a L3 \u662f 8 \u6838\u5171\u4eab\u7684\u3002\u5b9e\u9a8c\u7ed1\u5728 15 \u53f7\u6838\u4e0a\u8dd1，\u4f46\u5982\u679c\u522b\u7684\u6838\u540c\u65f6\u5728\u5403 L3，\u4f60\u80fd\u7528\u7684 L3 \u5c31\u4e0d\u5230 16MB\u3002\u8fd9\u5c31\u662f\u4e3a\u4ec0\u4e48 16MB \u90a3\u4e00\u6863\u7684\u6296\u52a8\u6700\u5927\u3002<\/p>\n

    \u6559\u6750\u6307\u5f15<\/h4>\n

    Guntheroth ch2\u3002\u4ed6\u7ed9\u7684\u662f\u5404\u7c7b\u7f13\u5b58\u884c\u4e3a\u7684\u5b9a\u6027\u63cf\u8ff0\u548c\u91cf\u7ea7，\u5177\u4f53\u6570\u5b57\u540c\u6837\u8981\u6c42\u4f60\u5728\u81ea\u5df1\u673a\u5668\u4e0a\u91cd\u6d4b\u3002<\/p>\n

    \u7b2c\u4e09\u8bb2 \u642c\u8fd0\u91cf\u76f8\u540c，\u901f\u7387\u5dee\u56db\u500d<\/h3>\n

    \u662f\u4ec0\u4e48<\/h4>\n

    \u4e0a\u4e00\u8bb2\u7684\u9636\u68af\u662f\u7528\u6307\u9488\u8ffd\u9010\u91cf\u51fa\u6765\u7684\u2014\u2014\u90a3\u662f\u5ef6\u8fdf：\u4e00\u6b65\u7b49\u4e00\u6b65，\u4e32\u884c，\u6ca1\u6709\u4efb\u4f55\u91cd\u53e0\u3002\u771f\u5b9e\u7684\u4ee3\u7801\u91cc，\u8bbf\u95ee\u4e4b\u95f4\u5e38\u5e38\u6ca1\u6709\u4f9d\u8d56，\u53ef\u4ee5\u540c\u65f6\u5728\u98de\u3002\u8fd9\u65f6\u5019\u8be5\u770b\u7684\u91cf\u6362\u6210\u4e86\u541e\u5410\u3002<\/p>\n

    exp07_prefetch.cpp \u62ff\u540c\u4e00\u4e2a 64MB \u6570\u7ec4\u505a\u4e09\u4ef6\u4e8b：<\/p>\n

    \u987a\u5e8f \u2014\u2014 16<\/span>M \u6b21\u8bbf\u95ee，\u6bcf\u6b21\u7528\u6ee1\u4e00\u6574\u884c，\u78b0\u5230 1<\/span>M \u884c
    \n\u6b65\u957f 16<\/span> \u2014\u2014 1<\/span>M \u6b21\u8bbf\u95ee，\u6bcf\u6b21\u53ea\u53d6 4<\/span> \u5b57\u8282，\u4f46\u4e5f\u78b0\u5230 1<\/span>M \u884c
    \n\u968f\u673a \u2014\u2014 1<\/span>M \u6b21\u8bbf\u95ee，\u540c\u6837\u662f 1<\/span>M \u884c，\u53ea\u662f\u5148\u540e\u987a\u5e8f\u88ab\u6253\u4e71<\/p>\n

    \u4e09\u6863\u642c\u8fd0\u7684\u5b57\u8282\u6570\u5b8c\u5168\u4e00\u6837，\u90fd\u662f 64MB\u3002\u5dee\u522b\u53ea\u5728\u987a\u5e8f\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u987a\u5e8f\u8bbf\u95ee\u80fd\u628a\u5ef6\u8fdf\u85cf\u8d77\u6765<\/h4>\n

    \u5148\u770b\u7ed3\u679c，\u518d\u89e3\u91ca\u3002<\/p>\n

    \u8bbf\u95ee\u987a\u5e8f \u8bbf\u95ee\u6b21\u6570 \u8017\u65f6 \u642c\u8fd0\u901f\u7387 \u6bcf\u6b21\u8bbf\u95ee
    \n\u987a\u5e8f 16777216 1.37 ms 45.6 GB\/s 0.08 ns
    \n\u6b65\u957f 16 1048576 1.30 ms 48.1 GB\/s 1.24 ns
    \n\u968f\u673a 1048576 5.42 ms 11.5 GB\/s 5.17 ns<\/p>\n

    \u987a\u5e8f\u90a3\u4e00\u6863\u8bbf\u95ee\u7684\u5143\u7d20\u4e2a\u6570\u662f\u53e6\u5916\u4e24\u6863\u7684 16 \u500d，\u8017\u65f6\u53cd\u800c\u6700\u77ed\u3002\u800c\u968f\u673a\u90a3\u4e00\u6863\u548c\u6b65\u957f 16 \u8bbf\u95ee\u7684\u5143\u7d20\u4e2a\u6570\u4e00\u6a21\u4e00\u6837\u3001\u78b0\u7684 cache line \u6761\u6570\u4e00\u6a21\u4e00\u6837\u3001\u642c\u8fd0\u7684\u5b57\u8282\u6570\u4e00\u6a21\u4e00\u6837，\u8017\u65f6\u662f\u5b83\u7684 4.2 \u500d\u3002<\/p>\n

    \u642c\u8fd0\u91cf\u76f8\u540c，\u901f\u7387\u5dee 4.2 \u500d\u3002 \u5148\u7528\u8ba1\u6570\u5668\u628a\u300c\u642c\u8fd0\u91cf\u76f8\u540c\u300d\u8fd9\u53e5\u8bdd\u786e\u8ba4\u4e0b\u6765，\u518d\u89e3\u91ca\u5dee\u5728\u54ea\u3002<\/p>\n

    \u8ba1\u6570\u5668\u8bf4：\u4e09\u6863\u78b0\u7684 line \u4e00\u6837\u591a<\/h4>\n

    exp07_prefetch \u4e5f\u6709\u5355\u6863\u5165\u53e3，\u540c\u6837\u914d\u4e00\u4e2a none \u6863，\u51cf\u6389\u5efa 64MB \u6570\u7ec4\u548c\u6253\u4e71\u4e0b\u6807\u7684\u6d41\u91cf：<\/p>\n

    $ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses \\\\<\/span>
    \n -e<\/span> l2_pf_hit_l2.all,l2_pf_miss_l2_l3.all .\/exp07_prefetch <<\/span>seq|<\/span>stride|<\/span>gather|<\/span>none><\/span><\/p>\n

    \u6bcf\u6863\u8dd1 20 \u904d，\u51cf\u6389\u57fa\u7ebf：<\/p>\n\n\u8bbf\u95ee\u987a\u5e8fL1 \u8bfb miss\u9884\u53d6\u8bf7\u6c42\u547d\u4e2d L2\u9884\u53d6\u8bf7\u6c42\u4e0b\u6c89\u5230 L3L2 \u9700\u6c42 miss<\/tr>\n\n\n\n\n
    \u987a\u5e8f<\/td>\n20,978,696<\/td>\n21,161,940<\/td>\n20,868,706<\/td>\n96,854<\/td>\n<\/tr>\n
    \u6b65\u957f 16<\/td>\n20,991,049<\/td>\n1,630,066<\/td>\n15,692,664<\/td>\n205,633<\/td>\n<\/tr>\n
    \u968f\u673a<\/td>\n22,335,258<\/td>\n1,604,650<\/td>\n1,152,055<\/td>\n21,686,647<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4e09\u6863\u6bcf\u6863\u90fd\u78b0 1M \u6761 line\u3001\u8dd1 20 \u904d，\u5171 20M \u6761\u3002<\/p>\n

    \u7b2c\u4e00\u5217\u7684\u4e09\u6863\u51e0\u4e4e\u76f8\u540c，\u8fd9\u5c31\u662f\u300c\u642c\u8fd0\u91cf\u76f8\u540c\u300d\u7684\u76f4\u63a5\u8bc1\u636e\u3002 2100 \u4e07\u8fd9\u4e2a\u6570\u5c31\u662f 20M \u6761 line \u7684\u9996\u89e6\u6b21\u6570\u2014\u2014\u7b2c\u56db\u8bb2\u90a3\u6761\u300c\u786c\u4ef6\u6309\u884c\u8bb0\u8d26\u300d\u5728\u8fd9\u91cc\u7b2c\u4e8c\u6b21\u51fa\u73b0\u3002<\/p>\n

    \u5dee\u5728\u7b2c\u4e09\u3001\u56db\u5217\u3002\u987a\u5e8f\u548c\u6b65\u957f\u4e24\u6863，\u9884\u53d6\u5668\u5206\u522b\u53d1\u51fa 2087 \u4e07\u548c 1570 \u4e07\u6b21\u53d6\u6570\u8bf7\u6c42，\u8fd9\u4e9b\u8bf7\u6c42\u5728 L2 \u91cc\u90fd\u6ca1\u6709\u547d\u4e2d，\u4e8e\u662f\u4e0b\u6c89\u5230 L3 \u53bb\u53d6\u3002\u7b49 CPU \u771f\u7684\u6765\u8981\u8fd9\u6761\u6570\u636e，\u5b83\u5df2\u7ecf\u5728 L2 \u91cc\u4e86，\u9700\u6c42 miss \u56e0\u6b64\u53ea\u6709 9.7 \u4e07\u548c 20.6 \u4e07\u3002\u968f\u673a\u90a3\u4e00\u6863\u9884\u53d6\u5668\u53ea\u53d1\u51fa 115 \u4e07\u6b21，\u5269\u4e0b\u4e24\u5343\u4e07\u6761\u5168\u8981\u5f53\u573a\u53bb L3 \u6216\u4e3b\u5b58\u53d6\u3002<\/p>\n

    \u8017\u65f6\u8ddf\u7740\u7b2c\u56db\u5217\u8d70，\u4e0d\u8ddf\u7740\u7b2c\u4e00\u5217\u3002<\/p>\n

    \u4e2d\u95f4\u90a3\u4e24\u5217\u4e0d\u80fd\u76f8\u52a0\u3002\u987a\u5e8f\u90a3\u4e00\u6863，\u9884\u53d6\u8bf7\u6c42\u300c\u547d\u4e2d L2\u300d\u548c\u300c\u4e0b\u6c89 L3\u300d\u90fd\u662f\u4e24\u5343\u591a\u4e07，\u52a0\u8d77\u6765\u8d85\u8fc7\u4e86\u5b83\u78b0\u5230\u7684 line \u6570\u2014\u2014\u540c\u4e00\u6761 line \u88ab\u9884\u53d6\u5668\u91cd\u590d\u8bf7\u6c42\u8fc7\u3002\u8fd9\u4e24\u4e2a\u8ba1\u6570\u4e0d\u662f\u628a\u540c\u4e00\u6279\u8bf7\u6c42\u5206\u6210\u4e92\u65a5\u7684\u4e24\u7c7b\u3002\u5224\u65ad\u9884\u53d6\u5668\u6709\u6ca1\u6709\u5728\u5e72\u6d3b，\u770b\u7b2c\u4e09\u5217\u7684\u91cf\u7ea7\u3002<\/p>\n

    \u5dee\u5728\u54ea：\u9884\u53d6\u5668\u4e0e\u5185\u5b58\u5e76\u884c\u5ea6<\/h4>\n

    \u4e00\u3001\u9884\u53d6\u5668\u3002 \u5b83\u76ef\u7740 CPU \u53d1\u51fa\u7684\u5730\u5740\u6d41，\u627e\u89c4\u5f8b\u3002\u770b\u5230\u5730\u5740\u6309 +64 \u5b57\u8282 \u7a33\u5b9a\u524d\u8fdb，\u5c31\u63d0\u524d\u628a\u540e\u9762\u51e0\u6761 line \u62c9\u8fdb\u6765；\u770b\u5230\u7a33\u5b9a\u7684 +4096 \u5b57\u8282 \u6b65\u957f，\u4e00\u6837\u80fd\u8bc6\u522b\u2014\u2014\u6b65\u957f 16 \u90a3\u4e00\u6863\u8d70\u7684\u6b63\u662f\u8fd9\u4e2a\u6a21\u5f0f，\u6240\u4ee5\u5b83\u548c\u987a\u5e8f\u6253\u5e73（48.1 \u5bf9 45.6 GB\/s）\u3002<\/p>\n

    \u968f\u673a\u7684\u5730\u5740\u6d41\u91cc\u6ca1\u6709\u89c4\u5f8b\u53ef\u627e\u3002\u4e0a\u8868\u7b2c\u4e09\u5217\u91cc\u5b83\u53ea\u6709 115 \u4e07，\u5176\u4f59\u4e24\u6863\u662f 1570 \u4e07\u548c 2087 \u4e07，\u5dee 14 \u5230 18 \u500d\u2014\u2014\u8fd9\u5c31\u662f\u300c\u9884\u53d6\u5668\u8ba4\u4e0d\u51fa\u300d\u5728\u8ba1\u6570\u5668\u4e0a\u7684\u6837\u5b50\u3002<\/p>\n

    \u9884\u53d6\u91cf\u5dee\u5341\u51e0\u500d，\u843d\u5230\u9700\u6c42 miss \u4e0a\u662f 105 \u5230 224 \u500d\u3002\u4e2d\u95f4\u591a\u51fa\u6765\u7684\u90a3\u4e00\u6bb5，\u662f\u300c\u9884\u53d6\u8bf7\u6c42\u53d1\u51fa\u53bb\u4e86\u300d\u548c\u300c\u8981\u7528\u7684\u65f6\u5019\u6570\u636e\u5728\u4e0d\u5728\u300d\u4e4b\u95f4\u7684\u5dee\u3002<\/p>\n

    \u4e8c\u3001\u4e71\u5e8f\u6267\u884c\u4e0e\u5185\u5b58\u5e76\u884c\u5ea6\u3002 \u987a\u5e8f\u90a3\u4e00\u6863，s0 += d[i] \u548c s1 += d[i+1] \u4e4b\u95f4\u6ca1\u6709\u4f9d\u8d56，CPU \u53ef\u4ee5\u540c\u65f6\u53d1\u51fa\u5f88\u591a\u6761\u8bbf\u5b58\u6307\u4ee4\u3002\u5355\u6b21 miss \u8981\u7b49 90 ns，\u4f46\u540c\u65f6\u6709\u5341\u51e0\u6761 miss \u5728\u98de，\u644a\u5230\u6bcf\u4e00\u6b21\u5c31\u53ea\u5269\u51e0\u7eb3\u79d2\u3002<\/p>\n

    \u7b97\u4e00\u4e0b\u644a\u8584\u7684\u6bd4\u4f8b\u3002\u968f\u673a\u90a3\u4e00\u6863\u6bcf\u904d 104.8576 \u4e07\u6b21\u8bbf\u95ee，\u8017\u65f6 5.42 ms，\u4e00\u5171\u7ea6 108 \u4e07\u6b21 L2 \u9700\u6c42 miss\u2014\u2014\u6bcf\u6b21 miss \u644a\u5230 5.02 ns\u3002 \u800c\u5355\u6b21\u8bbf\u5b58\u5ef6\u8fdf\u662f 90 ns（\u7b2c\u4e00\u8bb2）\u3002\u4e24\u8005\u5dee 18 \u500d，\u4e5f\u5c31\u662f\u8bf4\u5e73\u5747\u6709\u5341\u51e0\u4e2a miss \u540c\u65f6\u5728\u98de\u3002<\/p>\n

    \u968f\u673a\u90a3\u4e00\u6863\u8fd8\u7559\u7740\u8fd9\u4e2a\u80fd\u529b，\u6240\u4ee5\u5b83\u662f 5.17 ns \u800c\u4e0d\u662f 90 ns\u3002\u628a\u4e24\u4ef6\u4e8b\u90fd\u6390\u6389\u7684\u662f\u5e26\u4e0a\u6570\u636e\u4f9d\u8d56\u7684\u6307\u9488\u8ffd\u9010，\u90a3\u624d\u662f\u4e0a\u4e00\u8bb2\u7684 90~106 ns\u3002<\/p>\n

    \u4e09\u6863\u7684\u5206\u5de5：\u987a\u5e8f\u90a3\u6863\u5df2\u7ecf\u9876\u5230\u5185\u5b58\u5e26\u5bbd\u4e0a\u9650（45.6 GB\/s，\u548c\u7b2c\u56db\u8bb2\u91cf\u5230\u7684 50 GB\/s \u662f\u540c\u4e00\u4e2a\u6570），\u968f\u673a\u90a3\u6863\u53ea\u8dd1\u5230 11.5 GB\/s，\u79bb\u4e0a\u9650\u8fd8\u8fdc\u3002\u6240\u4ee5\u968f\u673a\u90a3\u6863\u4e0d\u662f\u88ab\u5e26\u5bbd\u5361\u4f4f\u7684，\u662f\u88ab\u5ef6\u8fdf\u5361\u4f4f\u7684\u2014\u2014\u5e26\u5bbd\u4e0d\u662f\u74f6\u9888，\u5ef6\u8fdf\u624d\u662f\u3002<\/p>\n

    \u4ee3\u7801\u9010\u884c<\/h4>\n

    \/\/ \u6b65\u957f 16 \u4e2a int = 64 \u5b57\u8282，\u6b63\u597d\u9694\u4e00\u6761 line\u3002\u6bcf\u6761 line \u53ea\u7528 4 \u5b57\u8282\u3002<\/span>
    \ninline<\/span> std::<\/span>uint64_t<\/span> sum_stride<\/span>(<\/span>const<\/span> std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span>&<\/span> d)<\/span> {<\/span>
    \n std::<\/span>uint64_t<\/span> s0 =<\/span> 0<\/span>,<\/span> s1 =<\/span> 0<\/span>;<\/span>
    \n std::<\/span>size_t i =<\/span> 0<\/span>;<\/span>
    \n for<\/span> (<\/span>;<\/span> i +<\/span> 32<\/span> <<\/span> d.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i +=<\/span> 32<\/span>)<\/span> {<\/span> s0 +=<\/span> d[<\/span>i]<\/span>;<\/span> s1 +=<\/span> d[<\/span>i +<\/span> 16<\/span>]<\/span>;<\/span> }<\/span>
    \n return<\/span> s0 +<\/span> s1;<\/span>
    \n}<\/span><\/p>\n

    \u4e00\u6b21\u5faa\u73af\u5904\u7406\u4e24\u4e2a\u5143\u7d20，\u4e2d\u95f4\u9694 16 \u4e2a int\u3002\u8fd9\u6837\u4e24\u6863\u7684\u5faa\u73af\u6b21\u6570\u662f\u5143\u7d20\u6570\u7684\u4e00\u534a，\u65b9\u4fbf\u548c\u987a\u5e8f\u7248\u5bf9\u7167\u3002<\/p>\n

    \/\/ \u6309\u4e0b\u6807\u5e8f\u5217\u53d6\u3002\u4e0b\u6807\u662f\u9884\u6253\u4e71\u7684，\u786c\u4ef6\u731c\u4e0d\u51fa\u4e0b\u4e00\u4e2a\u662f\u8c01\u3002<\/span>
    \ninline<\/span> std::<\/span>uint64_t<\/span> sum_gather<\/span>(<\/span>const<\/span> std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span>&<\/span> d,<\/span>
    \n const<\/span> std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span>&<\/span> idx)<\/span> {<\/span>
    \n std::<\/span>uint64_t<\/span> s0 =<\/span> 0<\/span>,<\/span> s1 =<\/span> 0<\/span>;<\/span>
    \n std::<\/span>size_t i =<\/span> 0<\/span>;<\/span>
    \n for<\/span> (<\/span>;<\/span> i +<\/span> 2<\/span> <=<\/span> idx.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> i +=<\/span> 2<\/span>)<\/span> {<\/span> s0 +=<\/span> d[<\/span>idx[<\/span>i]<\/span>]<\/span>;<\/span> s1 +=<\/span> d[<\/span>idx[<\/span>i +<\/span> 1<\/span>]<\/span>]<\/span>;<\/span> }<\/span>
    \n for<\/span> (<\/span>;<\/span> i <<\/span> idx.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> ++<\/span>i)<\/span> s0 +=<\/span> d[<\/span>idx[<\/span>i]<\/span>]<\/span>;<\/span>
    \n return<\/span> s0 +<\/span> s1;<\/span>
    \n}<\/span><\/p>\n

    \u4e0b\u6807\u6570\u7ec4\u9884\u5148\u6253\u4e71\u597d，\u91cc\u9762\u5b58\u7684\u662f\u5df2\u7ecf\u4e58\u8fc7 16 \u7684\u4f4d\u7f6e，\u76f4\u63a5\u62ff\u6765\u505a\u6570\u7ec4\u4e0b\u6807\u3002\u591a\u8bfb\u4e00\u4e2a 4MB \u7684\u4e0b\u6807\u6570\u7ec4\u662f\u8fd9\u7b14\u6d4b\u91cf\u7684\u6210\u672c\u2014\u2014\u5b83\u662f\u987a\u5e8f\u8bfb\u7684，\u901f\u7387\u63a5\u8fd1\u5e26\u5bbd\u4e0a\u9650，\u76f8\u6bd4 64MB \u7684\u4e3b\u6570\u636e\u6d41\u53ef\u4ee5\u5ffd\u7565\u3002<\/p>\n

    std::<\/span>vector<<\/span>std::<\/span>uint32_t<\/span>><\/span> idx<\/span>(<\/span>SPARSE_N)<\/span>;<\/span>
    \nstd::<\/span>iota<\/span>(<\/span>idx.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> idx.<\/span>end<\/span>(<\/span>)<\/span>,<\/span> 0u<\/span>)<\/span>;<\/span>
    \nstd::<\/span>mt19937 rng<\/span>(<\/span>20260912<\/span>)<\/span>;<\/span>
    \nstd::<\/span>shuffle<\/span>(<\/span>idx.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> idx.<\/span>end<\/span>(<\/span>)<\/span>,<\/span> rng)<\/span>;<\/span>
    \nfor<\/span> (<\/span>auto<\/span>&<\/span> v :<\/span> idx)<\/span> v *=<\/span> 16<\/span>;<\/span> \/\/ \u644a\u5230\u6574\u5757\u5185\u5b58\u4e0a<\/span><\/p>\n

    \u79cd\u5b50\u5199\u6b7b，\u4efb\u4f55\u4eba\u91cd\u8dd1\u90fd\u5f97\u5230\u540c\u4e00\u4e2a\u6392\u5217\u3002\u8fd9\u4e00\u6b65\u4e0d\u80fd\u7701\u2014\u2014\u6362\u6210\u968f\u673a\u79cd\u5b50，\u4e24\u6b21\u8fd0\u884c\u7684\u7ed3\u8bba\u5c31\u6ca1\u6cd5\u6bd4\u4e86\u3002<\/p>\n

