{"id":122992,"date":"2026-11-06T05:56:46","date_gmt":"2026-11-05T21:56:46","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/122992.html"},"modified":"2026-11-06T05:56:46","modified_gmt":"2026-11-05T21:56:46","slug":"gpu-%e5%86%85%e5%ad%98%e6%a8%a1%e5%9e%8b%e6%b5%85%e8%a7%a3-%e5%9b%9b%e5%b1%82%e5%ad%98%e5%82%a8%e3%80%81%e7%bc%96%e7%a8%8b%e6%8e%a7%e5%88%b6","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/122992.html","title":{"rendered":"GPU \u5185\u5b58\u6a21\u578b\u6d45\u89e3 - \u56db\u5c42\u5b58\u50a8\u3001\u7f16\u7a0b\u63a7\u5236"},"content":{"rendered":"

\/* MD \/ \u5bcc\u6587\u672c\u4e2d\u7684 .toc\uff08\u542b\u535a\u5ba2\u56ed\u642c\u5bb6\u7b49\u5d4c\u5957\u7ed3\u6784\uff09\uff1b.toc-box \u5728\u4fa7\u680f\uff0c\u4e0d\u53d7\u5f71\u54cd *\/
\n #content_views .toc,
\n \/* \u7f16\u8f91\u5668\u5e38\u5728\u76ee\u5f55\u524d\u540e\u63d2\u5165\u7a7a p\uff08:empty \u4ecd\u5360 20px\uff09\uff0c\u4e00\u5e76\u53bb\u6389\u907f\u514d\u9876\u7a7a\u9699 *\/
\n #content_views.markdown_views > p:empty:has(+ .toc),
\n #content_views.markdown_views > .toc + p:empty,
\n \/* \u5bcc\u6587\u672c\u65e7\u7248\u76ee\u5f55\u6807\u8bb0 *\/
\n #content_views.htmledit_views #main-toc,
\n #content_views.htmledit_views #hr-toc,
\n #content_views.htmledit_views p[id*=\\”-toc\\”] {
\n display: none !important;
\n }
\n \/* \u76ee\u5f55\u53bb\u6389\u540e\uff0c\u7d27\u8ddf\u7684\u9996\u4e2a\u6807\u9898\u4e0d\u518d\u591a\u51fa\u4e00\u5757\u4e0a\u8fb9\u8ddd *\/
\n #content_views.markdown_views > .toc + h1,
\n #content_views.markdown_views > .toc + h2,
\n #content_views.markdown_views > .toc + h3,
\n #content_views.markdown_views > .toc + h4,
\n #content_views.markdown_views > .toc + p:empty + h1,
\n #content_views.markdown_views > .toc + p:empty + h2,
\n #content_views.markdown_views > .toc + p:empty + h3,
\n #content_views.markdown_views > .toc + p:empty + h4 {
\n margin-top: 0 !important;
\n }<\/p>\n

\u6982\u8ff0<\/h2>\n

GPU \u5185\u5b58\u6a21\u578b\u63cf\u8ff0\u7684\u662f：\u6570\u636e\u5b58\u5728\u54ea\u91cc\u3001\u79bb\u8ba1\u7b97\u5355\u5143（SM）\u6709\u591a\u8fdc\u3001\u8bbf\u95ee\u6709\u591a\u5feb\u3001\u8c01\u6765\u7ba1\u7406\u3002<\/p>\n

\u6838\u5fc3\u601d\u60f3\u662f\u5b58\u50a8\u5c42\u6b21\u7ed3\u6784（Memory Hierarchy）：<\/p>\n

\u8d8a\u9760\u8fd1 SM（\u8ba1\u7b97\u6838\u5fc3） \u2192 \u8d8a\u5feb\u3001\u8d8a\u5c0f\u3001\u8d8a\u8d35
\n\u8d8a\u8fdc\u79bb SM \u2192 \u8d8a\u6162\u3001\u8d8a\u5927\u3001\u8d8a\u4fbf\u5b9c<\/p>\n

A100 \u7684\u56db\u5c42\u7ed3\u6784：
\n\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\"<\/p>\n

\u5c0f\u7ed3: \u5bc4\u5b58\u5668 1 \u5468\u671f，\u5171\u4eab\u5185\u5b58 33 \u5468\u671f，L2 200 \u5468\u671f，\u5168\u5c40\u5185\u5b58 290 \u5468\u671f\u3002\u4ece\u5171\u4eab\u5185\u5b58\u5230\u5168\u5c40\u5185\u5b58，\u5ef6\u8fdf\u5dee\u4e86\u8fd1 9 \u500d\u3002<\/p>\n