    \u4e09\u6761\u72ec\u7acb\u7684\u7d2f\u52a0\u94fe（s0\u3001s1）\u662f\u8fd9\u4e2a\u5b9e\u9a8c\u7684\u53e6\u4e00\u4e2a\u524d\u63d0\u3002\u5982\u679c\u53ea\u7528\u4e00\u4e2a\u7d2f\u52a0\u53d8\u91cf，\u4e24\u4e2a\u52a0\u6cd5\u4e4b\u95f4\u5c31\u5e26\u4e0a\u4e86\u4f9d\u8d56，\u5faa\u73af\u672c\u8eab\u4f1a\u6210\u4e3a\u74f6\u9888，\u628a\u8bbf\u5b58\u7684\u5dee\u522b\u76d6\u4f4f\u3002\u8fd9\u4e2a\u5751\u5728\u5355\u5143\u4e00\u7684 exp02 \u91cc\u5df2\u7ecf\u8e29\u8fc7\u4e00\u6b21\u3002<\/p>\n

    \u4ee3\u7801\u8fd0\u884c\u7ed3\u679c<\/h4>\n

    \u89c1\u4e0a\u8868\u3002\u8fd9\u91cc\u8865\u4e00\u6bb5\u7a0b\u5e8f\u81ea\u5df1\u7684\u5f52\u56e0：<\/p>\n

    \u4e09\u6863\u642c\u8fd0\u7684\u5b57\u8282\u6570\u5b8c\u5168\u4e00\u6837，\u90fd\u662f 64 MB
    \n\u642c\u8fd0\u91cf\u76f8\u540c，\u901f\u7387\u5dee\u4e86 4.2 \u500d\u3002\u987a\u5e8f\u548c\u6b65\u957f 16 \u90fd\u8dd1\u5728 46 GB\/s \u9644\u8fd1，
    \n\u968f\u673a\u90a3\u4e00\u6863\u53ea\u6709 11.5 GB\/s，\u79bb\u4e0a\u9650\u8fd8\u5dee\u5f97\u8fdc\u2014\u2014\u5b83\u4e0d\u662f\u88ab\u5e26\u5bbd\u5361\u4f4f\u7684，
    \n\u662f\u88ab\u5ef6\u8fdf\u5361\u4f4f\u7684\u3002<\/p>\n

    \u5e38\u89c1\u5751<\/h4>\n

    \u5751\u4e00：\u53ea\u770b\u8bbf\u95ee\u6b21\u6570，\u4e0d\u770b\u642c\u8fd0\u91cf\u3002 \u300c\u6b65\u957f 16 \u53ea\u53d6\u4e86 1\/16 \u7684\u5143\u7d20，\u600e\u4e48\u6ca1\u5feb 16 \u500d？\u300d\u2014\u2014\u56e0\u4e3a\u52a0\u6cd5\u6b21\u6570\u5c11\u4e86 16 \u500d，\u642c\u8fd0\u7684\u5b57\u8282\u6570\u4e00\u4e2a\u6ca1\u5c11\u3002\u53d6\u591a\u5c11\u5143\u7d20\u51b3\u5b9a\u52a0\u6cd5\u6b21\u6570，\u78b0\u591a\u5c11\u884c\u624d\u51b3\u5b9a\u8017\u65f6\u3002\u8fd9\u4e24\u7b14\u8d26\u4ece\u8fd9\u4e00\u8bb2\u8d77\u8981\u5206\u5f00\u7b97\u3002<\/p>\n

    \u5751\u4e8c：\u628a\u968f\u673a\u8bbf\u95ee\u7684 5 ns \u5f53\u6210\u300c\u968f\u673a\u8bbf\u95ee\u7684\u6210\u672c\u300d\u3002 5.17 ns \u662f\u5927\u6279\u72ec\u7acb\u8bbf\u95ee\u91cd\u53e0\u4e4b\u540e\u7684\u644a\u8584\u503c\u3002\u5355\u6b21\u968f\u673a\u8bbf\u5b58\u5ef6\u8fdf\u662f 90~106 ns（\u7b2c\u4e00\u8bb2）\u3002\u5199\u4ee3\u7801\u65f6\u8be5\u7528\u54ea\u4e2a\u6570，\u53d6\u51b3\u4e8e\u8fd9\u6bb5\u8bbf\u95ee\u6709\u6ca1\u6709\u4f9d\u8d56\u94fe：\u904d\u5386\u4e00\u4e2a vector<int> \u7528 5 ns，\u8ddf\u7740 next \u6307\u9488\u8d70\u7528 100 ns\u3002<\/p>\n

    \u5751\u4e09：\u4ee5\u4e3a\u9884\u53d6\u5668\u53ea\u8ba4\u300c\u8fde\u7eed\u300d\u3002 \u672c\u673a\u7684\u9884\u53d6\u5668\u8ba4\u6b65\u957f，\u6b65\u957f 16 \u90a3\u4e00\u6863\u548c\u987a\u5e8f\u6253\u5e73\u5c31\u662f\u8bc1\u636e\u3002\u6240\u4ee5\u300c\u628a\u6570\u636e\u6253\u6563\u5c31\u80fd\u907f\u514d\u9884\u53d6\u5668\u5e72\u6270\u300d\u8fd9\u4e2a\u60f3\u6cd5\u4e0d\u6210\u7acb\u2014\u2014\u8981\u6253\u65ad\u9884\u53d6，\u5f97\u8ba9\u5730\u5740\u4e0d\u53ef\u9884\u6d4b\u3002<\/p>\n

    \u6559\u6750\u6307\u5f15<\/h4>\n

    Guntheroth ch2 \u8bb2\u7f13\u5b58\u884c\u4e3a\u65f6\u628a\u9884\u53d6\u548c\u4e71\u5e8f\u6267\u884c\u653e\u5728\u4e00\u8d77\u8bf4\u3002\u4ed6\u7ed9\u7684\u5224\u65ad\u662f：\u786c\u4ef6\u80fd\u81ea\u52a8\u5904\u7406\u7684\u6a21\u5f0f\u6bd4\u591a\u6570\u4eba\u4ee5\u4e3a\u7684\u591a，\u6240\u4ee5\u5148\u91cf\u518d\u6539\u3002<\/p>\n

    \u7b2c\u56db\u8bb2 \u786c\u4ef6\u6309\u884c\u8bb0\u8d26<\/h3>\n

    \u662f\u4ec0\u4e48<\/h4>\n

    \u4e0a\u4e00\u8bb2\u5df2\u7ecf\u6697\u793a\u4e86\u4e00\u4ef6\u4e8b：\u51b3\u5b9a\u6210\u672c\u7684\u4e0d\u662f\u300c\u53d6\u4e86\u591a\u5c11\u5b57\u8282\u300d，\u662f\u300c\u78b0\u4e86\u591a\u5c11\u6761 cache line\u300d\u3002\u8fd9\u4e00\u8bb2\u628a\u5b83\u91cf\u6210\u4e00\u6761\u53ef\u4ee5\u76f4\u63a5\u7528\u7684\u6362\u7b97\u3002<\/p>\n

    exp08_linecost.cpp \u7528\u5143\u7d20\u5c3a\u5bf8\u4ece 4 \u5b57\u8282\u626b\u5230 128 \u5b57\u8282，\u6bcf\u6b21\u53ea\u8bfb\u5143\u7d20\u5f00\u5934\u7684 4 \u5b57\u8282：<\/p>\n

    \/\/ \u6bcf\u4e2a\u5143\u7d20\u53ea\u53d6\u5f00\u5934\u90a3\u4e2a int\u3002alignas \u628a\u5143\u7d20\u5c3a\u5bf8\u9489\u6b7b\u6210 Sz\u3002<\/span>
    \ntemplate<\/span> <<\/span>std::<\/span>size_t Sz><\/span>
    \nvoid<\/span> sum_aligned<\/span>(<\/span>const<\/span> void<\/span>*<\/span> base,<\/span> std::<\/span>size_t n)<\/span> {<\/span>
    \n struct<\/span> alignas<\/span>(<\/span>Sz)<\/span> E {<\/span> int<\/span> v;<\/span> }<\/span>;<\/span>
    \n static_assert<\/span>(<\/span>sizeof<\/span>(<\/span>E)<\/span> ==<\/span> Sz,<\/span> "\u5bf9\u9f50\u6ca1\u6709\u628a\u5c3a\u5bf8\u9489\u4f4f"<\/span>)<\/span>;<\/span>
    \n const<\/span> E*<\/span> p =<\/span> static_cast<\/span><<\/span>const<\/span> E*<\/span>><\/span><\/span><\/span>(<\/span>base)<\/span>;<\/span>
    \n std::<\/span>uint64_t<\/span> s0 =<\/span> 0<\/span>,<\/span> s1 =<\/span> 0<\/span>;<\/span>
    \n std::<\/span>size_t i =<\/span> 0<\/span>;<\/span>
    \n for<\/span> (<\/span>;<\/span> i +<\/span> 2<\/span> <=<\/span> n;<\/span> i +=<\/span> 2<\/span>)<\/span> {<\/span> s0 +=<\/span> std::<\/span>uint32_t<\/span>(<\/span>p[<\/span>i]<\/span>.<\/span>v)<\/span>;<\/span> s1 +=<\/span> std::<\/span>uint32_t<\/span>(<\/span>p[<\/span>i +<\/span> 1<\/span>]<\/span>.<\/span>v)<\/span>;<\/span> }<\/span>
    \n for<\/span> (<\/span>;<\/span> i <<\/span> n;<\/span> ++<\/span>i)<\/span> s0 +=<\/span> std::<\/span>uint32_t<\/span>(<\/span>p[<\/span>i]<\/span>.<\/span>v)<\/span>;<\/span>
    \n g_sink =<\/span> s0 +<\/span> s1;<\/span>
    \n}<\/span><\/p>\n

    alignas(Sz) \u628a\u5143\u7d20\u5c3a\u5bf8\u9489\u6210 Sz，\u4e0d\u7528\u624b\u5199 padding \u6570\u7ec4\u3002static_assert \u4fdd\u8bc1\u5bf9\u9f50\u786e\u5b9e\u751f\u6548\u4e86\u2014\u2014\u5c11\u4e86\u5b83，alignas(16) \u5230\u5e95\u6709\u6ca1\u6709\u628a sizeof \u9876\u5230 16 \u53ea\u80fd\u9760\u731c\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u300c\u8bfb 4 \u5b57\u8282\u300d\u548c\u300c\u642c 64 \u5b57\u8282\u300d\u662f\u4e24\u7b14\u8d26<\/h4>\n

    \u5148\u770b\u7ed3\u679c\u3002<\/p>\n

    \u5143\u7d20\u5c3a\u5bf8 \u4e00\u884c\u88c5 \u642c\u8fd0\u91cf \u8017\u65f6 \u6bcf\u6b21\u8bbf\u95ee \u642c\u8fd0\u901f\u7387 \u76f8\u5bf9 4B
    \n(\u5b57\u8282) \u51e0\u4e2a (MB) (ms) (ns) (GB\/s)
    \n4 16 16 0.31 ms 0.07 ns 50.3 1.00x
    \n8 8 32 0.55 ms 0.13 ns 56.8 1.77x
    \n16 4 64 1.17 ms 0.28 ns 53.3 3.77x
    \n32 2 128 2.48 ms 0.59 ns 50.3 8.00x
    \n64 1 256 5.07 ms 1.21 ns 49.3 16.31x
    \n128 \u8de8\u4e24\u884c 512 18.26 ms 4.35 ns 27.4 58.77x<\/p>\n

    \u516d\u6863\u7684\u6709\u7528\u6570\u636e\u4e00\u5171 16 MB，\u8bbf\u95ee\u6b21\u6570\u90fd\u662f 4194304\u3002\u4e24\u6837\u90fd\u6ca1\u53d8\u3002<\/p>\n

    \u5143\u7d20\u4ece 4 \u5b57\u8282\u957f\u5230 64 \u5b57\u8282，\u642c\u8fd0\u91cf\u6da8 16 \u500d，\u8017\u65f6\u6da8 16.31 \u500d\u3002<\/p>\n

    \u8bfb\u5230\u7684\u6709\u7528\u6570\u636e\u4e00\u4e2a\u5b57\u8282\u6ca1\u53d8，\u591a\u51fa\u6765\u7684\u94b1\u5168\u82b1\u5728\u300c\u987a\u5e26\u642c\u8fdb\u6765\u7684\u90a3\u4e9b\u5b57\u8282\u300d\u4e0a\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48\u987a\u5e26\u642c\u8fdb\u6765\u7684\u662f 64 \u5b57\u8282\u3002 DRAM \u7684\u5b58\u50a8\u9635\u5217\u4e00\u6b21\u7a81\u53d1\u4f20\u8f93\u5c31\u662f 64 \u5b57\u8282（8 \u6b21 64 \u4f4d\u4f20\u8f93），\u8fd9\u662f\u63a5\u53e3\u5bbd\u5ea6\u5b9a\u6b7b\u7684\u3002\u6240\u4ee5\u4ece\u4e3b\u5b58\u5f80\u7f13\u5b58\u642c\u6570\u636e\u7684\u6700\u5c0f\u5355\u4f4d\u5c31\u662f 64 \u5b57\u8282，\u7f13\u5b58\u884c\u4e5f\u662f 64 \u5b57\u8282\u3002\u4f60\u8bfb 4 \u5b57\u8282，\u786c\u4ef6\u642c 64 \u5b57\u8282，\u5269\u4e0b 60 \u5b57\u8282\u662f\u642d\u8f66\u7684\u3002<\/p>\n

    \u770b\u642c\u8fd0\u901f\u7387\u90a3\u4e00\u5217\u3002 4 \u5230 64 \u5b57\u8282\u4e94\u6863\u90fd\u843d\u5728 49~57 GB\/s，\u5f7c\u6b64\u5dee\u4e0d\u5230 15%\u3002\u540c\u4e00\u6761\u901f\u7387\u51fa\u73b0\u5728\u642c\u8fd0\u91cf\u5dee 16 \u500d\u7684\u4e94\u6bb5\u4ee3\u7801\u91cc，\u8bf4\u660e\u5361\u4f4f\u5b83\u4eec\u7684\u662f\u540c\u4e00\u4ef6\u4e8b\u2014\u2014\u5185\u5b58\u5e26\u5bbd，\u4e0d\u662f\u8bbf\u95ee\u6b21\u6570\u4e5f\u4e0d\u662f\u6307\u4ee4\u6570\u3002\u4e8e\u662f\u6709\u4e86\u4e00\u6761\u6362\u7b97：<\/p>\n

    \u8017\u65f6 \u2248 \u642c\u8fd0\u91cf \u00f7 \u5e26\u5bbd，\u642c\u8fd0\u91cf\u6309 64 \u5b57\u8282\u7684\u884c\u7b97\u3002<\/p>\n

    \u6700\u540e\u4e00\u6863 128 \u5b57\u8282\u6389\u5230 27.4 GB\/s\u3002 \u6bd4\u6309\u6bd4\u4f8b\u5916\u63a8\u7684\u8fd8\u6162\u3002\u5143\u7d20\u8de8\u5728\u4e24\u884c\u4e0a，\u786c\u4ef6\u8981\u51d1\u9f50\u4e24\u6b21\u884c\u586b\u5145\u624d\u80fd\u7ed9\u51fa\u4e00\u4e2a\u5143\u7d20\u2014\u2014\u8fd9\u7b14\u4ee3\u4ef7\u5728\u6392\u7248\u7ed3\u6784\u4f53\u7684\u65f6\u5019\u4f1a\u53cd\u590d\u9047\u5230，\u5355\u5143\u4e09\u4f1a\u4e13\u95e8\u8bb2\u3002<\/p>\n

    \u4ee3\u7801\u9010\u884c<\/h4>\n

    template<\/span> <<\/span>std::<\/span>size_t Sz><\/span>
    \nvoid<\/span> sample_ms<\/span>(<\/span>const<\/span> void<\/span>*<\/span> base,<\/span> std::<\/span>size_t n,<\/span> int<\/span> rounds,<\/span> double<\/span>&<\/span> best,<\/span> double<\/span>&<\/span> median)<\/span> {<\/span>
    \n std::<\/span>vector<<\/span>double<\/span>><\/span> v;<\/span>
    \n v.<\/span>reserve<\/span>(<\/span>static_cast<\/span><<\/span>std::<\/span>size_t><\/span><\/span><\/span>(<\/span>rounds)<\/span>)<\/span>;<\/span>
    \n for<\/span> (<\/span>int<\/span> r =<\/span> 0<\/span>;<\/span> r <<\/span> rounds;<\/span> ++<\/span>r)<\/span> {<\/span>
    \n auto<\/span> t0 =<\/span> clk::<\/span>now<\/span>(<\/span>)<\/span>;<\/span>
    \n sum_aligned<\/span><<\/span>Sz><\/span><\/span><\/span>(<\/span>base,<\/span> n)<\/span>;<\/span>
    \n v.<\/span>push_back<\/span>(<\/span>std::<\/span>chrono::<\/span>duration<\/span><<\/span>double<\/span>,<\/span> std::<\/span>milli><\/span><\/span><\/span>(<\/span>clk::<\/span>now<\/span>(<\/span>)<\/span> –<\/span> t0)<\/span>.<\/span>count<\/span>(<\/span>)<\/span>)<\/span>;<\/span>
    \n }<\/span>
    \n std::<\/span>sort<\/span>(<\/span>v.<\/span>begin<\/span>(<\/span>)<\/span>,<\/span> v.<\/span>end<\/span>(<\/span>)<\/span>)<\/span>;<\/span>
    \n best =<\/span> v.<\/span>front<\/span>(<\/span>)<\/span>;<\/span>
    \n median =<\/span> v[<\/span>v.<\/span>size<\/span>(<\/span>)<\/span> \/<\/span> 2<\/span>]<\/span>;<\/span>
    \n}<\/span><\/p>\n

    \u9664\u4e86\u6700\u5c0f\u503c，\u8fd9\u91cc\u8fd8\u628a\u4e2d\u4f4d\u6570\u4e00\u8d77\u62a5\u51fa\u6765\u3002\u4e24\u8005\u5dee\u5f97\u591a，\u8bf4\u660e\u8fd9\u4e00\u6863\u7684\u8bfb\u6570\u4e0d\u7a33，\u7ed3\u8bba\u5c31\u4e0d\u80fd\u53ea\u9760\u6700\u5c0f\u503c\u6491\u7740\u3002<\/p>\n

    \/\/ \u5c0f\u5c3a\u5bf8\u90a3\u51e0\u6863\u66f4\u5feb\u3001\u8bfb\u6570\u4e5f\u66f4\u98d8，\u591a\u8dd1\u51e0\u8f6e\u624d\u770b\u5f97\u6e05<\/span>
    \nconst<\/span> int<\/span> rounds =<\/span> (<\/span>sz <=<\/span> 16<\/span>)<\/span> ?<\/span> 21<\/span> :<\/span> 7<\/span>;<\/span><\/p>\n

    \u8f6e\u6570\u968f\u5c3a\u5bf8\u53d8\u3002\u8fd9\u4e00\u884c\u662f\u88ab\u4e00\u6b21\u9519\u8bef\u903c\u51fa\u6765\u7684：4 \u5b57\u8282\u90a3\u4e00\u6863\u8dd1 5 \u8f6e\u65f6\u62a5 19.1 GB\/s，\u8dd1\u5230 21 \u8f6e\u624d\u7a33\u5b9a\u5728 48~50 GB\/s\u3002\u524d\u9762\u51e0\u8f6e\u662f\u5728\u7b49\u5185\u5b58\u5b50\u7cfb\u7edf\u548c\u9891\u7387\u8fdb\u7a33\u6001\u3002<\/p>\n

    \u62a5\u8bfb\u6570\u7684\u65f6\u5019\u8fde\u8f6e\u6570\u4e00\u8d77\u62a5，\u8fd9\u6837\u522b\u4eba\u91cd\u8dd1\u65f6\u77e5\u9053\u8be5\u8dd1\u591a\u5c11\u8f6e\u3002<\/p>\n

    \u4ee3\u7801\u8fd0\u884c\u7ed3\u679c<\/h4>\n

    \u89c1\u4e0a\u8868\u3002\u7a0b\u5e8f\u81ea\u5df1\u7ed9\u51fa\u7684\u4e09\u6761\u7ed3\u8bba：<\/p>\n

    \u5143\u7d20\u5c3a\u5bf8\u4ece 4 \u6da8\u5230 64，\u642c\u8fd0\u91cf\u6da8 16 \u500d，\u8017\u65f6\u6da8 16.31 \u500d\u3002<\/p>\n

    \u518d\u770b\u642c\u8fd0\u901f\u7387\u90a3\u4e00\u5217：4 \u5230 64 \u5b57\u8282\u4e94\u6863\u90fd\u843d\u5728 48 GB\/s \u4e0a\u4e0b，
    \n\u8bf4\u660e\u5361\u4f4f\u5b83\u4eec\u7684\u662f\u540c\u4e00\u4ef6\u4e8b\u2014\u2014\u5185\u5b58\u5e26\u5bbd\u3002<\/p>\n

    \u6700\u540e\u4e00\u6863 128 \u5b57\u8282\u6389\u5230 27 GB\/s，\u5143\u7d20\u8de8\u5728\u4e24\u884c\u4e0a\u3002<\/p>\n

    \u5e38\u89c1\u5751<\/h4>\n

    \u5751\u4e00：\u8f6e\u6570\u4e0d\u591f，\u628a\u300c\u8fd8\u6ca1\u70ed\u8eab\u300d\u5f53\u6210\u300c\u8fd9\u4e00\u6863\u66f4\u5feb\u300d\u3002 \u4e0a\u9762\u90a3\u4e00\u884c rounds \u5c31\u662f\u4e3a\u6b64\u5199\u7684\u3002\u56db\u4e2a\u5b57\u8282\u7684\u5143\u7d20\u8bbf\u95ee\u6700\u5feb，\u53d7\u9891\u7387\u722c\u5347\u7684\u5f71\u54cd\u4e5f\u6700\u5927\u3002<\/p>\n

    \u5751\u4e8c：\u4ee5\u4e3a\u5143\u7d20\u5c0f\u5c31\u4e00\u5b9a\u5feb\u3002 \u5143\u7d20\u5c0f\u53ea\u5728\u300c\u4e00\u884c\u88c5\u5f97\u4e0b\u591a\u4e2a\u300d\u65f6\u5212\u7b97\u3002\u8868\u91cc 4 \u5b57\u8282\u548c 8 \u5b57\u8282\u90fd\u662f 8~16 \u4e2a\u4e00\u884c，\u901f\u7387\u53ea\u5dee 13%\u3002\u8df3\u53d8\u53d1\u751f\u5728 64 \u5b57\u8282\u90a3\u4e00\u6863\u2014\u2014\u4e00\u884c\u53ea\u88c5\u5f97\u4e0b\u4e00\u4e2a\u5143\u7d20，\u4ece\u8fd9\u4e00\u6863\u8d77，\u6bcf\u53d6\u4e00\u4e2a\u5143\u7d20\u5c31\u5b9e\u6253\u5b9e\u642c\u4e00\u6574\u884c\u3002<\/p>\n

    \u5751\u4e09：\u628a\u8fd9\u6761\u6362\u7b97\u7528\u5230\u5bb9\u91cf\u53d7\u9650\u7684\u573a\u666f\u4e0a\u3002 \u300c\u8017\u65f6 \u2248 \u642c\u8fd0\u91cf \u00f7 \u5e26\u5bbd\u300d\u6210\u7acb\u7684\u524d\u63d0\u662f\u6570\u636e\u88c5\u4e0d\u8fdb\u7f13\u5b58\u3001\u5fc5\u987b\u4ece\u4e3b\u5b58\u6d41\u8fc7\u6765\u3002\u5982\u679c\u5de5\u4f5c\u96c6\u53ea\u6709\u51e0 MB，\u5168\u90e8\u5f85\u5728 L3 \u91cc，\u8fd9\u6761\u5f0f\u5b50\u7ed9\u7684\u662f\u4e0a\u9650\u800c\u4e0d\u662f\u5b9e\u9645\u503c\u2014\u2014\u90a3\u65f6\u5019\u7684\u74f6\u9888\u5728 L3 \u5e26\u5bbd\u548c L1 \u7ec4\u51b2\u7a81\u4e0a，\u7b2c\u4e94\u8bb2\u91cf\u8fd9\u4e2a\u3002<\/p>\n

    \u6559\u6750\u6307\u5f15<\/h4>\n

    Guntheroth ch2\u3002cache line \u662f 64 \u5b57\u8282\u8fd9\u4e00\u6761\u4ed6\u5728\u8bb2\u7f13\u5b58\u884c\u4e3a\u65f6\u7ed9\u51fa，\u540e\u9762 ch10\u300cOptimize Data Structures\u300d\u6574\u7ae0\u90fd\u5728\u7528\u5b83\u2014\u2014\u7ed3\u6784\u4f53\u600e\u4e48\u6392\u3001AoS \u8fd8\u662f SoA，\u5224\u636e\u90fd\u843d\u56de\u8fd9\u4e00\u6761\u3002<\/p>\n

    \u7b2c\u4e94\u8bb2 \u6539\u904d\u5386\u987a\u5e8f，\u4e0d\u6539\u6570\u636e\u7ed3\u6784<\/h3>\n

    \u662f\u4ec0\u4e48<\/h4>\n

    \u524d\u56db\u8bb2\u628a\u6210\u672c\u63a8\u5230\u4e86\u300c\u78b0\u591a\u5c11\u6761 cache line\u300d\u3002\u8fd9\u4e00\u8bb2\u7ed9\u51fa\u4e00\u4e2a\u5e38\u5e38\u4e0d\u7528\u6539\u4e00\u4e2a\u5b57\u8282\u6570\u636e\u5c31\u80fd\u628a\u6761\u6570\u964d\u4e0b\u6765\u7684\u529e\u6cd5：\u6362\u904d\u5386\u987a\u5e8f\u3002<\/p>\n

    exp09_locality.cpp \u5904\u7406\u4e00\u4e2a N\u00d7N \u7684 int \u77e9\u9635，\u884c\u4f18\u5148\u5b58\u653e，\u6c42\u5168\u90e8\u5143\u7d20\u7684\u548c\u3002\u4e09\u6bb5\u4ee3\u7801\u505a\u540c\u4e00\u4ef6\u4e8b，\u53ea\u6709\u987a\u5e8f\u4e0d\u540c：<\/p>\n

    template<\/span> <<\/span>std::<\/span>size_t N><\/span>
    \nvoid<\/span> sum_rowmajor<\/span>(<\/span>const<\/span> int<\/span>*<\/span> m)<\/span> {<\/span> \/\/ \u4e00\u884c\u4e00\u884c\u5730\u52a0<\/span>
    \n std::<\/span>uint64_t<\/span> s[<\/span>CHAINS]<\/span> =<\/span> {<\/span>}<\/span>;<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> N;<\/span> ++<\/span>i)<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t j =<\/span> 0<\/span>;<\/span> j <<\/span> N;<\/span> ++<\/span>j)<\/span>
    \n s[<\/span>j %<\/span> CHAINS]<\/span> +=<\/span> std::<\/span>uint32_t<\/span>(<\/span>m[<\/span>i *<\/span> N +<\/span> j]<\/span>)<\/span>;<\/span>
    \n g_sink =<\/span> fold<\/span>(<\/span>s)<\/span>;<\/span>
    \n}<\/span><\/p>\n

    template<\/span> <<\/span>std::<\/span>size_t N><\/span>
    \nvoid<\/span> sum_colmajor<\/span>(<\/span>const<\/span> int<\/span>*<\/span> m)<\/span> {<\/span> \/\/ \u4e00\u5217\u4e00\u5217\u5730\u52a0<\/span>
    \n std::<\/span>uint64_t<\/span> s[<\/span>CHAINS]<\/span> =<\/span> {<\/span>}<\/span>;<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t j =<\/span> 0<\/span>;<\/span> j <<\/span> N;<\/span> ++<\/span>j)<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> N;<\/span> ++<\/span>i)<\/span>
    \n s[<\/span>i %<\/span> CHAINS]<\/span> +=<\/span> std::<\/span>uint32_t<\/span>(<\/span>m[<\/span>i *<\/span> N +<\/span> j]<\/span>)<\/span>;<\/span>
    \n g_sink =<\/span> fold<\/span>(<\/span>s)<\/span>;<\/span>
    \n}<\/span><\/p>\n

    \u7b2c\u4e09\u6bb5 sum_blocked \u628a\u77e9\u9635\u5207\u6210 16\u00d716 \u7684\u5c0f\u65b9\u5757，\u5757\u5185\u6309\u884c\u52a0，\u5757\u4e4b\u95f4\u6309\u5217\u8d70\u3002<\/p>\n

    \u4e3a\u4ec0\u4e48 4 MB \u88c5\u5f97\u8fdb L3，\u8fd8\u662f\u6162 12.7 \u500d<\/h4>\n

    N \u53d6\u4e09\u6863，\u5de5\u4f5c\u96c6\u5206\u522b\u662f 16KB\u30014MB\u300164MB：<\/p>\n

    16 KB（\u6574\u5757\u88c5\u5f97\u8fdb L1）
    \n\u904d\u5386\u987a\u5e8f \u8017\u65f6 \u6bcf\u6b21\u8bbf\u95ee \u76f8\u5bf9\u884c\u4f18\u5148
    \n\u884c\u4f18\u5148 0.0014 ms 0.34 ns 1.0x
    \n\u5217\u4f18\u5148 0.0016 ms 0.38 ns 1.1x
    \n\u5206\u5757 16 0.0021 ms 0.51 ns 1.5x
    \n\u884c\u4f18\u5148 \/ \u5217\u4f18\u5148 = 1.1 \u500d<\/p>\n

    4 MB（L1 \u88c5\u4e0d\u4e0b，L3 \u88c5\u5f97\u4e0b）
    \n\u884c\u4f18\u5148 0.3981 ms 0.38 ns 1.0x
    \n\u5217\u4f18\u5148 5.0396 ms 4.81 ns 12.7x
    \n\u5206\u5757 16 0.4015 ms 0.38 ns 1.0x
    \n\u884c\u4f18\u5148 \/ \u5217\u4f18\u5148 = 12.7 \u500d<\/p>\n

    64 MB（L3 \u4e5f\u88c5\u4e0d\u4e0b）
    \n\u884c\u4f18\u5148 5.8857 ms 0.35 ns 1.0x
    \n\u5217\u4f18\u5148 117.9601 ms 7.03 ns 20.0x
    \n\u5206\u5757 16 8.0741 ms 0.48 ns 1.4x
    \n\u884c\u4f18\u5148 \/ \u5217\u4f18\u5148 = 20.0 \u500d<\/p>\n

    \u500d\u7387\u8fd9\u6837\u8d70：1.1 \u2192 12.7 \u2192 20.0\u3002<\/p>\n

    \u6211\u8dd1\u4e4b\u524d\u731c\u7684\u662f\u7b2c\u4e8c\u6863\u5e94\u8be5\u6ca1\u4e8b\u2014\u20144MB \u6574\u5757\u90fd\u5728 16MB \u7684 L3 \u91cc\u5f85\u7740\u3002\u5b9e\u6d4b 12.7 \u500d\u3002<\/p>\n

    \u5148\u7b97\u6e05\u695a\u4e3a\u4ec0\u4e48\u3002\u4e09\u4e2a\u7f13\u5b58\u5404\u6709\u591a\u5c11\u4e2a\u7ec4，\u51b3\u5b9a\u6b65\u957f\u4f1a\u4e0d\u4f1a\u649e\u8f66\u3002\u672c\u673a\u7684\u51e0\u4f55（\u4ece sysfs \u8bfb，\u4e0d\u662f\u80cc\u7684）：<\/p>\n\n\u5bb9\u91cf\u76f8\u8054\u5ea6\u7ec4\u6570<\/tr>\n\n\n\n\n
    L1d<\/td>\n32 KB<\/td>\n8 \u8def<\/td>\n64<\/td>\n<\/tr>\n
    L2<\/td>\n1 MB<\/td>\n8 \u8def<\/td>\n2048<\/td>\n<\/tr>\n
    L3<\/td>\n16 MB<\/td>\n16 \u8def<\/td>\n16384<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u7ec4\u6570\u5168\u662f 2 \u7684\u5e42\u3002 \u8fd9\u4e00\u6761\u662f\u6574\u4ef6\u4e8b\u7684\u6765\u6e90\u3002<\/p>\n

    N=1024 \u65f6\u5217\u4f18\u5148\u7684\u6b65\u957f\u662f 1024 \u4e2a int = 4096 \u5b57\u8282 = 64 \u6761 cache line\u3002\u5730\u5740\u843d\u5728\u54ea\u4e2a\u7ec4，\u770b\u7684\u662f\u884c\u53f7\u5bf9\u7ec4\u6570\u53d6\u6a21\u3002\u6240\u4ee5\u540c\u4e00\u5217\u4e0a\u76f8\u90bb\u4e24\u6b21\u8bbf\u95ee，\u7ec4\u53f7\u76f8\u5dee 64\u3002<\/p>\n

    \u5bf9\u4e09\u7ea7\u5206\u522b\u7b97：<\/p>\n

    L1 64 mod 64 = 0 \u2192 1024 \u6b21\u8bbf\u95ee\u5168\u843d 1 \u4e2a\u7ec4， 8 \u8def\u88c5 1024 \u6761 \u2192 \u5168\u584c
    \nL2 64 mod 2048 = 64 \u2192 \u843d\u5728 32 \u4e2a\u7ec4，\u6bcf\u7ec4 32 \u6761， 8 \u8def\u88c5 32 \u6761 \u2192 \u584c
    \nL3 64 mod 16384 = 64 \u2192 \u843d\u5728 256 \u4e2a\u7ec4，\u6bcf\u7ec4 4 \u6761， 16 \u8def\u88c5 4 \u6761 \u2192 \u88c5\u5f97\u4e0b<\/p>\n

    L3 \u88c5\u5f97\u4e0b，L1 \u548c L2 \u90fd\u584c\u30024MB \u7684\u6570\u636e\u5728 L3 \u91cc\u653e\u5f97\u597d\u597d\u7684，\u800c L1 \u6bcf\u6b21\u53bb\u770b\u90fd\u662f\u7a7a\u7684\u2014\u2014\u8fd9\u4e0d\u662f\u5bb9\u91cf\u4e0d\u591f，\u662f\u7ec4\u51b2\u7a81\u3002<\/p>\n

    N=64 \u65f6\u6b65\u957f\u662f 256 \u5b57\u8282 = 4 \u6761 line，\u5bf9 64 \u53d6\u6a21\u7b49\u4e8e 4，64 \u6b21\u8bbf\u95ee\u4f9d\u6b21\u843d\u5728 16 \u4e2a\u7ec4\u4e0a，\u6bcf\u7ec4 4 \u6761，8 \u8def\u88c5\u5f97\u4e0b\u3002\u6240\u4ee5\u7b2c\u4e00\u6863\u53ea\u6709 1.1 \u500d\u3002<\/p>\n

    N=4096 \u65f6\u6b65\u957f\u662f 16384 \u5b57\u8282 = 256 \u6761 line：<\/p>\n

    L1 256 mod 64 = 0 \u2192 1 \u4e2a\u7ec4，4096 \u6761 \u2192 \u584c
    \nL2 256 mod 2048 = 256 \u2192 8 \u4e2a\u7ec4，\u6bcf\u7ec4 512 \u6761 \u2192 \u584c
    \nL3 256 mod 16384 = 256 \u2192 64 \u4e2a\u7ec4，\u6bcf\u7ec4 64 \u6761，16 \u8def\u88c5 64 \u6761 \u2192 \u4e5f\u584c\u4e86<\/p>\n

    \u8fd9\u4e00\u6863\u4e09\u7ea7\u5168\u584c，\u6240\u4ee5\u500d\u7387\u4ece 12.7 \u6da8\u5230 20.0\u3002<\/p>\n

    \u7528 perf \u628a\u8fd9\u4ef6\u4e8b\u91cf\u51fa\u6765<\/h4>\n

    \u4e0a\u9762\u5168\u662f\u7b97\u672f\u3002\u786c\u4ef6\u8ba1\u6570\u5668\u80fd\u7ed9\u51fa\u72ec\u7acb\u7684\u8bc1\u636e\u3002exp09_locality \u6709\u4e00\u4e2a\u5355\u6863\u5165\u53e3，\u4e13\u4f9b\u5916\u90e8\u5de5\u5177\u8ba1\u6570：<\/p>\n

    $ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses .\/exp09_locality 1024<\/span> none
    \n$ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses .\/exp09_locality 1024<\/span> row
    \n$ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses .\/exp09_locality 1024<\/span> col
    \n$ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses .\/exp09_locality 1024<\/span> blk<\/p>\n

    none \u6863\u53ea\u5efa\u77e9\u9635\u4e0d\u904d\u5386\u3002\u5b83\u5b58\u5728\u7684\u7406\u7531\u662f：\u8ba1\u6570\u5668\u6570\u7684\u662f\u8fdb\u7a0b\u505a\u8fc7\u7684\u5168\u90e8\u4e8b\u60c5\u3002 \u5efa\u90a3\u4e2a 4MB \u77e9\u9635\u672c\u8eab\u5c31\u6709\u5185\u5b58\u6d41\u91cf，\u4e0d\u6253\u6389\u7684\u8bdd\u4f1a\u7a00\u91ca\u6389\u4e09\u6863\u4e4b\u95f4\u7684\u5dee\u522b\u3002\u4e24\u6761\u547d\u4ee4\u76f8\u51cf，\u662f\u8fd9\u7c7b\u5de5\u5177\u7684\u901a\u7528\u5957\u8def\u3002<\/p>\n

    N=1024，\u6bcf\u6863 30 \u904d，\u4e00\u5171 31,457,280 \u6b21\u8bbf\u95ee\u3002\u51cf\u6389 none \u57fa\u7ebf\u540e：<\/p>\n\n\u904d\u5386\u987a\u5e8fL1 \u8bfb miss\u5360\u8bbf\u95ee\u6b21\u6570L2 miss\u5360\u8bbf\u95ee\u6b21\u6570<\/tr>\n\n\n\n\n
    \u884c\u4f18\u5148<\/td>\n1,993,090<\/td>\n6.3%<\/td>\n32,094<\/td>\n0.10%<\/td>\n<\/tr>\n
    \u5217\u4f18\u5148<\/td>\n33,442,254<\/td>\n106.3%<\/td>\n16,227,239<\/td>\n51.6%<\/td>\n<\/tr>\n
    \u5206\u5757 16<\/td>\n6,251,754<\/td>\n19.9%<\/td>\n312,837<\/td>\n1.0%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u884c\u4f18\u5148\u7684 L1 miss \u6570，\u6b63\u597d\u7b49\u4e8e\u5b83\u78b0\u5230\u7684 cache line \u6761\u6570\u3002 4MB \u77e9\u9635\u662f 65536 \u6761 line，\u8dd1 30 \u904d\u5c31\u662f 1,966,080 \u6b21\u9996\u89e6\u3002\u591a\u6b21\u8fd0\u884c\u5b9e\u6d4b\u5728 1,971,190 \u5230 1,993,090 \u4e4b\u95f4，\u6bd4\u7406\u8bba\u503c\u9ad8 0.26% \u5230 1.4%\u3002\u7b2c\u56db\u8bb2\u90a3\u6761\u300c\u786c\u4ef6\u6309\u884c\u8bb0\u8d26\u300d，\u5728\u8fd9\u91cc\u88ab\u76f4\u63a5\u91cf\u5230\u4e86\u3002<\/p>\n

    \u5217\u4f18\u5148\u78b0\u7684\u662f\u540c\u4e00\u6279 line，\u5374\u62a5\u4e86 33,442,254 \u6b21\u2014\u2014\u540c\u4e00\u5757\u6570\u636e\u591a\u642c\u4e86 16.8 \u500d\u3002 \u591a\u51fa\u6765\u7684\u90e8\u5206\u5168\u662f\u584c\u6389\u4e4b\u540e\u53cd\u590d\u53d6\u56de\u3002<\/p>\n

    L2 \u90a3\u4e00\u5217\u5dee\u5f97\u66f4\u8fdc：32,094 \u5bf9 16,227,239，\u4e24\u4e2a\u6570\u91cf\u7ea7\u3002\u8fd9\u548c\u4e0a\u9762\u90a3\u5f20\u51e0\u4f55\u8868\u5bf9\u5f97\u4e0a\u2014\u2014L3 \u88c5\u5f97\u4e0b，L1 \u548c L2 \u90fd\u88c5\u4e0d\u4e0b\u3002<\/p>\n

    \u884c\u4f18\u5148\u90a3\u683c\u7684 L2 \u6570\u8981\u6253\u4e2a\u6298\u770b\u3002\u5b83\u662f\u4e24\u4e2a\u5c0f\u6570\u5b57\u76f8\u51cf\u5f97\u6765\u7684（row \u7684 95,572 \u51cf none \u7684 63,478），\u800c L2 \u6b63\u662f\u4e09\u6863\u91cc\u6700\u4e0d\u7a33\u7684\u4e00\u5217，\u8dd1\u51e0\u6b21\u80fd\u5728\u51e0\u4e07\u8fd9\u4e2a\u91cf\u7ea7\u4e0a\u6643\u4e00\u500d\u3002\u7a33\u7684\u662f\u5217\u4f18\u5148\u90a3\u4e00\u683c\u2014\u2014\u4e00\u5343\u516d\u767e\u4e07\u8fd9\u4e2a\u6570\u843d\u5728\u4e24\u4e2a\u6570\u91cf\u7ea7\u7684\u5dee\u8ddd\u4e0a，\u600e\u4e48\u6643\u90fd\u4e0d\u4f1a\u53cd\u8fc7\u6765\u3002\u62a5\u6570\u65f6\u6309\u7a33\u5b9a\u6027\u5206\u5f00\u5bf9\u5f85，\u4e0d\u662f\u6240\u6709\u683c\u5b50\u90fd\u914d\u5f97\u4e0a\u540c\u6837\u7684\u4f4d\u6570\u3002<\/p>\n

    \u5206\u5757\u662f\u600e\u4e48\u628a\u8fd9\u4ef6\u4e8b\u6309\u56de\u53bb\u7684\u3002 \u5757\u5185 16 \u4e2a int \u6b63\u597d\u5360\u6ee1\u4e00\u884c；\u5757\u53ea\u6709 16 \u884c，\u4e00\u6574\u4e2a\u5757\u7684\u5de5\u4f5c\u96c6\u662f 16\u00d764 = 1KB，\u88c5\u5f97\u4e0b L1\u3002\u5757\u5185\u6309\u884c\u52a0，\u6bcf\u6b21\u8bbf\u95ee\u7528\u6ee1\u4e00\u884c；\u6362\u5230\u4e0b\u4e00\u4e2a\u5757\u65f6，\u524d\u9762\u7684\u5757\u5df2\u7ecf\u7528\u5b8c\u4e86，\u88ab\u6324\u51fa\u53bb\u4e5f\u65e0\u6240\u8c13\u3002<\/p>\n

    \u4e09\u6863\u91cc\u5206\u5757\u5206\u522b\u53ea\u6bd4\u884c\u4f18\u5148\u8d35 1.50\u30011.01\u30011.37 \u500d\u3002\u6570\u636e\u5e03\u5c40\u4e00\u4e2a\u5b57\u8282\u90fd\u6ca1\u52a8，\u6539\u7684\u53ea\u662f\u904d\u5386\u987a\u5e8f\u3002<\/p>\n

    \u4ee3\u7801\u9010\u884c<\/h4>\n

    \/\/ \u6bcf\u6761\u7d2f\u52a0\u94fe\u53ea\u5e26 1 \u6b21\u52a0\u6cd5\u3002\u591a\u5f00\u51e0\u6761，\u8ba9\u5185\u5c42\u4e0d\u88ab\u52a0\u6cd5\u5ef6\u8fdf\u5361\u4f4f，<\/span>
    \n\/\/ \u8fd9\u6837\u91cf\u5230\u7684\u5dee\u522b\u624d\u5f52\u56e0\u5230\u8bbf\u5b58\u4e0a\u3002<\/span>
    \nconstexpr<\/span> int<\/span> CHAINS =<\/span> 4<\/span>;<\/span><\/p>\n

    inline<\/span> std::<\/span>uint64_t<\/span> fold<\/span>(<\/span>const<\/span> std::<\/span>uint64_t<\/span> (<\/span>&<\/span>s)<\/span>[<\/span>CHAINS]<\/span>)<\/span> {<\/span>
    \n return<\/span> s[<\/span>0<\/span>]<\/span> +<\/span> s[<\/span>1<\/span>]<\/span> +<\/span> s[<\/span>2<\/span>]<\/span> +<\/span> s[<\/span>3<\/span>]<\/span>;<\/span>
    \n}<\/span><\/p>\n

    CHAINS = 4 \u7684\u4f5c\u7528\u548c\u4e0a\u4e00\u8bb2\u7684 s0\/s1 \u4e00\u6837，\u53ea\u662f\u8fd9\u91cc\u7528\u6570\u7ec4\u7edf\u4e00\u5904\u7406\u3002\u6309 j % CHAINS \u8f6e\u6d41\u7d2f\u52a0，\u56db \u6761\u94fe\u4e92\u76f8\u72ec\u7acb\u3002<\/p>\n

    \/\/ \u77e9\u9635\u8d8a\u5c0f\u8d8a\u5feb，\u8d8a\u8981\u8dd1\u591f\u8f6e\u6570\u628a\u70ed\u8eab\u644a\u6389；\u5927\u77e9\u9635\u7684\u5217\u4f18\u5148\u662f\u79d2\u7ea7，\u5c11\u8dd1\u51e0\u8f6e<\/span>
    \nconst<\/span> int<\/span> rounds =<\/span> (<\/span>N <=<\/span> 128<\/span>)<\/span> ?<\/span> 21<\/span> :<\/span> (<\/span>N <=<\/span> 1024<\/span> ?<\/span> 9<\/span> :<\/span> 3<\/span>)<\/span>;<\/span>
    \nconst<\/span> int<\/span> repeat =<\/span> (<\/span>N <=<\/span> 128<\/span>)<\/span> ?<\/span> 300<\/span> :<\/span> 1<\/span>;<\/span><\/p>\n

    repeat \u662f\u628a\u540c\u4e00\u6bb5\u8dd1 repeat \u904d\u518d\u9664\u4ee5 repeat\u3002N=64 \u65f6\u6574\u6bb5\u53ea\u6709 5 \u5fae\u79d2，\u76f4\u63a5\u91cf\u4f1a\u88ab\u65f6\u949f\u7cbe\u5ea6\u5403\u6389\u2014\u2014\u5355\u6b21 steady_clock::now() \u8981 16~18 ns（\u5355\u5143\u4e00 exp04）\u3002\u8dd1 300 \u904d\u628a\u603b\u65f6\u957f\u6491\u5230\u6beb\u79d2\u7ea7\u3002<\/p>\n

    \u8fd9\u662f\u5355\u5143\u4e00\u7b2c\u56db\u8bb2\u90a3\u6761\u89c4\u5219\u7684\u76f4\u63a5\u5e94\u7528：\u8981\u91cf\u4e00\u6bb5\u6bd4\u5c3a\u5b50\u8fd8\u77ed\u7684\u4ee3\u7801，\u5c31\u628a\u5b83\u5305\u8fdb\u4e00\u6279\u518d\u644a\u8584\u3002<\/p>\n

    sample<\/span>(<\/span>[<\/span>&<\/span>]<\/span> {<\/span> sum_rowmajor<\/span><<\/span>N><\/span><\/span><\/span>(<\/span>m.<\/span>data<\/span>(<\/span>)<\/span>)<\/span>;<\/span> }<\/span>,<\/span> rounds,<\/span> repeat,<\/span> r_best,<\/span> r_med)<\/span>;<\/span>
    \nsample<\/span>(<\/span>[<\/span>&<\/span>]<\/span> {<\/span> sum_colmajor<\/span><<\/span>N><\/span><\/span><\/span>(<\/span>m.<\/span>data<\/span>(<\/span>)<\/span>)<\/span>;<\/span> }<\/span>,<\/span> rounds,<\/span> repeat,<\/span> c_best,<\/span> c_med)<\/span>;<\/span>
    \nsample<\/span>(<\/span>[<\/span>&<\/span>]<\/span> {<\/span> sum_blocked<\/span><<\/span>N><\/span><\/span><\/span>(<\/span>m.<\/span>data<\/span>(<\/span>)<\/span>,<\/span> 16<\/span>)<\/span>;<\/span> }<\/span>,<\/span> rounds,<\/span> repeat,<\/span> b_best,<\/span> b_med)<\/span>;<\/span><\/p>\n

    \u4e09\u6bb5\u5404\u8dd1\u5404\u7684，\u53d6\u5404\u81ea\u7684\u6700\u5c0f\u503c\u518d\u6bd4\u3002\u4e0d\u8981\u5728\u540c\u4e00\u8f6e\u91cc\u6df7\u7740\u8dd1\u4e09\u6bb5\u518d\u6bd4\u603b\u548c，\u90a3\u6837\u524d\u4e00\u6bb5\u4f1a\u628a\u7f13\u5b58\u72b6\u6001\u7559\u7ed9\u540e\u4e00\u6bb5，\u6bd4\u7684\u662f\u8dd1\u7684\u987a\u5e8f\u3002<\/p>\n

    \u4ee3\u7801\u8fd0\u884c\u7ed3\u679c<\/h4>\n

    \u89c1\u4e0a\u8868\u3002\u7a0b\u5e8f\u5728\u7ed3\u5c3e\u7ed9\u4e86\u4e00\u6761\u5173\u4e8e\u81ea\u5df1\u7ed3\u8bba\u9002\u7528\u8303\u56f4\u7684\u63d0\u793a：<\/p>\n

    \u500d\u7387\u4e0d\u662f\u4e00\u4e2a\u80fd\u80cc\u4e0b\u6765\u7684\u5e38\u6570\u3002\u540c\u4e00\u6bb5\u4ee3\u7801，\u77e9\u9635\u4ece 4 MB \u957f\u5230 64 MB，
    \n\u500d\u7387\u5c31\u4ece 12.7 \u8d70\u5230 20.0\u3002\u62a5\u4e00\u4e2a\u6570\u5b57\u7684\u65f6\u5019，\u628a\u89c4\u6a21\u4e00\u8d77\u62a5\u4e0a\u3002<\/p>\n

    \u5e38\u89c1\u5751<\/h4>\n

    \u5751\u4e00：\u628a\u300c\u6162 20 \u500d\u300d\u5f53\u6210\u4e00\u4e2a\u53ef\u4ee5\u80cc\u7684\u5e38\u6570\u3002 \u500d\u7387\u968f\u89c4\u6a21\u53d8\u3002\u540c\u4e00\u4efd\u6e90\u7801，16KB \u65f6\u662f 1.1 \u500d，64MB \u65f6\u662f 20 \u500d\u3002\u79bb\u5f00\u89c4\u6a21\u8c08\u500d\u6570\u6ca1\u6709\u610f\u4e49\u3002<\/p>\n

    \u5751\u4e8c：\u4ee5\u4e3a\u5206\u5757\u8981\u8c03\u5f88\u591a\u53c2\u6570\u3002 \u672c\u673a\u7684\u5206\u5757\u8fb9\u957f 16 \u4e0d\u662f\u8c03\u51fa\u6765\u7684，\u662f\u7b97\u51fa\u6765\u7684：\u4e00\u884c 64 \u5b57\u8282，int \u662f 4 \u5b57\u8282，16 \u4e2a\u4e00\u884c\u3002\u6362 double \u5c31\u662f 8 \u4e2a\u4e00\u884c\u3002\u5206\u5757\u8fb9\u957f\u5148\u53d6\u300c\u4e00\u884c\u88c5\u51e0\u4e2a\u300d，\u518d\u770b\u6574\u4e2a\u5757\u88c5\u4e0d\u88c5\u5f97\u4e0b L1，\u901a\u5e38\u4e00\u6b21\u5c31\u4e2d\u3002<\/p>\n

    \u5751\u4e09：\u53ea\u76ef\u7740 L3 \u770b\u3002 \u7ec4\u51b2\u7a81\u53d1\u751f\u5728 L1，\u800c L1 \u53ea\u6709 32KB\u3002\u6240\u6709\u4ee5 2 \u7684\u5e42\u4e3a\u6b65\u957f\u7684\u8bbf\u95ee\u90fd\u8981\u68c0\u67e5\u4e00\u904d\u4f1a\u4e0d\u4f1a\u5168\u843d\u8fdb\u540c\u4e00\u4e2a\u7ec4\u2014\u2014\u8fd9\u662f\u5e03\u5c40\u95ee\u9898\u7684\u5e38\u89c1\u6765\u6e90，\u5355\u5143\u4e09\u4f1a\u518d\u9047\u5230\u3002<\/p>\n

    \u6559\u6750\u6307\u5f15<\/h4>\n

    Guntheroth ch2 \u7ed9\u4e86\u5c40\u90e8\u6027\u7684\u5b9a\u6027\u63cf\u8ff0\u548c\u300c\u6309\u884c\u8fd8\u662f\u6309\u5217\u300d\u7684\u4f8b\u5b50\u3002\u5206\u5757\u5728 ch10 \u8bb2\u6570\u636e\u7ed3\u6784\u4f18\u5316\u65f6\u4f5c\u4e3a\u624b\u6cd5\u51fa\u73b0\u3002<\/p>\n

    A \u7ebf\u4efb\u52a1 \u00b7 probe v0.2：\u62d0\u70b9\u626b\u63cf\u5668<\/h3>\n

    \u5355\u5143\u4e00\u9020\u4e86 probe \u7684\u56db\u4e2a\u96f6\u4ef6：\u5206\u4f4d\u6570\u3001\u6837\u672c\u96c6\u3001\u8ba1\u65f6\u5668\u3001\u5bf9\u6570\u76f4\u65b9\u56fe\u3002\u8fd9\u4e00\u7248\u52a0\u7b2c\u4e94\u4e2a\u2014\u2014\u62d0\u70b9\u626b\u63cf\u5668，\u628a\u672c\u5355\u5143\u624b\u5199\u7684\u90a3\u5957\u300c\u626b\u4e00\u5708\u89c4\u6a21\u3001\u7b97\u500d\u6570\u3001\u6807\u53f0\u9636\u300d\u6536\u6210\u4e00\u4e2a\u51fd\u6570\u3002<\/p>\n

    struct<\/span> SweepPoint<\/span> {<\/span>
    \n std::<\/span>size_t bytes =<\/span> 0<\/span>;<\/span> \/\/ \u5de5\u4f5c\u96c6\u5927\u5c0f<\/span>
    \n std::<\/span>size_t items =<\/span> 0<\/span>;<\/span> \/\/ \u8ba1\u6570\u5355\u4f4d\u4e2a\u6570<\/span>
    \n double<\/span> ns_per_item =<\/span> 0<\/span>;<\/span>
    \n double<\/span> ratio =<\/span> 1.0<\/span>;<\/span> \/\/ \u76f8\u5bf9\u6700\u5c0f\u89c4\u6a21\u90a3\u4e00\u70b9\u7684\u500d\u6570<\/span>
    \n bool<\/span> knee =<\/span> false<\/span>;<\/span> \/\/ \u76f8\u5bf9\u4e0a\u4e00\u70b9\u8df3\u4e86 1.8 \u500d\u4ee5\u4e0a<\/span>
    \n}<\/span>;<\/span><\/p>\n

    template<\/span> <<\/span>typename<\/span> Make<\/span>,<\/span> typename<\/span> Body<\/span>,<\/span> typename<\/span> ItemsOf<\/span>><\/span>
    \nstd::<\/span>vector<<\/span>SweepPoint><\/span> sweep<\/span>(<\/span>const<\/span> std::<\/span>vector<<\/span>std::<\/span>size_t><\/span>&<\/span> sizes,<\/span> int<\/span> rounds,<\/span>
    \n Make make,<\/span> Body body,<\/span> ItemsOf items_of)<\/span>;<\/span><\/p>\n

    \u4e09\u4e2a\u8bbe\u8ba1\u51b3\u5b9a，\u6bcf\u4e00\u4e2a\u90fd\u662f\u88ab\u524d\u9762\u51e0\u8bb2\u7684\u5751\u903c\u51fa\u6765\u7684\u3002<\/p>\n

    \u4e00\u3001make \u548c body \u5206\u5f00，make \u4e0d\u8ba1\u65f6\u3002 \u9020\u6570\u636e\u672c\u8eab\u53ef\u80fd\u8981\u51e0\u767e\u6beb\u79d2（\u6bd4\u5982\u7ed9 64MB \u6570\u7ec4\u5efa\u4e00\u4e2a\u968f\u673a\u73af），\u6df7\u8fdb\u8ba1\u65f6\u7ed3\u679c\u4f1a\u628a\u7ed3\u8bba\u5e26\u504f\u3002\u5206\u5f00\u4e4b\u540e，\u8ba1\u65f6\u533a\u95f4\u91cc\u53ea\u5269\u4f60\u8981\u91cf\u7684\u90a3\u6bb5\u3002<\/p>\n

    \u4e8c\u3001items_of \u5fc5\u4f20\u3002 \u5de5\u4f5c\u96c6\u7684\u5355\u4f4d\u662f\u5b57\u8282，\u4f46\u4f60\u5173\u5fc3\u7684\u5355\u4f4d\u53ef\u80fd\u662f\u5143\u7d20\u3002\u5c11\u4e86\u8fd9\u4e2a\u6362\u7b97，\u62a5\u51fa\u6765\u7684\u300c\u6bcf\u5143\u7d20\u8017\u65f6\u300d\u4f1a\u8ddf\u7740\u5143\u7d20\u5927\u5c0f\u53d8，\u4e24\u79cd\u5143\u7d20\u7684\u4ee3\u7801\u5c31\u6ca1\u6cd5\u6bd4\u3002\u9ed8\u8ba4\u6309\u5b57\u8282\u7b97，\u8981\u6309\u5143\u7d20\u7b97\u5c31\u4f20 bytes \/ 4\u3002<\/p>\n

    \u4e09\u3001\u53f0\u9636\u5224\u636e\u5199\u6b7b\u6210\u5e38\u91cf，\u5e76\u4e14\u6253\u5370\u51fa\u6765\u3002<\/p>\n

    constexpr<\/span> double<\/span> KNEE_RATIO =<\/span> 1.8<\/span>;<\/span>
    \n const<\/span> double<\/span> base =<\/span> pts.<\/span>empty<\/span>(<\/span>)<\/span> ?<\/span> 1.0<\/span> :<\/span> pts.<\/span>front<\/span>(<\/span>)<\/span>.<\/span>ns_per_item;<\/span>
    \n for<\/span> (<\/span>std::<\/span>size_t i =<\/span> 0<\/span>;<\/span> i <<\/span> pts.<\/span>size<\/span>(<\/span>)<\/span>;<\/span> ++<\/span>i)<\/span> {<\/span>
    \n pts[<\/span>i]<\/span>.<\/span>ratio =<\/span> base ><\/span> 0<\/span> ?<\/span> pts[<\/span>i]<\/span>.<\/span>ns_per_item \/<\/span> base :<\/span> 1.0<\/span>;<\/span>
    \n pts[<\/span>i]<\/span>.<\/span>knee =<\/span> (<\/span>i ><\/span> 0<\/span>)<\/span> &&<\/span> (<\/span>pts[<\/span>i]<\/span>.<\/span>ns_per_item ><\/span> pts[<\/span>i –<\/span> 1<\/span>]<\/span>.<\/span>ns_per_item *<\/span> KNEE_RATIO)<\/span>;<\/span>
    \n }<\/span><\/p>\n

    1.8 \u662f\u7ecf\u9a8c\u503c：\u7f13\u5b58\u8fb9\u754c\u4e0a\u901a\u5e38\u8df3 2 \u500d\u4ee5\u4e0a，\u566a\u58f0\u5219\u8fdc\u4f4e\u4e8e\u8fd9\u4e2a\u95e8\u69db\u3002\u9009 1.8 \u800c\u4e0d\u662f\u300c\u770b\u7740\u50cf\u53f0\u9636\u5c31\u7b97\u300d，\u662f\u4e3a\u4e86\u8ba9\u5224\u636e\u53ef\u4ee5\u88ab\u522b\u4eba\u590d\u7b97\u3002\u628a\u5224\u636e\u5199\u8fdb\u4ee3\u7801\u3001\u6253\u5370\u5728\u8f93\u51fa\u91cc，\u522b\u4eba\u624d\u80fd\u4e0d\u540c\u610f\u4f60\u7684\u5224\u636e\u5e76\u4e14\u6307\u51fa\u6765\u3002<\/p>\n

    \u9a8c\u6536：\u65b0\u5de5\u5177\u4e0d\u80fd\u6539\u6389\u6d4b\u6cd5<\/h4>\n

    probe_sweep_demo.cpp \u7528 probe::sweep \u91cd\u505a exp06 \u7684\u7f13\u5b58\u9636\u68af，\u548c\u624b\u5199\u7248\u9010\u4e2a\u5bf9\u7167\u3002<\/p>\n

    $ g++ -std<\/span>=<\/span>c++23 -O2<\/span> -Wall<\/span> -Wextra<\/span> -o<\/span> probe_sweep_demo probe_sweep_demo.cpp
    \n$ taskset -c<\/span> 15<\/span> .\/probe_sweep_demo<\/p>\n

    \u5de5\u4f5c\u96c6 \u8ba1\u6570\u5355\u4f4d \u6bcf\u5355\u4f4d\u8017\u65f6 \u76f8\u5bf9\u6700\u5c0f
    \n 16<\/span> KB 12288<\/span> 1.04<\/span> ns 1<\/span>.00x
    \n 64<\/span> KB 49152<\/span> 2.08<\/span> ns 2<\/span>.00x \u25c0 \u62d0\u70b9
    \n 256<\/span> KB 196608<\/span> 2.74<\/span> ns 2<\/span>.64x
    \n 1<\/span> MB 786432<\/span> 4.13<\/span> ns 3<\/span>.98x
    \n 4<\/span> MB 3145728<\/span> 9.89<\/span> ns 9<\/span>.52x \u25c0 \u62d0\u70b9
    \n 16<\/span> MB 12582912<\/span> 28.27<\/span> ns 27<\/span>.22x \u25c0 \u62d0\u70b9
    \n 64<\/span> MB 50331648<\/span> 84.95<\/span> ns 81<\/span>.78x \u25c0 \u62d0\u70b9<\/p>\n

    \u548c exp06 \u624b\u5199\u7248\u5bf9\u7167（\u6bcf\u6b65\u5ef6\u8fdf，\u53d6\u4e09\u8f6e\u6700\u5c0f\u503c）：
    \n \u5de5\u4f5c\u96c6 exp06 \u624b\u5199 \u672c demo \u504f\u5dee
    \n 16<\/span> KB 1.04<\/span> ns 1.04<\/span> ns -0.1%
    \n 1024<\/span> KB 5.36<\/span> ns 4.13<\/span> ns -23.0%
    \n 16384<\/span> KB 34.09<\/span> ns 28.27<\/span> ns -17.1%
    \n 65536<\/span> KB 90.01<\/span> ns 84.95<\/span> ns -5.6%<\/p>\n

    \u8fd9\u6b21\u8bd5\u9a8c\u7b2c\u4e00\u6b21\u8dd1\u51fa\u6765\u7684\u662f\u9519\u7684，\u800c\u4e14\u9519\u5f97\u4e0d\u660e\u663e\u3002<\/p>\n

    \u7b2c\u4e00\u7248\u7684 body \u91cc\u6709\u4e2a\u70ed\u8eab\u5faa\u73af（\u8d70 3\/4 \u5708）\u52a0\u8ba1\u65f6\u5faa\u73af（\u8d70 3 \u5708），\u4e00\u5171 3.75 \u5708；\u800c items_of \u6309\u5143\u7d20\u4e2a\u6570\u7b97，\u7b49\u4e8e\u58f0\u79f0\u53ea\u8d70\u4e86 1 \u5708\u3002\u7ed3\u679c\u6574\u6761\u66f2\u7ebf\u6574\u4f53\u504f\u4e86 3.75 \u500d\u2014\u201416KB \u62a5 3.67 ns \u800c\u4e0d\u662f 0.98 ns\u3002<\/p>\n

    \u6bcf\u4e00\u6863\u90fd\u504f\u9ad8\u540c\u4e00\u4e2a\u500d\u6570，\u66f2\u7ebf\u7684\u5f62\u72b6\u4e00\u70b9\u6ca1\u53d8\u3002 \u53f0\u9636\u8fd8\u5728\u539f\u6765\u7684\u4f4d\u7f6e，\u500d\u6570\u5173\u7cfb\u4e5f\u5bf9（2.05x\u30012.76x\u30015.27x \u5168\u5bf9）\u3002\u5355\u770b\u90a3\u4efd\u8f93\u51fa，\u5b83\u50cf\u4e00\u4efd\u5b8c\u5168\u6b63\u5e38\u7684\u9636\u68af\u6570\u636e\u3002\u53ea\u6709\u62ff\u53bb\u548c exp06 \u5bf9\u7167，\u624d\u770b\u5f97\u51fa\u7edd\u5bf9\u503c\u5168\u9519\u3002<\/p>\n

    \u8fd9\u5c31\u662f items_of \u8fd9\u4e2a\u53c2\u6570\u5b58\u5728\u7684\u7406\u7531，\u4e5f\u662f\u5b83\u7684\u7528\u6cd5：\u5b83\u5fc5\u987b\u7b49\u4e8e body \u91cc\u90a3\u4ef6\u4e8b\u5b9e\u9645\u53d1\u751f\u4e86\u51e0\u6b21\u3002 \u4e00\u6b21\u6307\u9488\u8ffd\u9010\u7b97\u4e00\u6b21\u3002sweep \u7528\u5b83\u6765\u644a\u8584\u603b\u65f6\u95f4，\u5199\u9519\u4e0d\u4f1a\u62a5\u9519，\u53ea\u4f1a\u8ba9\u6574\u6761\u66f2\u7ebf\u6574\u4f53\u7f29\u653e\u3002<\/p>\n

    \u4fee\u6cd5\u662f\u628a\u70ed\u8eab\u5faa\u73af\u53bb\u6389\u2014\u2014sweep \u5bf9\u6bcf\u4e00\u6863\u8dd1 5 \u8f6e\u53d6\u6700\u5c0f，\u7b2c\u4e00\u8f6e\u7684\u51b7\u542f\u52a8\u672c\u6765\u5c31\u4f1a\u88ab\u540e\u9762\u51e0\u8f6e\u6324\u6389，exp06 \u624b\u5199\u7248\u91cc\u90a3\u4e2a\u70ed\u8eab\u5faa\u73af\u5728\u53d6\u6700\u5c0f\u7684\u6846\u67b6\u4e0b\u662f\u591a\u4f59\u7684\u3002\u6539\u5b8c\u91cd\u8dd1，16KB\u300164KB\u3001256KB\u30014MB\u300164MB \u4e94\u6863\u90fd\u843d\u8fdb\u4e86 8% \u4ee5\u5185\u3002<\/p>\n

    1MB \u548c 16MB \u5bf9\u4e0d\u4e0a，\u800c\u8fd9\u6b21\u4e0d\u8be5\u6539\u4ee3\u7801<\/h4>\n

    \u5269\u4e0b\u4e24\u6863\u5dee\u5f97\u8fdc\u3002\u591a\u8dd1\u51e0\u8f6e，\u770b\u8fd9\u4e24\u4e2a\u6570\u5404\u81ea\u7684\u5206\u5e03：<\/p>\n\n\u5de5\u4f5c\u96c6demo \u8de8\u591a\u6b21\u8fd0\u884cexp06 \u624b\u5199\u7248\u90a3\u4e00\u5217<\/tr>\n\n\n\n\n\n\n\n\n
    16 KB<\/td>\n0.98 ~ 1.08 ns<\/td>\n1.04 ns<\/td>\n<\/tr>\n
    64 KB<\/td>\n2.01 ~ 2.21 ns<\/td>\n2.14 ns<\/td>\n<\/tr>\n
    256 KB<\/td>\n2.72 ~ 3.00 ns<\/td>\n2.94 ns<\/td>\n<\/tr>\n
    1 MB<\/td>\n4.12 ~ 5.91 ns<\/td>\n5.36 ns<\/td>\n<\/tr>\n
    4 MB<\/td>\n9.84 ~ 10.80 ns<\/td>\n10.22 ns<\/td>\n<\/tr>\n
    16 MB<\/td>\n27.03 ~ 177.43 ns<\/td>\n34.09 ns<\/td>\n<\/tr>\n
    64 MB<\/td>\n82.47 ~ 85.22 ns<\/td>\n90.01 ns<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    1MB \u5728\u4e0a\u9762\u8fd9\u8f6e\u8bfb 4.13，\u53e6\u4e00\u8f6e\u8bfb 5.91\u2014\u2014\u5b83\u81ea\u5df1\u662f\u6563\u7684，\u4e0d\u662f demo \u548c exp06 \u8c01\u5bf9\u8c01\u9519\u3002<\/p>\n

    16MB \u66f4\u6781\u7aef：57 \u500d\u7684\u8303\u56f4\u3002\u5b83\u538b\u5728 L3 \u5bb9\u91cf（16MB）\u4e0a，\u5176\u4ed6\u6838\u591a\u5360\u4e00\u70b9 L3，\u8fd9\u4e00\u6863\u5c31\u6362\u4e00\u4e2a\u6570\u3002<\/p>\n

    \u5173\u952e\u7684\u4e00\u6b65\u662f：\u672c\u6b21 exp06 \u91cd\u8dd1\u7ed9\u7684\u662f 27.68 ns，\u548c demo \u7684 27.03~28.27 \u4e00\u81f4\u3002 \u4e24\u8fb9\u5728 16MB \u4e0a\u5176\u5b9e\u662f\u5bf9\u5f97\u4e0a\u7684，\u5bf9\u4e0d\u4e0a\u7684\u662f\u6211\u90a3\u5f20\u6807\u79f0\u8868\u91cc\u7684 34.09\u2014\u2014\u5b83\u662f\u5f53\u521d\u91c7\u96c6\u65f6\u649e\u4e0a\u5e72\u6270\u7684\u4e00\u4e2a\u504f\u9ad8\u503c\u3002\u6ca1\u6709\u7b2c\u4e8c\u4e2a\u6765\u6e90\u5bf9\u7167，\u8fd9\u4e2a\u9519\u4f1a\u4e00\u76f4\u7559\u5728\u8868\u91cc\u3002<\/p>\n

    \u5224\u65ad\u8fd9\u7c7b\u504f\u5dee\u6709\u4e2a\u6bd4\u6570\u503c\u66f4\u5feb\u7684\u529e\u6cd5：\u770b\u5f62\u72b6\u3002 \u66f2\u7ebf\u5728 16MB \u5904\u9f13\u8d77\u6765\u3001\u5bfc\u81f4 16MB \u6bd4 64MB \u8fd8\u6162，\u8fd9\u662f\u73af\u5883\u5728\u8bf4\u8bdd\u2014\u2014\u8bbf\u5b58\u5ef6\u8fdf\u4e0d\u4f1a\u8fd9\u4e48\u8d70\u3002\u770b\u5230\u975e\u5355\u8c03，\u5148\u6000\u7591\u73af\u5883，\u522b\u6539\u4ee3\u7801\u3002<\/p>\n

    A \u7ebf\u5de5\u5177\u7684\u8f93\u51fa\u91cc，\u89c4\u6a21\u548c\u504f\u5dee\u90fd\u8981\u8ddf\u7740\u8d70\u3002 \u53ea\u62a5\u4e00\u4e2a\u7edd\u5bf9\u503c，\u8bfb\u8005\u6ca1\u6cd5\u5224\u65ad\u5b83\u662f\u4e0d\u662f\u53ef\u4fe1\u7684\u3002demo \u628a\u504f\u5dee\u7b97\u51fa\u6765\u6253\u5728\u5c4f\u5e55\u4e0a，\u800c\u4e0d\u662f\u5728\u6536\u5c3e\u6587\u5b57\u91cc\u65ad\u8a00\u300c\u5bf9\u5f97\u4e0a\u300d\u2014\u2014\u673a\u5668\u5fd9\u7684\u65f6\u5019\u5b83\u5c31\u8be5\u96be\u770b\u3002<\/p>\n

    \u4ea4\u4ed8\u8981\u6c42<\/h4>\n
  • probe.hpp \u91cc\u52a0\u4e0a SweepPoint\u3001sweep\u3001print_sweep，\u7f16\u8bd1\u901a\u8fc7\u3002<\/li>\n
  • probe_sweep_demo.cpp \u8dd1\u51fa\u548c exp06 \u4e00\u81f4\u7684\u9636\u68af（\u5dee\u5728\u51e0\u4e2a\u767e\u5206\u70b9\u5185）\u3002<\/li>\n
  • \u5199\u4e0b\u4f60\u7684 KNEE_RATIO \u53d6\u503c\u548c\u7406\u7531\u3002\u5982\u679c\u4e0d\u7528 1.8 \u800c\u7528\u522b\u7684\u503c，\u8bf4\u660e\u5b83\u5bf9\u53f0\u9636\u5224\u5b9a\u6709\u4ec0\u4e48\u5f71\u54cd\u3002<\/li>\n

    B \u7ebf\u4efb\u52a1 \u00b7 MiniQuote v0.2：\u7b2c\u4e00\u6b21 profiling<\/h3>\n

    \u5148\u8bf4\u5de5\u5177<\/h4>\n

    \u5355\u5143\u4e00\u8981\u6c42\u4f60\u7528\u5206\u4f4d\u6570\u800c\u4e0d\u662f\u5e73\u5747\u503c\u6c47\u62a5\u6027\u80fd\u3002\u8fd9\u4e00\u8bb2\u8981\u7684\u662f\u53e6\u4e00\u4ef6\u4e8b：\u4f60\u7684\u76f4\u89c9\u6307\u51fa\u7684\u70ed\u70b9，\u548c\u5de5\u5177\u6307\u51fa\u7684\u70ed\u70b9，\u662f\u4e0d\u662f\u540c\u4e00\u6279\u3002<\/p>\n

    \u8fd9\u4e00\u8bb2\u624b\u4e0a\u6709\u56db\u4e2a\u5de5\u5177，\u80fd\u529b\u4e92\u8865：<\/p>\n\n\u5de5\u5177\u7ed9\u4f60\u4ec0\u4e48\u62ff\u4e0d\u5230\u4ec0\u4e48<\/tr>\n\n\n\n\n\n
    \u81ea\u5df1\u5199\u7684\u5206\u9636\u6bb5\u8ba1\u65f6<\/td>\n\u6bcf\u4e2a\u9636\u6bb5\u7684\u5899\u949f\u65f6\u95f4<\/td>\n\u9636\u6bb5\u5185\u90e8\u5230\u5e95\u82b1\u5728\u54ea<\/td>\n<\/tr>\n
    perf stat<\/td>\n\u786c\u4ef6\u8ba1\u6570\u5668：\u771f\u5b9e\u673a\u5668\u4e0a\u7684 L1\/L2 miss<\/td>\n\u5f52\u5c5e\u5230\u51fd\u6570\u6216\u6e90\u7801\u884c<\/td>\n<\/tr>\n
    valgrind –tool=cachegrind<\/td>\n\u6309\u51fd\u6570\u3001\u6309\u6e90\u7801\u884c\u7684 miss \u5f52\u5c5e，\u6bcf\u6b21\u4e00\u6837<\/td>\n\u662f\u6a21\u62df，\u4e0d\u662f\u771f\u5b9e\u786c\u4ef6<\/td>\n<\/tr>\n
    gprof<\/td>\n\u8c03\u7528\u6b21\u6570\u4e0e\u8c03\u7528\u5173\u7cfb，\u4e0d\u9700\u8981\u4efb\u4f55\u6743\u9650<\/td>\n\u65f6\u95f4\u5f52\u56e0\u53d7\u5185\u8054\u4e0e -O0 \u5f71\u54cd<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u51c6\u5907：<\/p>\n

    sudo<\/span> sysctl<\/span> kernel.perf_event_paranoid<\/span>=<\/span>-1 # perf \u9700\u8981，valgrind \u4e0d\u9700\u8981<\/span>
    \nsudo<\/span> apt<\/span> install<\/span> valgrind # gprof \u968f binutils，\u672c\u6765\u5c31\u6709<\/span><\/p>\n

    \u7f16\u8bd1\u65f6\u8bb0\u5f97\u5e26 -g\u3002 \u4e0d\u5e26\u7684\u8bdd cachegrind \u7167\u6837\u8dd1，\u4f46 cg_annotate \u7684\u51fd\u6570\u8868\u662f\u7a7a\u7684\u2014\u2014
    \n\u5b83\u624b\u4e0a\u6709\u8ba1\u6570\u5668，\u6ca1\u6709\u7b26\u53f7，\u4e0d\u77e5\u9053\u90a3\u4e9b\u6570\u8be5\u6302\u5230\u8c01\u5934\u4e0a\u3002<\/p>\n

    \u57fa\u7ebf：v0.1 \u7684\u5206\u9636\u6bb5\u8bfb\u6570<\/h4>\n

    mini_quote_v01.cpp \u662f B \u7ebf\u7684\u8d77\u70b9\u3002\u5b83\u6309\u5355\u5143\u4e00\u7684\u8981\u6c42\u5199\u6210\u6700\u76f4\u767d\u7684\u6837\u5b50，\u6545\u610f\u7559\u4e86\u4e24\u5904\u6d6a\u8d39：<\/p>\n

    \/\/ v0.1 \u7684\u6d6a\u8d39\u70b9\u4e4b\u4e00：\u6bcf\u6761\u8bb0\u5f55\u7684\u6bcf\u4e2a\u5b57\u6bb5\u5404\u5360\u4e00\u4e2a std::string\u3002<\/span>
    \n\/\/ 5 \u4e2a string \u5c31\u662f 160 \u5b57\u8282，\u800c\u539f\u59cb\u8bb0\u5f55\u53ea\u6709 24 \u5b57\u8282\u3002<\/span>
    \nstruct<\/span> StrTick<\/span> {<\/span>
    \n std::<\/span>string ts;<\/span>
    \n std::<\/span>string order_id;<\/span>
    \n std::<\/span>string price;<\/span>
    \n std::<\/span>string qty;<\/span>
    \n std::<\/span>string side;<\/span>
    \n}<\/span>;<\/span><\/p>\n

    \u8dd1 100 \u4e07\u6761：<\/p>\n

    $ .\/gen_quote 1000000 && .\/mini_quote_v01<\/p>\n

    \u8f93\u5165 ticks.bin，1000000 \u6761，22.9 MB
    \nStrTick \u5185\u5b58 152.6 MB（\u6bcf\u6761 160 \u5b57\u8282，\u539f\u59cb\u8bb0\u5f55\u53ea\u6709 24 \u5b57\u8282）<\/p>\n

    \u5206\u9636\u6bb5\u8017\u65f6
    \n \u8bfb\u6587\u4ef6 13.5 ms 6.7%
    \n \u5efa StrTick \u6570\u7ec4 65.5 ms 32.5%
    \n \u9010\u6761\u8f6c\u5b57\u7b26\u4e32 74.7 ms 37.1%
    \n \u5efa map \u5e76\u6c47\u603b 46.7 ms 23.2%
    \n \u7b97\u6c47\u603b\u6570\u5b57 0.9 ms 0.4%
    \n \u5408\u8ba1 201.3 ms<\/p>\n

    \u8dd1\u4e4b\u524d\u5148\u5199\u4e0b\u4f60\u731c\u7684\u70ed\u70b9\u3002 \u4e0d\u662f\u8d70\u8fc7\u573a\u2014\u2014Guntheroth \u8bf4\u4ed6\u51ed\u76f4\u89c9\u627e\u5230\u7684\u70ed\u70b9\u5217\u8868\u548c profiler \u7ed9\u51fa\u7684\u57fa\u672c\u662f\u540c\u4e00\u6279，\u4f46\u4ed6\u4f9d\u7136\u8ba4\u4e3a\u76f4\u89c9\u8def\u7ebf\u4e0d\u53ef\u53d6，\u7406\u7531\u662f\u4ed6\u81ea\u5df1\u7ed9\u7684：\u76f4\u89c9\u51c6\u4e0d\u51c6\u662f\u4e00\u56de\u4e8b，\u522b\u4eba\u6ca1\u6cd5\u9a8c\u8bc1\u4f60\u7684\u76f4\u89c9\u662f\u53e6\u4e00\u56de\u4e8b，\u540e\u8005\u5728\u5de5\u7a0b\u91cc\u66f4\u81f4\u547d\u3002<\/p>\n

    \u5bf9\u7167\u4e0b\u9762\u8fd9\u5f20\u8868，\u770b\u4e24\u4ef6\u4e8b：\u4f60\u7684\u731c\u6d4b\u548c\u5b9e\u6d4b\u5dee\u5728\u54ea，\u4ee5\u53ca\u8fd9\u4e2a\u5dee\u8ddd\u80fd\u4e0d\u80fd\u9760\u300c\u7ecf\u9a8c\u300d\u6d88\u9664\u3002<\/p>\n

    \u4e00\u4e2a\u5bb9\u6613\u5ffd\u7565\u7684\u8bfb\u6cd5：StrTick \u6570\u7ec4\u5360 152.6 MB，\u662f\u539f\u59cb\u6570\u636e 22.9 MB \u7684 6.7 \u500d\u3002 \u5355\u5143\u4e00\u7684 baseline \u91cc 24MB \u5c31\u5df2\u7ecf\u8d85\u51fa\u672c\u673a L3 \u4e86，\u5230 152MB \u65f6\u6bcf\u4e00\u6b21\u8bbf\u95ee\u90fd\u5fc5\u7136\u843d\u5230\u4e3b\u5b58\u3002\u8fd9\u4e00\u7248\u6162\u7684\u6839\u6e90\u4e0d\u662f\u300c\u5b57\u7b26\u4e32\u8f6c\u6362\u6162\u300d，\u662f\u5b83\u628a\u5de5\u4f5c\u96c6\u6491\u5927\u4e86 6.7 \u500d\u3002\u8fd9\u6b63\u662f\u672c\u5355\u5143\u524d\u56db\u8bb2\u8981\u6559\u7684\u5f52\u56e0\u65b9\u5f0f：\u5148\u95ee\u642c\u8fd0\u91cf，\u518d\u95ee\u6307\u4ee4\u6570\u3002<\/p>\n

    \u9010\u6761\u8ba1\u65f6\u5728\u8fd9\u4e00\u5c42\u6ca1\u6709\u7528<\/h4>\n

    v0.1 \u91cc\u6309\u5355\u5143\u4e00\u7684\u8981\u6c42\u8bb0\u4e86\u5355\u6761\u5904\u7406\u5ef6\u8fdf：<\/p>\n

    \u5355\u6761\u5904\u7406\u5ef6\u8fdf（\u7b2c 2 \u9636\u6bb5\u5185\u90e8，\u9010\u6761\u8ba1\u65f6）
    \n p50 50.0 ns p90 51.0 ns p99 70.0 ns max 13786.0 ns n=1000000<\/p>\n

    \u5148\u522b\u770b\u8fd9\u51e0\u4e2a\u6570\u3002 \u5355\u5143\u4e00\u91cf\u8fc7\u4e00\u6b21 steady_clock::now() \u8981 16~18 ns，\u800c\u8fd9\u91cc\u6bcf\u6761\u8bb0\u5f55\u53ea\u505a 5 \u6b21 to_string，\u771f\u5b9e\u8017\u65f6\u5728 15 ns \u4e0a\u4e0b\u3002\u4e5f\u5c31\u662f\u8bf4\u8fd9\u51e0\u4e2a\u5206\u4f4d\u6570\u91cc，\u6709\u4e00\u5927\u534a\u662f\u5c3a\u5b50\u81ea\u5df1\u7684\u91cd\u91cf\u3002<\/p>\n

    \u8981\u91cf\u8fd9\u4e00\u5c42，\u5f97\u7528\u5206\u5757\u8ba1\u65f6\u2014\u2014\u628a 4096 \u6761\u5305\u6210\u4e00\u6279，\u8bfb\u4e00\u6b21\u65f6\u949f，\u518d\u9664\u4ee5\u6279\u5927\u5c0f\u3002\u8fd9\u662f\u5355\u5143\u4e00 exp04 \u7684\u7ed3\u8bba\u5728\u8fd9\u91cc\u7684\u7b2c\u4e8c\u6b21\u5e94\u7528\u3002<\/p>\n

    \u5206\u9636\u6bb5\u8ba1\u65f6\u5230\u8fd9\u91cc\u5c31\u7ed9\u5230\u5934\u4e86：\u5b83\u80fd\u544a\u8bc9\u4f60\u300c\u5efa StrTick \u6570\u7ec4\u5360 32.5%\u300d，\u7b54\u4e0d\u51fa\u8fd9 32.5% \u662f\u82b1\u5728\u5206\u914d\u3001\u62f7\u8d1d\u8fd8\u662f\u6784\u9020\u4e0a\u3002\u524d\u9762\u51e0\u8bb2\u53cd\u590d\u7528\u7684\u90a3\u4e24\u4e2a\u95ee\u9898，\u5728\u8fd9\u91cc\u8981\u4ea4\u7ed9\u8ba1\u6570\u5668：<\/p>\n

  • \u642c\u8fd0\u91cf\u591a\u5927\u3002 \u8fd9\u4e9b\u9636\u6bb5\u5404\u81ea\u78b0\u4e86\u591a\u5c11\u6761 cache line\u3002<\/li>\n
  • \u843d\u5728\u54ea\u4e00\u7ea7\u3002 \u78b0\u7684\u884c\u662f\u547d\u4e2d\u5728 L2，\u8fd8\u662f\u6bcf\u6b21\u90fd\u6389\u5230\u4e3b\u5b58\u3002<\/li>\n

    perf stat \u770b\u5230\u7684：\u6574\u4e2a\u8fdb\u7a0b<\/h4>\n

    $ taskset -c<\/span> 15<\/span> perf stat<\/span> -e<\/span> L1-dcache-load-misses,cache-misses,cache-references \\\\<\/span>
    \n .\/mini_quote_v01<\/p>\n

    23,191<\/span>,183 L1-dcache-load-misses
    \n 1,797<\/span>,244 cache-misses
    \n 43,826<\/span>,849 cache-references
    \n 0.246360417<\/span> seconds time<\/span> elapsed<\/p>\n

    \u5904\u7406\u4e00\u6b21 24MB \u8f93\u5165，L1 \u8bfb miss \u4e24\u5343\u4e09\u767e\u4e07\u6b21，L2 \u9700\u6c42 miss \u4e00\u767e\u516b\u5341\u4e07\u6b21\u3002<\/p>\n

    \u8fd9\u4e24\u4e2a\u6570\u56de\u7b54\u4e0d\u4e86\u8fd9\u4e00\u8bb2\u7684\u95ee\u9898\u2014\u2014\u5b83\u4eec\u5c5e\u4e8e\u6574\u4e2a\u8fdb\u7a0b，\u4e0d\u5c5e\u4e8e\u67d0\u4e2a\u9636\u6bb5\u3002
    \n\u8981\u5f52\u5230\u51fd\u6570\u4e0a，\u5f97\u6362\u5de5\u5177\u3002<\/p>\n

    \u8fd9\u4e24\u4e2a\u6570\u672c\u8eab\u7684\u7a33\u5b9a\u6027\u4e5f\u503c\u5f97\u8bb0\u4e00\u7b14\u3002\u540c\u4e00\u4efd\u8f93\u5165\u8fde\u8dd1\u4e94\u6b21：<\/p>\n\n\u4e8b\u4ef6\u4e94\u6b21\u7684\u8303\u56f4\u76f8\u5bf9\u6ce2\u52a8<\/tr>\n\n\n\n\n
    L1 \u8bfb miss<\/td>\n23,028,641 ~ 23,796,633<\/td>\n3.3%<\/td>\n<\/tr>\n
    L2 \u9700\u6c42 miss<\/td>\n938,879 ~ 1,895,992<\/td>\n2.0 \u500d<\/td>\n<\/tr>\n
    cache-references<\/td>\n41.8M ~ 44.4M<\/td>\n6.0%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    L1 \u90a3\u4e2a\u6570\u7a33，L2 \u90a3\u4e2a\u6643\u4e24\u500d\u3002\u7406\u7531\u5728\u7b2c\u4e09\u8bb2\u91cf\u8fc7：L2 \u7684\u5bb9\u91cf\u4f59\u91cf\u5c0f，
    \n\u8fb9\u754c\u4e0a\u90a3\u90e8\u5206\u6570\u636e\u7559\u4e0d\u7559\u5f97\u4f4f，\u53d6\u51b3\u4e8e\u8fd9\u4e00\u8f6e\u8dd1\u7684\u65f6\u5019 L3 \u91cc\u8fd8\u538b\u7740\u8c01\u3002
    \n\u4f59\u91cf\u5927\u7684\u90a3\u4e00\u7ea7\u53ef\u4ee5\u53ea\u62a5\u4e00\u4e2a\u6570，\u8d34\u7740\u5bb9\u91cf\u4e0a\u9650\u7684\u90a3\u4e00\u7ea7\u8981\u5e26\u8303\u56f4\u3002
    \n\u8fd9\u6761\u5224\u65ad\u4e0d\u662f\u8fd9\u4e00\u5904\u7279\u6709\u7684，\u540e\u9762\u6bcf\u4e00\u7ea7\u90fd\u8fd9\u4e48\u770b\u3002<\/p>\n

    cachegrind \u770b\u5230\u7684：\u5f52\u5230\u51fd\u6570<\/h4>\n

    $ g++ -std<\/span>=<\/span>c++23 -O2<\/span> -g<\/span> -o<\/span> mini_quote_v01_g mini_quote_v01.cpp
    \n$ valgrind –tool<\/span>=<\/span>cachegrind –cache-sim=<\/span>yes \\\\<\/span>
    \n –I1<\/span>=<\/span>32768,8<\/span>,64 –D1<\/span>=<\/span>32768,8<\/span>,64 –LL<\/span>=<\/span>1048576,8<\/span>,64 \\\\<\/span>
    \n –cachegrind-out-file=<\/span>cg.out .\/mini_quote_v01_g
    \n$ cg_annotate –show<\/span>=<\/span>Dr,D1mr,DLmr –threshold<\/span>=<\/span>0.5<\/span> cg.out<\/p>\n

    –LL \u4f20\u7684\u662f L2 \u7684\u51e0\u4f55（1MB \/ 8 \u8def）\u3002cachegrind \u53ea\u6a21\u62df\u4e24\u7ea7，\u8981\u8ba9\u5b83\u7684
    \n\u300cLL\u300d\u5bf9\u5e94\u672c\u673a\u7684\u54ea\u4e00\u7ea7，\u5c31\u5f97\u628a\u8fd9\u4e2a\u6570\u4f20\u5bf9\u3002\u4f20\u6210\u672c\u673a L3 \u7684 16MB \u662f\u53e6\u4e00\u4e2a\u95ee\u9898\u2014\u2014
    \n\u90a3\u65f6\u5019 LL miss \u6307\u7684\u662f\u300c\u8fde L3 \u90fd\u6ca1\u547d\u4e2d\u300d\u3002\u4e24\u8005\u90fd\u4f1a\u751f\u6548，\u8f93\u51fa\u5934\u90e8\u4f1a\u5199\u660e\u7528\u7684\u662f\u54ea\u4e00\u5957\u3002<\/p>\n

    –threshold=0.5 \u662f\u5fc5\u987b\u7684\u3002\u9ed8\u8ba4\u9608\u503c\u4f1a\u628a\u6240\u6709\u4f4e\u4e8e 1% \u7684\u884c\u85cf\u8d77\u6765，
    \n\u800c\u8fd9\u91cc\u6b63\u8981\u770b\u7684\u5c31\u662f\u90a3\u51e0\u884c\u5c0f\u6761\u76ee\u2014\u2014\u5b83\u4eec\u5355\u72ec\u90fd\u4e0d\u5927，\u52a0\u8d77\u6765\u624d\u662f\u5927\u5934\u3002<\/p>\n

    \u5173\u952e\u5217\u662f DLmr（last-level miss，\u8bfb）：<\/p>\n

    Dr D1mr DLmr file:function
    \n 39,000,000 3,500,002 3,500,002 bits\/basic_string.h
    \n \u2514 main 1,000,002 \/ ~vector<StrTick> 2,500,000
    \n 39,006,194 1,000,005 1,000,005 strtol_l.c:____strtoul_l_internal
    \n 40,741,642 337,809 52,358 bits\/stl_tree.h<\/p>\n

    \u8fd9\u4e00\u6b21\u8fd0\u884c\u91cc，D1 \u8bfb miss \u5171 709 \u4e07，LLd \u8bfb miss \u5171 612 \u4e07\u3002\u6309\u4efd\u989d\u6392：<\/p>\n\n\u5f52\u5c5e\u5360 D1 \u8bfb miss\u5360 LLd \u8bfb miss<\/tr>\n\n\n\n\n\n
    basic_string（\u5b57\u7b26\u4e32\u6784\u9020\u3001\u8d4b\u503c\u3001\u6790\u6784）<\/td>\n49.3%<\/td>\n57.2%<\/td>\n<\/tr>\n
    ____strtoul_l_internal<\/td>\n14.1%<\/td>\n16.3%<\/td>\n<\/tr>\n
    stl_tree（std::map）<\/td>\n4.8%<\/td>\n0.9%<\/td>\n<\/tr>\n
    \u5408\u8ba1<\/td>\n68.2%<\/td>\n74.4%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u8bfb miss \u91cc\u8fd1\u56db\u5206\u4e4b\u4e09\u843d\u5728\u4e09\u5904，\u5176\u4e2d\u4e00\u5904\u662f\u5b57\u7b26\u4e32\u64cd\u4f5c，\u4e00\u5904\u662f\u628a\u5b57\u7b26\u4e32\u89e3\u6790\u56de\u6570\u5b57\u3002<\/p>\n

    strtoul \u90a3 100 \u4e07\u6b21\u662f v0.1 \u91cc\u300c\u628a\u5b57\u7b26\u4e32\u89e3\u6790\u56de\u6570\u5b57\u300d\u90a3\u4e00\u6b65\u7684\u8d26\u5355，
    \n\u5206\u9636\u6bb5\u8ba1\u65f6\u628a\u5b83\u8bb0\u5728\u300c\u5efa map \u5e76\u6c47\u603b\u300d\u540d\u4e0b，\u770b\u4e0d\u51fa\u5b83\u5177\u4f53\u8d35\u5728\u89e3\u6790\u4e0a\u3002
    \n~vector<StrTick> \u90a3 250 \u4e07\u6b21\u66f4\u9690\u853d\u2014\u2014\u9500\u6bc1\u4e00\u767e\u4e07\u4e2a StrTick \u8981\u8bfb\u6bcf\u4e2a string
    \n\u7684\u63a7\u5236\u5757，\u8fd9\u7b14\u5f00\u9500\u5728\u5206\u9636\u6bb5\u8ba1\u65f6\u91cc\u6839\u672c\u6ca1\u6709\u5355\u72ec\u4e00\u884c\u3002<\/p>\n

    \u8fd9\u4e24\u6761\u6b63\u597d\u56de\u7b54\u4e86\u300c\u5148\u8bf4\u5de5\u5177\u300d\u91cc\u90a3\u4e2a\u95ee\u9898：\u5206\u9636\u6bb5\u8ba1\u65f6\u7ed9\u51fa\u7684\u70ed\u70b9\u548c\u8ba1\u6570\u5668\u7ed9\u51fa\u7684\u70ed\u70b9，
    \n\u5728\u51fd\u6570\u8fd9\u4e00\u5c42\u5bf9\u4e0d\u4e0a\u3002 \u5bf9\u4e0d\u4e0a\u7684\u5730\u65b9，\u5c31\u662f v0.2 \u8981\u52a8\u7684\u5730\u65b9\u3002<\/p>\n

    cachegrind \u4e5f\u8981\u5148\u8bf4\u6e05\u5b83\u81ea\u5df1\u6643\u4e0d\u6643\u3002\u540c\u4e00\u4efd\u4e8c\u8fdb\u5236\u8fde\u8dd1\u56db\u6b21：<\/p>\n\n\u4e8b\u4ef6\u56db\u6b21\u7684\u8303\u56f4\u76f8\u5bf9\u6ce2\u52a8<\/tr>\n\n\n\n\n\n
    D1 \u8bfb miss<\/td>\n6,943,732 ~ 7,093,054<\/td>\n2.2%<\/td>\n<\/tr>\n
    D1 \u5199 miss<\/td>\n5,515,303 ~ 5,515,417<\/td>\n0.002%<\/td>\n<\/tr>\n
    LLd \u8bfb miss<\/td>\n5,954,911 ~ 6,122,230<\/td>\n2.8%<\/td>\n<\/tr>\n
    LLd \u5199 miss<\/td>\n5,512,462 ~ 5,512,481<\/td>\n0.0003%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u5199\u4fa7\u7684 miss \u9010\u4f4d\u53ef\u590d\u73b0，\u8bfb\u4fa7\u4f1a\u6643\u4e24\u4e2a\u767e\u5206\u70b9\u3002\u539f\u56e0\u662f\u5b83\u6a21\u62df\u7684\u7f13\u5b58\u6309\u5730\u5740\u7d22\u5f15，
    \n\u800c\u5806\u4e0a\u90a3\u4e9b\u8282\u70b9\u7684\u5730\u5740\u6bcf\u6b21\u8fd0\u884c\u90fd\u5728\u53d8（ASLR \u52a0\u5206\u914d\u5668\u884c\u4e3a），
    \n\u8c01\u548c\u8c01\u649e\u5728\u540c\u4e00\u4e2a\u7ec4\u91cc\u968f\u4e4b\u6539\u53d8\u3002\u5199\u4fa7\u591a\u662f\u5927\u5757\u987a\u5e8f\u5199，\u53d7\u5730\u5740\u6446\u653e\u5f71\u54cd\u5c0f\u3002<\/p>\n

    \u8fd9\u6761\u503c\u5f97\u5355\u72ec\u8bb0：\u300c\u6a21\u62df\u5668\u53ef\u590d\u73b0\u300d\u662f\u4e2a\u5e38\u89c1\u7684\u9ed8\u8ba4\u5047\u8bbe，\u800c\u5b83\u5e76\u4e0d\u603b\u6210\u7acb\u3002
    \n\u4e00\u4e2a\u5de5\u5177\u8dd1\u51fa\u4e24\u4e2a\u6570\u65f6，\u5148\u786e\u8ba4\u662f\u5de5\u5177\u5728\u6643，\u8fd8\u662f\u88ab\u6d4b\u5bf9\u8c61\u5728\u6643\u3002\u8fd9\u91cc\u4e24\u8005\u90fd\u5728\u6643，
    \n\u800c\u4e14\u6643\u7684\u5e45\u5ea6\u6bd4\u540e\u9762\u8981\u7528\u7684\u90a3\u4e2a 8 \u500d\u5dee\u8ddd\u5c0f\u4e00\u4e2a\u6570\u91cf\u7ea7，\u7ed3\u8bba\u4e0d\u53d7\u5f71\u54cd\u3002<\/p>\n

    \u4e24\u4efd\u8ba1\u6570\u5bf9\u4e0d\u4e0a，\u800c\u8fd9\u4e00\u6b21\u4e5f\u4e0d\u8be5\u6539\u4ee3\u7801<\/h4>\n

    \u62ff\u4e24\u4e2a\u5de5\u5177\u5404\u81ea\u591a\u6b21\u8fd0\u884c\u7684\u8303\u56f4\u53bb\u6bd4：<\/p>\n\n\u8303\u56f4\u6ce2\u52a8<\/tr>\n\n\n\n
    cachegrind \u7684 LLd miss<\/td>\n1,147 \u4e07 ~ 1,163 \u4e07<\/td>\n1.5%<\/td>\n<\/tr>\n
    perf \u7684 L2 \u9700\u6c42 miss<\/td>\n94 \u4e07 ~ 190 \u4e07<\/td>\n2.0 \u500d<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4e24\u8005\u76f8\u5dee 6 \u5230 12 \u500d，\u8fdc\u8fdc\u8d85\u51fa\u5b83\u4eec\u5404\u81ea\u7684\u6643\u52a8\u5e45\u5ea6\u3002 \u8fd9\u4e2a\u5dee\u8ddd\u662f\u771f\u7684\u3002<\/p>\n

    \u4e24\u4e2a\u6570\u90fd\u6ca1\u9519，\u91cf\u7684\u4e0d\u662f\u540c\u4e00\u4ef6\u4e8b：<\/p>\n

  • cachegrind \u4e0d\u6a21\u62df\u9884\u53d6\u5668\u3002 \u771f\u5b9e\u786c\u4ef6\u4f1a\u628a\u987a\u5e8f\u8bbf\u95ee\u7684\u6570\u636e\u63d0\u524d\u62c9\u8fdb L2，
    \n\u8fd9\u90e8\u5206\u547d\u4e2d\u5728 cachegrind \u91cc\u5168\u90fd\u7b97\u6210 miss\u3002MiniQuote \u8bfb vector<Tick> \u662f\u987a\u5e8f\u7684，
    \n\u90a3\u4e00\u6bb5\u5728\u771f\u673a\u4e0a\u5f88\u5c11 miss \u4e8e L2，\u5728 cachegrind \u91cc\u5168\u90e8\u7b97 miss\u3002<\/li>\n
  • perf \u7684 cache-misses \u53ea\u6570\u9700\u6c42 miss，\u4e0d\u542b\u9884\u53d6\u6d41\u91cf；\u800c cachegrind \u6ca1\u6709\u9884\u53d6，
    \n\u4e24\u8005\u5728\u8fd9\u4e00\u70b9\u4e0a\u5fc5\u7136\u5206\u5c94\u3002<\/li>\n

    \u6240\u4ee5\u8fd9\u91cc\u6ca1\u6709\u300c\u8c01\u66f4\u51c6\u300d，\u53ea\u6709\u5206\u5de5：perf \u544a\u8bc9\u4f60\u771f\u5b9e\u673a\u5668\u4e0a\u6709\u591a\u7cdf，
    \ncachegrind \u544a\u8bc9\u4f60\u90a3\u4e9b miss \u662f\u54ea\u51e0\u884c\u4ee3\u7801\u4ea7\u751f\u7684\u3002 \u7528\u9519\u7684\u5de5\u5177\u95ee\u9519\u7684\u95ee\u9898，
    \n\u62ff\u5230\u7684\u6570\u518d\u7cbe\u786e\u4e5f\u6ca1\u7528\u3002<\/p>\n

    \u7528 gprof \u5bf9\u4e00\u904d<\/h4>\n

    \u5148\u6309\u6b63\u5e38\u65b9\u5f0f\u7f16：<\/p>\n

    $ g++ -std<\/span>=<\/span>c++23 -O2<\/span> -pg<\/span> -Wall<\/span> -Wextra<\/span> -o<\/span> mini_quote_v01_prof mini_quote_v01.cpp
    \n$ .\/mini_quote_v01_prof &&<\/span> gprof .\/mini_quote_v01_prof gmon.out |<\/span> head<\/span> -8<\/span><\/p>\n

    Flat profile:<\/p>\n

    Each sample counts as 0.01<\/span> seconds.
    \n % cumulative self self total
    \n time<\/span> seconds seconds calls ms\/call ms\/call name
    \n 87.50<\/span> 0.14<\/span> 0.14<\/span> main
    \n 12.50<\/span> 0.16<\/span> 0.02<\/span> 7<\/span> 2.86<\/span> 2.86<\/span> (<\/span>anonymous namespace)<\/span>::Dist::p(<\/span>double)<\/span> const<\/p>\n

    \u8fd9\u4efd\u5e73\u8868\u6ca1\u6709\u7528\u3002\u4e24\u5904\u95ee\u9898：<\/p>\n

  • 87.5% \u8bb0\u5728 main \u4e0a\u3002 -O2 \u628a\u4e00\u5207\u90fd\u5185\u8054\u8fdb\u4e86 main，gprof \u770b\u4e0d\u5230\u51fd\u6570\u8fb9\u754c\u3002<\/li>\n
  • Dist::p \u663e\u793a 12.5%，\u800c\u5b83\u53ea\u88ab\u8c03\u7528\u4e86 7 \u6b21\u3002 \u6574\u4e2a\u7a0b\u5e8f\u53ea\u8dd1 200ms，gprof \u6309 100Hz \u91c7\u6837，\u603b\u5171\u624d\u91c7\u5230 16 \u4e2a\u6837\u672c\u30027 \u6b21\u8c03\u7528\u4e0d\u53ef\u80fd\u5403\u6389 12.5% \u7684\u65f6\u95f4，\u8fd9\u662f\u91c7\u6837\u566a\u58f0\u3002<\/li>\n

    \u628a\u6570\u636e\u91cf\u52a0\u5230 500 \u4e07\u6761\u3001\u6863\u4f4d\u964d\u5230 -O0（\u5173\u6389\u5185\u8054），gprof \u624d\u7ed9\u51fa\u50cf\u6837\u7684\u5e73\u8868：<\/p>\n

    $ g++ -std<\/span>=<\/span>c++23 -O0<\/span> -pg<\/span> -Wall<\/span> -Wextra<\/span> -o<\/span> mq_prof_o0 mini_quote_v01.cpp
    \n$ .\/gen_quote 5000000<\/span> &&<\/span> .\/mq_prof_o0 &&<\/span> gprof .\/mq_prof_o0 gmon.out |<\/span> head<\/span> -14<\/span><\/p>\n

    \u73b0\u5728\u5e73\u8868\u6709\u5185\u5bb9\u4e86，\u4f46\u9876\u4e0a\u90a3\u6761\u53ea\u5360 10.94%（std::_Construct<StrTick>，\u5c31\u662f\u5efa\u6570\u7ec4\u65f6\u7684\u6784\u9020）\u3002\u5b83\u7b54\u4e0d\u51fa\u300c\u4e09\u5206\u4e4b\u4e00\u7684\u65f6\u95f4\u5728\u5efa StrTick \u6570\u7ec4\u300d\u2014\u2014\u90a3\u6761\u7ed3\u8bba\u88ab\u644a\u788e\u5728\u4e09\u767e\u591a\u4e2a std:: \u6761\u76ee\u91cc\u3002<\/p>\n

    \u66f4\u9ebb\u70e6\u7684\u662f -O0 \u548c -O2 \u7ed9\u51fa\u7684\u70ed\u70b9\u6392\u5e8f\u4e0d\u4e00\u6837\u3002 \u540c\u4e00\u4efd\u6e90\u7801\u3001\u540c\u4e00\u4e2a 500 \u4e07\u6761\u8f93\u5165：<\/p>\n\n\u9636\u6bb5-O2\u5360\u6bd4-O0 -pg\u5360\u6bd4<\/tr>\n\n\n\n\n\n
    \u5efa StrTick \u6570\u7ec4<\/td>\n315.4 ms<\/td>\n32.1%<\/td>\n1430.1 ms<\/td>\n9.6%<\/td>\n<\/tr>\n
    \u9010\u6761\u8f6c\u5b57\u7b26\u4e32<\/td>\n362.3 ms<\/td>\n36.8%<\/td>\n9681.0 ms<\/td>\n64.9%<\/td>\n<\/tr>\n
    \u5efa map \u5e76\u6c47\u603b<\/td>\n238.5 ms<\/td>\n24.2%<\/td>\n3737.5 ms<\/td>\n25.1%<\/td>\n<\/tr>\n
    \u5408\u8ba1<\/td>\n983.8 ms<\/td>\n<\/td>\n14920.0 ms<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4e24\u4ef6\u4e8b\u540c\u65f6\u53d1\u751f：<\/p>\n

  • -O0 \u6bd4 -O2 \u6162 15.2 \u500d\u3002\u5728 -O0 \u4e0b\u6d4b\u51fa\u6765\u7684\u7edd\u5bf9\u65f6\u95f4\u6ca1\u6709\u4efb\u4f55\u53c2\u8003\u4ef7\u503c\u3002<\/li>\n
  • \u70ed\u70b9\u7684\u6392\u5e8f\u53d8\u4e86\u3002 -O2 \u4e0b\u300c\u8f6c\u5b57\u7b26\u4e32\u300d\u5360 36.8%，-O0 \u4e0b\u5360 64.9%\u3002\u56e0\u4e3a -O0 \u5173\u6389\u4e86\u5185\u8054，\u6240\u6709\u5b57\u7b26\u4e32\u64cd\u4f5c\u90fd\u53d8\u6210\u771f\u5b9e\u51fd\u6570\u8c03\u7528，\u4ee3\u4ef7\u88ab\u653e\u5927\u5f97\u4e0d\u6210\u6bd4\u4f8b\u3002<\/li>\n

    \u8fd8\u6709\u7b2c\u4e09\u4ef6\u4e8b：gprof \u91c7\u6837\u5230\u7684\u603b\u65f6\u957f\u53ea\u6709 4.17 \u79d2，\u800c\u7a0b\u5e8f\u5b9e\u9645\u8dd1\u4e86 14.92 \u79d2\u3002\u4e09\u5206\u4e4b\u4e8c\u7684\u65f6\u95f4\u82b1\u5728 gprof \u770b\u4e0d\u89c1\u7684\u5730\u65b9\u2014\u2014std::to_string\u3001std::string::operator=\u3001std::map \u7684\u5b9e\u73b0\u90fd\u5728 libstdc++ \u52a8\u6001\u5e93\u91cc，\u800c gprof \u7684\u91c7\u6837\u76f4\u65b9\u56fe\u53ea\u8986\u76d6\u4e3b\u7a0b\u5e8f\u81ea\u5df1\u7684\u4ee3\u7801\u6bb5\u3002<\/p>\n

    \u4e09\u6761\u5408\u8d77\u6765\u6307\u5411\u540c\u4e00\u4e2a\u7ed3\u8bba：gprof \u7b54\u4e0d\u4e86\u8fd9\u4e00\u8bb2\u7684\u95ee\u9898，\u800c\u5b83\u7b54\u4e0d\u4e86\u7684\u539f\u56e0\u53ef\u4ee5\u4e8b\u5148\u8bf4\u6e05\u3002
    \n\u5b83\u7684\u8c03\u7528\u6b21\u6570\u662f\u51c6\u7684（\u90a3\u90e8\u5206\u5b83\u6570\u5f97\u6e05\u695a），\u65f6\u95f4\u5f52\u56e0\u8981\u7ed9 -O0 \u6253\u6298，\u800c\u4e14\u8981\u77e5\u9053\u6253\u591a\u5c11\u6298\u3002<\/p>\n

    \u56db\u4e2a\u5de5\u5177\u653e\u5230\u4e00\u8d77，\u5404\u81ea\u8be5\u95ee\u4ec0\u4e48\u95ee\u9898\u662f\u5206\u597d\u7684：<\/p>\n\n\u4f60\u60f3\u95ee\u7684\u95ee\u9898\u8be5\u7528\u54ea\u4e2a<\/tr>\n\n\n\n\n\n
    \u6bcf\u4e2a\u9636\u6bb5\u82b1\u4e86\u591a\u5c11\u6beb\u79d2<\/td>\n\u81ea\u5df1\u7684\u5206\u9636\u6bb5\u8ba1\u65f6<\/td>\n<\/tr>\n
    \u771f\u5b9e\u673a\u5668\u4e0a\u78b0\u4e86\u591a\u5c11\u6761 line\u3001\u843d\u5728\u54ea\u4e00\u7ea7<\/td>\nperf stat<\/td>\n<\/tr>\n
    \u8fd9\u4e9b miss \u662f\u54ea\u51e0\u884c\u4ee3\u7801\u4ea7\u751f\u7684<\/td>\ncachegrind<\/td>\n<\/tr>\n
    \u8c01\u8c03\u7528\u4e86\u8c01\u3001\u5404\u8c03\u4e86\u591a\u5c11\u6b21<\/td>\ngprof<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u56db\u4e2a\u91cc\u53ea\u6709 cachegrind \u4f1a\u76f4\u63a5\u6307\u5230\u6e90\u7801\u884c，\u4ee3\u4ef7\u662f\u6162 50 \u500d\u3001\u4e14\u4e0d\u6a21\u62df\u9884\u53d6\u5668\u3002
    \n\u62a5\u5b83\u7684\u6570\u5b57\u65f6，\u8fd9\u4e24\u4ef6\u4e8b\u8981\u4e00\u8d77\u62a5\u51fa\u53bb\u3002<\/p>\n

    v0.2 \u8981\u4ea4\u4ed8\u7684\u4e1c\u897f<\/h4>\n
  • \u4e00\u4efd baseline.txt，\u6765\u81ea versions\/v0.1\/，\u4e0d\u6539\u52a8\u3002<\/li>\n
  • \u4e00\u5f20\u5bf9\u7167\u8868，\u4e24\u5217：\n
      \n
    • \u4f60\u8dd1\u4e4b\u524d\u731c\u7684\u70ed\u70b9\u6392\u5e8f<\/li>\n
    • \u5206\u9636\u6bb5\u8ba1\u65f6\u7ed9\u51fa\u7684\u5b9e\u9645\u6392\u5e8f
      \n\u5199\u6e05\u695a\u5dee\u5728\u54ea，\u4ee5\u53ca\u4f60\u731c\u9519（\u6216\u731c\u5bf9）\u7684\u5730\u65b9\u662f\u56e0\u4e3a\u4ec0\u4e48\u3002<\/li>\n<\/ul>\n<\/li>\n
    • \u4e00\u4efd\u8ba1\u6570\u5668\u8bb0\u5f55：perf stat \u7684\u6574\u7a0b\u5e8f\u8bfb\u6570，\u52a0\u4e0a cg_annotate \u7684\u51fd\u6570\u8868\u524d 10 \u884c\u3002
      \n\u8981\u6c42\u80fd\u56de\u7b54：\u5206\u9636\u6bb5\u8ba1\u65f6\u628a\u67d0\u6bb5\u65f6\u95f4\u8bb0\u5728 A \u9636\u6bb5\u540d\u4e0b，\u800c\u8ba1\u6570\u5668\u628a\u5b83\u5f52\u5230\u4e86 B \u51fd\u6570\u4e0a\u2014\u2014
      \n\u8fd9\u79cd\u60c5\u51b5\u5728\u4f60\u7684\u8bb0\u5f55\u91cc\u51fa\u73b0\u4e86\u5417？\u4e0a\u9762 strtoul \u548c ~vector<StrTick> \u8fd9\u4e24\u6761\u5c31\u662f\u4f8b\u5b50\u3002<\/li>\n
    • \u4e00\u4efd gprof \u8bb0\u5f55，\u5305\u542b -O2 \u548c -O0 \u4e24\u6b21\u7684\u5e73\u8868\u524d 10 \u884c，\u5e76\u5728\u65c1\u8fb9\u6ce8\u4e0a\u4f60\u4ece\u4e0a\u9762\u90a3\u5f20\u5bf9\u7167\u8868\u91cc\u7b97\u51fa\u7684\u6298\u635f\u3002\u8981\u6c42\u80fd\u56de\u7b54：gprof \u7684\u54ea\u4e00\u6761\u7ed3\u8bba\u53ef\u4ee5\u76f4\u63a5\u7528，\u54ea\u4e00\u6761\u5fc5\u987b\u6253\u6298\u6263\u3002<\/li>\n
    • \u4e00\u53e5\u8bdd\u7ed3\u8bba：v0.3 \u4f60\u6253\u7b97\u5148\u6539\u54ea\u4e00\u5904，\u4f9d\u636e\u662f\u54ea\u4e2a\u6570\u5b57\u3002<\/li>\n

      Guntheroth \u5728\u4e66\u91cc\u8bb2\u8fc7\u4e00\u4e2a\u53cd\u4f8b：\u4ed6\u66fe\u5728\u8c03\u8bd5\u5668\u91cc\u6d4b\u51fa deque \u6bd4\u9884\u671f\u300c\u6162\u4e00\u5343\u500d\u300d\u3002\u8fd9\u4e2a\u6570\u5b57\u8ba9\u4ed6\u82b1\u4e86\u5927\u91cf\u65f6\u95f4\u53bb\u67e5 deque \u7684\u5b9e\u73b0，\u6700\u540e\u53d1\u73b0\u662f\u5728\u8c03\u8bd5\u5668\u91cc\u6d4b\u91cf\u5bfc\u81f4\u7684\u2014\u2014\u8c03\u8bd5\u5668\u5173\u6389\u4e86\u4f18\u5316\u3001\u6539\u53d8\u4e86\u5185\u5b58\u5e03\u5c40，\u91cf\u5230\u7684\u5b8c\u5168\u4e0d\u662f\u53d1\u5e03\u7248\u672c\u7684\u884c\u4e3a\u3002<\/p>\n

      \u4e0a\u9762\u90a3\u4e2a -O0 \u6bd4 -O2 \u6162 15.2 \u500d\u7684\u6570，\u662f\u540c\u4e00\u7c7b\u9677\u9631\u7684\u53e6\u4e00\u79cd\u5f62\u6001\u3002\u6570\u5b57\u672c\u8eab\u6ca1\u9519，\u9519\u7684\u662f\u628a\u5b83\u5f53\u6210\u53d1\u5e03\u7248\u672c\u7684\u6570\u5b57\u7528\u3002<\/p>\n

      \u672c\u5355\u5143\u5f15\u7528\u4e0e\u6570\u5b57\u901f\u67e5\u5361<\/h3>\n

      \u672c\u673a\u73af\u5883：g++ 15.2（Ubuntu），-std=c++23 -O2，AMD Ryzen 9 7940H（8 \u6838 16 \u7ebf\u7a0b，L1d 32KB\/\u6838，L2 1MB\/\u6838，L3 16MB）\u3002\u6240\u6709\u8bbf\u5b58\u5b9e\u9a8c\u90fd\u7528 taskset -c 15 \u7ed1\u6838，\u53d6\u591a\u8f6e\u6700\u5c0f\u503c\u3002<\/p>\n

      \u9636\u68af（exp06，\u4e09\u8f6e\u6700\u5c0f\u503c）<\/h4>\n\n\u5c42\u7ea7\u5de5\u4f5c\u96c6\u6bcf\u6b65\u5ef6\u8fdf\u76f8\u5bf9 L1\u6296\u52a8（\u4e09\u8f6e max\/min）<\/tr>\n\n\n\n\n\n\n\n\n\n\n\n\n
      L1d<\/td>\n16 KB<\/td>\n1.04 ns<\/td>\n1.00x<\/td>\n1.05x<\/td>\n<\/tr>\n
      L1d<\/td>\n64 KB<\/td>\n2.14 ns<\/td>\n2.06x<\/td>\n1.02x<\/td>\n<\/tr>\n
      L2<\/td>\n256 KB<\/td>\n2.94 ns<\/td>\n2.83x<\/td>\n1.01x<\/td>\n<\/tr>\n
      L2<\/td>\n512 KB<\/td>\n3.83 ns<\/td>\n3.68x<\/td>\n1.10x<\/td>\n<\/tr>\n
      L2<\/td>\n1 MB<\/td>\n5.36 ns<\/td>\n5.15x<\/td>\n1.06x<\/td>\n<\/tr>\n
      L3<\/td>\n4 MB<\/td>\n10.22 ns<\/td>\n9.83x<\/td>\n1.47x<\/td>\n<\/tr>\n
      L3<\/td>\n8 MB<\/td>\n11.86 ns<\/td>\n11.40x<\/td>\n2.69x<\/td>\n<\/tr>\n
      L3<\/td>\n16 MB<\/td>\n34.09 ns \u26a0<\/td>\n32.78x<\/td>\n\u8de8\u8fd0\u884c 6.4x<\/td>\n<\/tr>\n
      \u4e3b\u5b58<\/td>\n32 MB<\/td>\n67.14 ns<\/td>\n64.56x<\/td>\n1.21x<\/td>\n<\/tr>\n
      \u4e3b\u5b58<\/td>\n64 MB<\/td>\n90.01 ns<\/td>\n86.55x<\/td>\n1.00x<\/td>\n<\/tr>\n
      \u4e3b\u5b58<\/td>\n256 MB<\/td>\n106.39 ns<\/td>\n102.30x<\/td>\n1.01x<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      16 MB \u90a3\u4e00\u6863\u6700\u4e0d\u7a33\u3002\u540c\u4e00\u53f0\u673a\u5668\u5728\u53e6\u4e00\u4e9b\u65f6\u523b\u7ed9\u51fa\u8fc7 27.56 \u548c 177.43 ns，\u800c\u672c\u6b21 exp06 \u91cd\u8dd1\u7ed9\u7684\u662f 27.68 ns\u3002\u8868\u91cc\u7684 34.09 \u662f\u91c7\u96c6\u5f53\u65f6\u7684\u4e00\u4e2a\u504f\u9ad8\u8bfb\u6570，\u4e0d\u662f\u8fd9\u4e00\u6863\u7684\u771f\u5b9e\u503c\u3002 \u62a5\u8fd9\u4e00\u6863\u7684\u6570\u65f6，\u628a\u8303\u56f4\u4e00\u8d77\u62a5\u4e0a\u3002<\/p>\n

      \u4e09\u6863\u8bbf\u95ee\u987a\u5e8f（exp07）<\/h4>\n\n\u8bbf\u95ee\u987a\u5e8f\u8bbf\u95ee\u6b21\u6570\u8017\u65f6\u642c\u8fd0\u901f\u7387\u6bcf\u6b21\u8bbf\u95ee<\/tr>\n\n\n\n\n
      \u987a\u5e8f<\/td>\n16777216<\/td>\n1.37 ms<\/td>\n45.6 GB\/s<\/td>\n0.08 ns<\/td>\n<\/tr>\n
      \u6b65\u957f 16<\/td>\n1048576<\/td>\n1.30 ms<\/td>\n48.1 GB\/s<\/td>\n1.24 ns<\/td>\n<\/tr>\n
      \u968f\u673a<\/td>\n1048576<\/td>\n5.42 ms<\/td>\n11.5 GB\/s<\/td>\n5.17 ns<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u540c\u4e00\u6b21\u8fd0\u884c\u914d\u7684\u8ba1\u6570\u5668（\u6bcf\u6863 20 \u904d，\u5df2\u51cf none \u57fa\u7ebf）：<\/p>\n\n\u8bbf\u95ee\u987a\u5e8fL1 \u8bfb miss\u9884\u53d6\u8bf7\u6c42\u547d\u4e2d L2\u9884\u53d6\u8bf7\u6c42\u4e0b\u6c89 L3L2 \u9700\u6c42 miss<\/tr>\n\n\n\n\n
      \u987a\u5e8f<\/td>\n20,978,696<\/td>\n21,161,940<\/td>\n20,868,706<\/td>\n96,854<\/td>\n<\/tr>\n
      \u6b65\u957f 16<\/td>\n20,991,049<\/td>\n1,630,066<\/td>\n15,692,664<\/td>\n205,633<\/td>\n<\/tr>\n
      \u968f\u673a<\/td>\n22,335,258<\/td>\n1,604,650<\/td>\n1,152,055<\/td>\n21,686,647<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      L1 \u90a3\u4e00\u5217\u4e09\u6863\u76f8\u540c（\u642c\u8fd0\u91cf\u76f8\u540c），L2 \u9700\u6c42 miss \u5dee\u4e24\u4e2a\u6570\u91cf\u7ea7（\u9884\u53d6\u5668\u8ba4\u4e0d\u8ba4\u5f97\u51fa）\u3002
      \n\u4e2d\u95f4\u4e24\u5217\u4e0d\u80fd\u76f8\u52a0，\u7406\u7531\u89c1\u7b2c\u4e09\u8bb2\u3002<\/p>\n

      \u5143\u7d20\u5c3a\u5bf8\u626b\u63cf（exp08，\u6709\u7528\u6570\u636e\u6052\u4e3a 16 MB，\u8bbf\u95ee\u6b21\u6570\u6052\u4e3a 4194304）<\/h4>\n\n\u5143\u7d20\u5c3a\u5bf8\u4e00\u884c\u88c5\u51e0\u4e2a\u642c\u8fd0\u91cf\u8017\u65f6\u642c\u8fd0\u901f\u7387\u76f8\u5bf9 4B<\/tr>\n\n\n\n\n\n\n\n
      4 B<\/td>\n16<\/td>\n16 MB<\/td>\n0.31 ms<\/td>\n50.3 GB\/s<\/td>\n1.00x<\/td>\n<\/tr>\n
      8 B<\/td>\n8<\/td>\n32 MB<\/td>\n0.55 ms<\/td>\n56.8 GB\/s<\/td>\n1.77x<\/td>\n<\/tr>\n
      16 B<\/td>\n4<\/td>\n64 MB<\/td>\n1.17 ms<\/td>\n53.3 GB\/s<\/td>\n3.77x<\/td>\n<\/tr>\n
      32 B<\/td>\n2<\/td>\n128 MB<\/td>\n2.48 ms<\/td>\n50.3 GB\/s<\/td>\n8.00x<\/td>\n<\/tr>\n
      64 B<\/td>\n1<\/td>\n256 MB<\/td>\n5.07 ms<\/td>\n49.3 GB\/s<\/td>\n16.31x<\/td>\n<\/tr>\n
      128 B<\/td>\n\u8de8\u4e24\u884c<\/td>\n512 MB<\/td>\n18.26 ms<\/td>\n27.4 GB\/s<\/td>\n58.77x<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u904d\u5386\u987a\u5e8f（exp09）<\/h4>\n\n\u89c4\u6a21\u884c\u4f18\u5148\u5217\u4f18\u5148\u500d\u7387\u5206\u5757 16\u5206\u5757\u500d\u7387<\/tr>\n\n\n\n\n
      16 KB（N=64）<\/td>\n0.0014 ms<\/td>\n0.0016 ms<\/td>\n1.1x<\/td>\n0.0021 ms<\/td>\n1.50x<\/td>\n<\/tr>\n
      4 MB（N=1024）<\/td>\n0.3981 ms<\/td>\n5.0396 ms<\/td>\n12.7x<\/td>\n0.4015 ms<\/td>\n1.01x<\/td>\n<\/tr>\n
      64 MB（N=4096）<\/td>\n5.8857 ms<\/td>\n117.96 ms<\/td>\n20.0x<\/td>\n8.0741 ms<\/td>\n1.37x<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      N=1024 \u7684\u8ba1\u6570\u5668（\u6bcf\u6863 30 \u904d = 31,457,280 \u6b21\u8bbf\u95ee，\u5df2\u51cf none \u57fa\u7ebf）：<\/p>\n\n\u904d\u5386\u987a\u5e8fL1 \u8bfb miss\u5360\u8bbf\u95ee\u6b21\u6570L2 miss\u5360\u8bbf\u95ee\u6b21\u6570<\/tr>\n\n\n\n\n
      \u884c\u4f18\u5148<\/td>\n1,993,090<\/td>\n6.3%<\/td>\n32,094 \u26a0<\/td>\n0.10%<\/td>\n<\/tr>\n
      \u5217\u4f18\u5148<\/td>\n33,442,254<\/td>\n106.3%<\/td>\n16,227,239<\/td>\n51.6%<\/td>\n<\/tr>\n
      \u5206\u5757 16<\/td>\n6,251,754<\/td>\n19.9%<\/td>\n312,837<\/td>\n1.0%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u884c\u4f18\u5148\u7684 L1 \u5217\u662f\u7406\u8bba\u503c 1,966,080（65536 \u6761 line \u00d7 30 \u904d）\u52a0 1% \u4e0a\u4e0b\u3002
      \n\u26a0 \u8fd9\u4e00\u683c\u662f\u4e24\u4e2a\u5c0f\u6570\u5b57\u76f8\u51cf\u5f97\u5230\u7684，\u51e0\u6b21\u8fd0\u884c\u80fd\u5dee\u4e00\u500d；\u5217\u4f18\u5148\u90a3\u683c\u5dee\u4e24\u4e2a\u6570\u91cf\u7ea7，\u600e\u4e48\u6643\u90fd\u4e0d\u7ffb\u3002<\/p>\n

      MiniQuote v0.1（1M \u6761，-O2）<\/h4>\n\n\u9636\u6bb5\u8017\u65f6\u5360\u6bd4<\/tr>\n\n\n\n\n\n\n\n
      \u8bfb\u6587\u4ef6<\/td>\n13.5 ms<\/td>\n6.7%<\/td>\n<\/tr>\n
      \u5efa StrTick \u6570\u7ec4<\/td>\n65.5 ms<\/td>\n32.5%<\/td>\n<\/tr>\n
      \u9010\u6761\u8f6c\u5b57\u7b26\u4e32<\/td>\n74.7 ms<\/td>\n37.1%<\/td>\n<\/tr>\n
      \u5efa map \u5e76\u6c47\u603b<\/td>\n46.7 ms<\/td>\n23.2%<\/td>\n<\/tr>\n
      \u7b97\u6c47\u603b\u6570\u5b57<\/td>\n0.9 ms<\/td>\n0.4%<\/td>\n<\/tr>\n
      \u5408\u8ba1<\/td>\n201.3 ms<\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      StrTick \u5185\u5b58 152.6 MB（\u6bcf\u6761 160 B，\u539f\u59cb\u8bb0\u5f55 24 B）\u3002<\/p>\n

      \u4e24\u5957\u8ba1\u6570\u5668\u8bfb\u6570（MiniQuote v0.1，1M \u6761）<\/h4>\n

      \u4e24\u4e2a\u5de5\u5177\u5404\u8dd1\u4e00\u6b21，\u4e0d\u662f\u540c\u4e00\u6b21\u8fd0\u884c：<\/p>\n\nperf statcachegrind<\/tr>\n\n\n\n\n\n\n
      L1 \u8bfb miss<\/td>\n23,191,183<\/td>\n12,608,397（\u5360\u8bfb\u7684 2.3%）<\/td>\n<\/tr>\n
      \u4e0b\u4e00\u7ea7 miss<\/td>\n1,797,244（L2 \u9700\u6c42 miss）<\/td>\n11,634,697（LLd，2.1%）<\/td>\n<\/tr>\n
      \u8bbf\u95ee\u8ba1\u6570<\/td>\n43,826,849（cache-references）<\/td>\n541,724,149（D refs = Dr 320,744,941 + Dw 220,979,208）<\/td>\n<\/tr>\n
      \u5899\u949f<\/td>\n0.246 s<\/td>\n\u6162\u7ea6 50 \u500d<\/td>\n<\/tr>\n
      \u81ea\u8eab\u6ce2\u52a8（\u591a\u6b21\u8fd0\u884c）<\/td>\nL1 3.3%，L2 2.0 \u500d<\/td>\n\u8bfb\u4fa7 2.2%，\u5199\u4fa7 0.002%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      L1 \u5dee 1.8 \u500d，\u4e0b\u4e00\u7ea7\u5dee 6.5 \u500d，\u90fd\u8fdc\u5927\u4e8e\u4e24\u4e2a\u5de5\u5177\u5404\u81ea\u7684\u6643\u52a8\u3002\u6765\u6e90\u89c1 B \u7ebf：
      \ncachegrind \u4e0d\u6a21\u62df\u9884\u53d6\u5668，\u800c perf \u7684 cache-misses \u53ea\u6570\u9700\u6c42 miss\u3002
      \n\u4e24\u5957\u6570\u4e0d\u80fd\u4e92\u76f8\u9a8c\u8bc1，\u53ea\u80fd\u4e92\u76f8\u8865\u5145\u3002<\/p>\n

      cg_annotate –show=Dr,D1mr,DLmr –threshold=0.5 \u7684\u524d\u51e0\u884c
      \n（-O2 -g \u6784\u5efa；\u4e0d\u5e26 -g \u8868\u662f\u7a7a\u7684，\u4e0d\u5e26 –threshold \u5c0f\u6761\u76ee\u4f1a\u88ab\u85cf\u8d77\u6765）：<\/p>\n\n\u5f52\u5c5eDrD1mrDLmr\u5360 D1 \u8bfb miss<\/tr>\n\n\n\n\n\n
      bits\/basic_string.h \u2190 main 100 \u4e07 \/ ~vector<StrTick> 250 \u4e07<\/td>\n39,000,000<\/td>\n3,500,002<\/td>\n3,500,002<\/td>\n49.3%<\/td>\n<\/tr>\n
      strtol_l.c:____strtoul_l_internal<\/td>\n39,006,194<\/td>\n1,000,005<\/td>\n1,000,005<\/td>\n14.1%<\/td>\n<\/tr>\n
      bits\/stl_tree.h \u2190 main<\/td>\n40,741,642<\/td>\n337,809<\/td>\n52,358<\/td>\n4.8%<\/td>\n<\/tr>\n
      \u4e09\u6761\u5408\u8ba1<\/td>\n<\/td>\n<\/td>\n<\/td>\n68.2%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u5de5\u5177\u6298\u635f（5M \u6761）<\/h4>\n\n-O2-O0 -pg<\/tr>\n\n\n\n\n\n\n
      \u5408\u8ba1<\/td>\n983.8 ms<\/td>\n14920.0 ms（15.2x）<\/td>\n<\/tr>\n
      gprof \u91c7\u6837\u5230\u7684\u65f6\u957f<\/td>\n\u2014<\/td>\n4.17 s（\u5360\u5b9e\u9645 28%）<\/td>\n<\/tr>\n
      \u5efa StrTick \u5360\u6bd4<\/td>\n32.1%<\/td>\n9.6%<\/td>\n<\/tr>\n
      \u8f6c\u5b57\u7b26\u4e32\u5360\u6bd4<\/td>\n36.8%<\/td>\n64.9%<\/td>\n<\/tr>\n
      \u5efa map \u5360\u6bd4<\/td>\n24.2%<\/td>\n25.1%<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u5e72\u6270\u91cf\u7ea7<\/h4>\n\n\u573a\u666f\u73b0\u8c61<\/tr>\n\n\n\n\n\n\n
      \u4e0d\u7ed1\u6838\u3001\u684c\u9762\u8d1f\u8f7d\u7ea6 3<\/td>\n512KB \u62a5 30.44 ns（\u5b9e\u4e3a 3.83），4MB \u62a5 113.18 ns（\u5b9e\u4e3a 10.22）<\/td>\n<\/tr>\n
      \u7ed1\u6838\u540e\u4ecd\u6296<\/td>\n8MB \u4e00\u6863\u5728 11.86 ~ 31.95 ns \u4e4b\u95f4\u8df3（2.69x）<\/td>\n<\/tr>\n
      \u5e72\u6270\u6301\u7eed\u6574\u6863<\/td>\n16MB \u4e00\u6863\u5728 27.56 ~ 177.43 ns \u4e4b\u95f4\u8df3（6.4x），min-of-5 \u6321\u4e0d\u4f4f<\/td>\n<\/tr>\n
      \u8f6e\u6570\u4e0d\u8db3<\/td>\n4B \u5143\u7d20\u6863\u8dd1 5 \u8f6e\u62a5 19.1 GB\/s，\u8dd1 21 \u8f6e\u624d\u7a33\u5b9a\u5728 50 GB\/s<\/td>\n<\/tr>\n
      \u6362\u7b97\u7cfb\u6570\u5199\u9519<\/td>\nitems_of \u5c11\u7b97 3.75 \u500d，\u6574\u6761\u66f2\u7ebf\u6574\u4f53\u7f29\u653e，\u5f62\u72b6\u4e0d\u53d8\u3001\u4e0d\u62a5\u9519<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u51fa\u81ea\u6559\u6750<\/h4>\n\n\u51fa\u81ea\u6559\u6750\u5185\u5bb9<\/tr>\n\n\n\n
      Guntheroth<\/td>\n\u76f4\u89c9\u627e\u70ed\u70b9\u548c profiler \u57fa\u672c\u4e00\u81f4，\u4f46\u76f4\u89c9\u8def\u7ebf\u4f9d\u7136\u4e0d\u53ef\u53d6\u2014\u2014\u522b\u4eba\u6ca1\u6cd5\u9a8c\u8bc1\u4f60\u7684\u76f4\u89c9<\/td>\n<\/tr>\n
      Guntheroth<\/td>\n\u5728\u8c03\u8bd5\u5668\u91cc\u6d4b\u51fa deque\u300c\u6162\u4e00\u5343\u500d\u300d，\u539f\u56e0\u662f\u6d4b\u91cf\u73af\u5883\u800c\u975e deque<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u7ec3\u4e60\u4e0e\u53c2\u8003\u7b54\u6848<\/h3>\n

      \u7ec3\u4e60 1（\u5fc5\u505a）：\u628a exp06 \u7684\u626b\u63cf\u70b9\u52a0\u5bc6\u5230 2 \u500d\u9012\u589e（16\u300132\u300164\u3001128\u2026\u2026），\u5728 16KB~64KB \u548c 512KB~1MB \u4e24\u6bb5\u5404\u8865\u51e0\u4e2a\u70b9\u3002\u91cd\u8dd1，\u56de\u7b54：L1 \u7684\u8fb9\u754c\u66f4\u63a5\u8fd1 32KB \u8fd8\u662f 64KB？\u548c\u6807\u79f0\u7684 32KB \u5dee\u591a\u5c11？<\/p>\n

      \u53c2\u8003\u7b54\u6848：\u8fb9\u754c\u4f1a\u843d\u5728\u4e00\u4e2a\u533a\u95f4\u91cc，\u4e0d\u4f1a\u843d\u5728 32KB \u8fd9\u4e2a\u70b9\u4e0a\u3002\u539f\u56e0\u6709\u4e09\u4e2a：L1 \u662f 8 \u8def\u7ec4\u76f8\u8054\u800c\u975e\u5168\u76f8\u8054，\u5b9e\u9645\u53ef\u7528\u7684\u5229\u7528\u7387\u4f4e\u4e8e 100%；L1 \u91cc\u8fd8\u8981\u653e\u6307\u4ee4\u3001TLB \u8868\u9879\u7b49；\u968f\u673a\u73af\u672c\u8eab\u7684\u5143\u6570\u636e\u4e5f\u5360\u7a7a\u95f4\u3002\u62a5\u8fb9\u754c\u65f6\u62a5\u533a\u95f4\u3002 \u8fd9\u9053\u9898\u7684\u6536\u83b7\u662f\u300c\u6807\u79f0\u5bb9\u91cf\u300d\u548c\u300c\u5b9e\u6d4b\u8fb9\u754c\u300d\u4e0d\u662f\u4e00\u56de\u4e8b\u3002<\/p>\n

      \u7ec3\u4e60 2：\u62ff exp07 \u6539\u4e00\u4e2a\u53c2\u6570\u2014\u2014\u628a\u968f\u673a\u90a3\u4e00\u6863\u7684 idx \u6539\u6210\u6392\u597d\u5e8f\u7684（\u4e0d\u518d\u662f\u968f\u673a\u987a\u5e8f），\u5176\u4ed6\u4e0d\u52a8，\u91cd\u8dd1\u3002\u4e09\u6863\u73b0\u5728\u5404\u662f\u4ec0\u4e48\u901f\u7387？<\/p>\n

      \u53c2\u8003\u7b54\u6848：\u6392\u597d\u5e8f\u4e4b\u540e\u5b83\u5c31\u662f\u987a\u5e8f\u8bbf\u95ee\u7684\u4e00\u4e2a\u7a00\u758f\u7248\u672c，\u901f\u7387\u4f1a\u56de\u5230 45 GB\/s \u4e0a\u4e0b，\u548c\u300c\u6b65\u957f 16\u300d\u90a3\u4e00\u6863\u51e0\u4e4e\u4e00\u6837\u3002\u8fd9\u9053\u9898\u60f3\u8bf4\u660e\u7684\u662f：\u51b3\u5b9a\u6210\u672c\u7684\u662f\u300c\u5730\u5740\u6d41\u80fd\u4e0d\u80fd\u88ab\u9884\u6d4b\u300d，\u53d6\u4e86\u591a\u5c11\u5143\u7d20\u53ea\u5728\u5176\u6b21\u3002 \u7a00\u758f\u672c\u8eab\u4e0d\u8d35，\u4e71\u624d\u8d35\u3002<\/p>\n

      \u7ec3\u4e60 3：\u7528 exp08 \u7684\u601d\u8def，\u8bbe\u8ba1\u4e00\u4e2a\u5b9e\u9a8c\u56de\u7b54\u8fd9\u4e2a\u95ee\u9898：std::vector<int> \u548c std::vector<char>，\u6c42\u548c\u4e00\u904d，\u54ea\u4e2a\u5feb？\u4e3a\u4ec0\u4e48？<\/p>\n

      \u53c2\u8003\u7b54\u6848：\u8981\u5148\u628a\u300c\u4e00\u5171\u591a\u5c11\u4e2a\u5143\u7d20\u300d\u56fa\u5b9a\u4f4f，\u5426\u5219\u4e24\u4e2a\u6570\u7ec4\u7684\u603b\u5b57\u8282\u6570\u4e0d\u540c，\u6bd4\u7684\u662f\u5bb9\u91cf\u4e0d\u662f\u5143\u7d20\u5c3a\u5bf8\u3002\u56fa\u5b9a\u5143\u7d20\u6570 N \u4e4b\u540e，vector<int> \u642c 4N \u5b57\u8282，vector<char> \u642c N \u5b57\u8282\u2014\u2014\u4f46\u4e24\u8005\u90fd\u53ef\u80fd\u843d\u5230\u300c\u4e00\u884c\u88c5\u5f97\u4e0b\u591a\u4e2a\u300d\u7684\u533a\u95f4\u91cc，\u5b9e\u9645\u901f\u7387\u4f1a\u5f88\u63a5\u8fd1，\u5dee\u5f02\u4e3b\u8981\u5728\u6bcf\u5468\u671f\u80fd\u53d1\u5c04\u7684\u8bbf\u5b58\u6307\u4ee4\u6570\u548c\u5411\u91cf\u5316\u5bbd\u5ea6\u4e0a\u3002\u8fd9\u9053\u9898\u7684\u4ef7\u503c\u662f\u66b4\u9732\u4e00\u4e2a\u5e38\u89c1\u9519\u8bef：\u6bd4\u8f83\u4e24\u79cd\u5143\u7d20\u5c3a\u5bf8\u65f6，\u4e0d\u56fa\u5b9a\u5143\u7d20\u6570\u5c31\u5f97\u4e0d\u51fa\u5e72\u51c0\u7ed3\u8bba\u3002<\/p>\n

      \u7ec3\u4e60 4：exp09 \u7684\u5217\u4f18\u5148\u5728 N=1024 \u65f6\u6162 12.7 \u500d，\u539f\u56e0\u662f\u6b65\u957f 4096 \u5b57\u8282\u5bf9 L1 \u7684 64 \u4e2a\u7ec4\u53d6\u6a21\u7b49\u4e8e 0\u3002\u8bf7\u7b97\u51fa N \u53d6\u591a\u5c11\u65f6\u5217\u4f18\u5148\u7684\u6b65\u957f\u4f1a\u4e0d\u548c L1 \u7ec4\u6570\u51b2\u7a81，\u5e76\u9a8c\u8bc1\u3002<\/p>\n

      \u53c2\u8003\u7b54\u6848：\u6b65\u957f = N \u00d7 4 \u5b57\u8282，\u9664\u4ee5 64 \u5b57\u8282\u5f97\u5230\u76f8\u9694\u7684 line \u6570 = N\/16\u3002\u8981\u8ba9 (N\/16) mod 64 \u2260 0，N \u4e0d\u80fd\u662f 1024 \u7684\u500d\u6570\u3002\u53d6 N = 1040（\u6b65\u957f 4160 \u5b57\u8282 = 65 \u6761 line，65 mod 64 = 1），\u7ec4\u51b2\u7a81\u6d88\u5931，\u5217\u4f18\u5148\u5e94\u8be5\u63a5\u8fd1\u884c\u4f18\u5148\u3002\u8dd1\u4e00\u4e0b\u5c31\u80fd\u9a8c\u8bc1\u2014\u2014exp09_locality.cpp \u91cc\u628a N \u4ece 1024 \u6362\u6210 1040 \u5373\u53ef\u3002\u8fd9\u9053\u9898\u8bf4\u660e\u300c2 \u7684\u5e42\u300d\u5728\u5e03\u5c40\u95ee\u9898\u91cc\u662f\u4e2a\u9700\u8981\u4e3b\u52a8\u6000\u7591\u7684\u6570\u5b57\u3002<\/p>\n

      \u7ec3\u4e60 5：B \u7ebf\u7684 v0.1 \u91cc，StrTick \u6570\u7ec4\u5360 152.6 MB \u800c\u539f\u59cb\u8bb0\u5f55\u53ea\u6709 22.9 MB\u3002\u7528\u672c\u5355\u5143\u7b2c\u56db\u8bb2\u7684\u6362\u7b97\u4f30\u4e00\u4e0b：\u5982\u679c\u53bb\u6389 StrTick \u8fd9\u4e00\u5c42，\u53ea\u4fdd\u7559 vector<Tick>，\u7b2c\u4e8c\u9636\u6bb5\u7684\u65f6\u95f4\u5927\u6982\u80fd\u964d\u5230\u591a\u5c11？\u5b9e\u9645\u6539\u4e00\u7248\u9a8c\u8bc1\u3002<\/p>\n

      \u53c2\u8003\u7b54\u6848：\u9884\u4f30\u7684\u601d\u8def\u662f\u300c\u8017\u65f6 \u2248 \u642c\u8fd0\u91cf \u00f7 \u5e26\u5bbd\u300d\u3002StrTick \u90a3\u4e00\u5c42\u8981\u642c 152.6 MB（\u6784\u9020\u4e00\u6b21）+ 152.6 MB（\u586b\u5b57\u6bb5），Tick \u90a3\u4e00\u5c42\u53ea\u8981\u642c 22.9 MB + 22.9 MB\u3002\u7c97\u7565\u4f30\u8ba1\u80fd\u964d\u5230\u539f\u6765\u7684 15% \u4e0a\u4e0b\u3002\u5b9e\u9645\u6539\u5b8c\u53ef\u80fd\u5bf9\u4e0d\u4e0a\u2014\u2014\u56e0\u4e3a\u300c\u8f6c\u5b57\u7b26\u4e32\u300d\u90a3\u4e00\u6b65\u7684\u4ee3\u4ef7\u4e0d\u53ea\u662f\u642c\u8fd0，\u8fd8\u6709 to_string \u672c\u8eab\u7684\u6307\u4ee4\u6570\u3002\u5bf9\u4e0d\u4e0a\u7684\u90e8\u5206\u5c31\u662f\u8fd9\u4e2a\u6a21\u578b\u7684\u8fb9\u754c，\u628a\u5b83\u8bb0\u4e0b\u6765\u3002<\/p>\n

      \u9a8c\u6536\u81ea\u6d4b（\u542b\u7b54\u6848）<\/h3>\n
    • \n

      \u4e00\u6bb5\u4ee3\u7801\u91cc\u6709\u4e00\u6b21\u4e3b\u5b58 miss\u3002CPU \u5728\u8fd9\u6bb5\u65f6\u95f4\u91cc\u672c\u6765\u80fd\u6267\u884c\u591a\u5c11\u6761\u6574\u6570\u52a0\u6cd5？
      \n\u7b54：\u4e3b\u5b58\u5ef6\u8fdf\u7ea6 90~106 ns（\u672c\u673a\u5b9e\u6d4b），\u6574\u6570\u52a0\u6cd5\u7ea6 0.25 ns，\u6240\u4ee5\u662f 300~400 \u6761\u3002\u8fd9\u5c31\u662f\u300c\u4e00\u6b21 miss \u503c\u51e0\u767e\u6761\u6307\u4ee4\u300d\u8fd9\u4e2a\u8bf4\u6cd5\u7684\u7b97\u672f\u6765\u6e90\u3002<\/p>\n<\/li>\n

    • \n

      \u540c\u4e00\u4efd exp06，\u4e0d\u7ed1\u6838\u65f6 512KB \u62a5 30.44 ns，\u7ed1\u6838\u540e\u62a5 3.83 ns\u3002\u54ea\u4e2a\u662f\u771f\u7684？
      \n\u7b54：3.83 ns\u3002\u4f46\u66f4\u91cd\u8981\u7684\u662f\u5224\u65ad\u65b9\u6cd5：\u770b\u6574\u6761\u66f2\u7ebf\u662f\u5426\u5355\u8c03\u3001\u662f\u5426\u5e73\u6ed1\u300230.44 \u90a3\u4e00\u7248\u5728 256KB（4.75 ns）\u548c 1MB（17.91 ns）\u4e4b\u95f4\u63d2\u4e86\u4e00\u4e2a 30.44，\u66f2\u7ebf\u9f13\u4e86\u4e00\u4e2a\u5305\u2014\u2014\u8bbf\u5b58\u5ef6\u8fdf\u4e0d\u4f1a\u8fd9\u4e48\u8d70\u3002\u5148\u770b\u5f62\u72b6，\u518d\u770b\u5355\u70b9\u3002<\/p>\n<\/li>\n

    • \n

      exp07 \u91cc\u968f\u673a\u90a3\u4e00\u6863\u53ea\u53d6 1\/16 \u7684\u5143\u7d20，\u5374\u6bd4\u987a\u5e8f\u90a3\u4e00\u6863\u6162 4 \u500d\u3002\u662f\u4e0d\u662f\u8bf4\u660e\u968f\u673a\u8bbf\u95ee\u300c\u66f4\u8d35\u300d？
      \n\u7b54：\u4e0d\u80fd\u8fd9\u4e48\u8bfb\u3002\u968f\u673a\u90a3\u4e00\u6863\u7684 5.17 ns \u662f\u644a\u5230\u6bcf\u6b21\u8bbf\u95ee\u7684\u541e\u5410\u503c，\u5b83\u9760\u5185\u5b58\u5e76\u884c\u5ea6\u644a\u8584\u8fc7\u3002\u5355\u6b21\u968f\u673a\u8bbf\u5b58\u5ef6\u8fdf\u662f 90~106 ns\u3002\u7528\u54ea\u4e2a\u6570\u53d6\u51b3\u4e8e\u4ee3\u7801\u91cc\u6709\u6ca1\u6709\u4f9d\u8d56\u94fe：\u904d\u5386\u6570\u7ec4\u7528 5 ns，\u8ddf\u7740\u6307\u9488\u8d70\u7528 100 ns\u3002<\/p>\n<\/li>\n

    • \n

      exp08 \u91cc\u5143\u7d20\u4ece 4 \u5b57\u8282\u957f\u5230 64 \u5b57\u8282，\u8017\u65f6\u6da8\u4e86 16.31 \u500d\u800c\u4e0d\u662f 16 \u500d，\u591a\u51fa\u6765\u7684 2% \u4ece\u54ea\u6765？
      \n\u7b54：\u8bfb\u5230\u7684\u6709\u7528\u5b57\u8282\u6570\u867d\u7136\u76f8\u540c，\u4f46\u6307\u4ee4\u6570\u5e76\u4e0d\u5b8c\u5168\u76f8\u540c；\u6b64\u5916 4 \u5b57\u8282\u90a3\u4e00\u6863\u7684\u8bfb\u6570\u672c\u8eab\u53d7\u53d1\u5c04\u5bbd\u5ea6\u5f71\u54cd，\u7a33\u5b9a\u6027\u548c\u5927\u5c3a\u5bf8\u6863\u4e0d\u540c\u3002\u8fd9\u7c7b\u5c0f\u504f\u5dee\u5c5e\u4e8e\u566a\u58f0\u91cf\u7ea7，\u4e0d\u8be5\u53bb\u89e3\u91ca\u5b83\u2014\u2014\u8981\u533a\u5206\u300c\u503c\u5f97\u89e3\u91ca\u7684\u5dee\u5f02\u300d\u548c\u300c\u566a\u58f0\u300d，\u6807\u51c6\u662f\u5b83\u6709\u6ca1\u6709\u8d85\u8fc7\u672c\u5355\u5143\u91cf\u5230\u7684\u6296\u52a8（1.0x~2.7x）\u3002<\/p>\n<\/li>\n

    • \n

      exp09 \u91cc 4MB \u7684\u77e9\u9635\u6574\u5757\u90fd\u5728 16MB \u7684 L3 \u91cc，\u5217\u4f18\u5148\u4e3a\u4ec0\u4e48\u8fd8\u6162 12.7 \u500d？
      \n\u7b54：\u5361\u4f4f\u5b83\u7684\u662f L1 \u4e0d\u662f L3\u3002N=1024 \u65f6\u5217\u4f18\u5148\u7684\u6b65\u957f\u662f 4096 \u5b57\u8282，\u6b63\u597d\u662f 64 \u6761 cache line，\u5bf9 L1 \u7684 64 \u4e2a\u7ec4\u53d6\u6a21\u7b49\u4e8e 0\u2014\u2014\u6bcf\u6b21\u8bbf\u95ee\u90fd\u843d\u5728\u540c\u4e00\u4e2a\u7ec4\u4e0a，8 \u8def\u88c5\u4e0d\u4e0b\u5c31\u4e92\u76f8\u6324\u3002\u8fd9\u662f\u7ec4\u51b2\u7a81，\u4e0d\u662f\u5bb9\u91cf\u4e0d\u8db3\u3002<\/p>\n<\/li>\n

    • \n

      \u4e00\u4e2a\u7ed3\u6784\u4f53 160 \u5b57\u8282，\u4f60\u8981\u904d\u5386\u5b83\u5e76\u5bf9\u5176\u4e2d\u4e00\u4e2a 4 \u5b57\u8282\u5b57\u6bb5\u6c42\u548c，\u5171 100 \u4e07\u4e2a\u5bf9\u8c61\u3002\u7528\u672c\u5355\u5143\u7684\u6362\u7b97\u4f30\u7b97\u642c\u8fd0\u91cf，\u5e76\u8bf4\u660e\u4e3a\u4ec0\u4e48\u62c6\u6210 SoA \u4e4b\u540e\u4f1a\u5feb\u3002
      \n\u7b54：160 \u5b57\u8282\u7684\u5143\u7d20，\u4e00\u884c 64 \u5b57\u8282\u88c5\u4e0d\u4e0b\u4e00\u4e2a，\u6bcf\u4e2a\u5143\u7d20\u8de8 3 \u6761 line（\u5bf9\u9f50\u540e 3 \u6761，\u5b9e\u9645\u53d6\u5230\u90a3\u6761 line \u53ea\u80fd\u8986\u76d6 64 \u5b57\u8282\u4e2d\u7684 4 \u5b57\u8282）\u3002\u642c\u8fd0\u91cf\u6309\u6700\u574f\u7b97\u662f 100 \u4e07 \u00d7 192 \u5b57\u8282 = 192 MB；\u62c6\u6210 SoA \u4e4b\u540e\u53ea\u9700\u8981\u90a3\u4e2a\u5b57\u6bb5\u7684 4 MB，\u642c\u8fd0\u91cf\u964d 48 \u500d\u3002\u8fd9\u6b63\u662f MiniQuote v0.1 \u91cc StrTick \u90a3\u4e00\u5c42\u7684\u5904\u5883\u2014\u2014\u5f52\u56e0\u843d\u5230\u300c\u5de5\u4f5c\u96c6\u88ab\u6491\u5927\u4e86\u51e0\u500d\u300d\u4e0a，\u6bd4\u843d\u5230\u300c\u5b57\u7b26\u4e32\u8f6c\u6362\u6162\u300d\u4e0a\u66f4\u6709\u89e3\u91ca\u529b\u3002<\/p>\n<\/li>\n

    • \n

      \u7528 gprof \u5728 -O0 \u4e0b\u6d4b\u51fa\u300c\u8f6c\u5b57\u7b26\u4e32\u5360 64.9%\u300d，\u5728 -O2 \u4e0b\u6d4b\u51fa\u300c\u5360 36.8%\u300d\u3002\u54ea\u4e2a\u8be5\u62ff\u53bb\u6307\u5bfc\u4f18\u5316？
      \n\u7b54：-O2 \u7684 36.8%\u3002-O0 \u5173\u6389\u4e86\u5185\u8054，\u6240\u6709\u5b57\u7b26\u4e32\u64cd\u4f5c\u53d8\u6210\u771f\u5b9e\u51fd\u6570\u8c03\u7528，\u4ee3\u4ef7\u88ab\u4e0d\u6210\u6bd4\u4f8b\u5730\u653e\u5927，\u70ed\u70b9\u7684\u6392\u5e8f\u90fd\u53d8\u4e86\u3002gprof \u8fd8\u6709\u4e00\u4e2a\u989d\u5916\u7684\u5c40\u9650：\u5b83\u53ea\u8986\u76d6\u4e3b\u7a0b\u5e8f\u7684\u4ee3\u7801\u6bb5，libstdc++ \u91cc\u7684\u65f6\u95f4\u770b\u4e0d\u89c1\u2014\u2014\u90a3\u4efd 5M \u6761\u7684\u8fd0\u884c\u91cc，gprof \u53ea\u91c7\u5230 4.17 \u79d2\u800c\u7a0b\u5e8f\u5b9e\u9645\u8dd1\u4e86 14.92 \u79d2\u3002<\/p>\n<\/li>\n","protected":false},"excerpt":{"rendered":"

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