\u5982\u679c\u8ba1\u7b97\u5355\u5143\u7b49\u5168\u5c40\u5185\u5b58，\u5927\u91cf\u65f6\u95f4\u5728\u7a7a\u8f6c\u3002<\/p>\n

\u56db\u5c42\u5b58\u50a8\u7684\u4f5c\u7528\u4e0e\u7f16\u7a0b\u63a7\u5236<\/h2>\n

\u5168\u5c40\u5185\u5b58（Global Memory）<\/h3>\n\n\u7279\u6027\u53c2\u6570<\/tr>\n\n\n\n\n\n\n
\u4f4d\u7f6e<\/td>\nGPU \u82af\u7247\u5916 HBM \u663e\u5b58<\/td>\n<\/tr>\n
\u5bb9\u91cf<\/td>\nA100 80GB<\/td>\n<\/tr>\n
\u5e26\u5bbd<\/td>\n\u7ea6 2 TB\/s<\/td>\n<\/tr>\n
\u5ef6\u8fdf<\/td>\n\u7ea6 290 \u5468\u671f<\/td>\n<\/tr>\n
\u7f16\u7a0b\u63a7\u5236<\/td>\n\u624b\u52a8 cudaMalloc，\u6240\u6709\u7ebf\u7a0b\u53ef\u89c1<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4f5c\u7528： \u5b58\u653e\u6a21\u578b\u6743\u91cd\u3001\u6fc0\u6d3b\u503c\u3001\u68af\u5ea6\u3001\u8bad\u7ec3\u6570\u636e\u3001\u4e2d\u95f4\u7ed3\u679c\u3001\u6700\u7ec8\u8f93\u51fa\u3002\u662f GPU \u7684\u201c\u5927\u4ed3\u5e93\u201d，\u5bb9\u91cf\u5927\u4f46\u901f\u5ea6\u6162\u3002<\/p>\n

\u7f16\u7a0b\u63a7\u5236： \u9700\u8981\u624b\u52a8\u5206\u914d\u3001\u624b\u52a8\u62f7\u8d1d（CPU\u2192GPU \u901a\u8fc7 PCIe）\u3002\u6240\u6709\u7ebf\u7a0b\u90fd\u80fd\u8bbf\u95ee，\u4f46\u6bcf\u6b21\u8bbf\u95ee\u90fd\u8981\u4ed8\u51fa\u9ad8\u5ef6\u8fdf\u3002<\/p>\n

L2 \u7f13\u5b58<\/h3>\n\n\u7279\u6027\u53c2\u6570<\/tr>\n\n\n\n\n\n\n
\u4f4d\u7f6e<\/td>\nGPU \u82af\u7247\u5185，\u6240\u6709 SM \u5171\u4eab<\/td>\n<\/tr>\n
\u5bb9\u91cf<\/td>\n40MB (A100)<\/td>\n<\/tr>\n
\u5e26\u5bbd<\/td>\n\u7ea6 5 TB\/s<\/td>\n<\/tr>\n
\u5ef6\u8fdf<\/td>\n\u7ea6 200 \u5468\u671f<\/td>\n<\/tr>\n
\u7f16\u7a0b\u63a7\u5236<\/td>\n\u786c\u4ef6\u81ea\u52a8\u7ba1\u7406，\u4e0d\u53ef\u624b\u52a8\u63a7\u5236<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

\u4f5c\u7528：<\/p>\n

    \n
  • \u7f13\u5b58\u5168\u5c40\u5185\u5b58\u7684\u70ed\u70b9\u6570\u636e（\u5982\u9891\u7e41\u8bbf\u95ee\u7684\u6743\u91cd），\u907f\u514d\u6bcf\u6b21\u90fd\u8bbf\u95ee HBM；<\/li>\n
  • \u6240\u6709 SM \u4e0e HBM \u4e4b\u95f4\u7684\u6570\u636e\u901a\u4fe1\u90fd\u5fc5\u987b\u7ecf\u8fc7 L2，\u662f GPU \u7684\u201c\u6570\u636e\u603b\u67a2\u7ebd\u201d；<\/li>\n
  • \u4e0d\u540c SM \u4e0a\u7684\u7ebf\u7a0b\u53ef\u4ee5\u901a\u8fc7 L2 \u9ad8\u6548\u5171\u4eab\u6570\u636e，\u4fdd\u8bc1\u6570\u636e\u4e00\u81f4\u6027\u3002<\/li>\n<\/ul>\n

    \u7f16\u7a0b\u63a7\u5236： \u5b8c\u5168\u81ea\u52a8，\u7a0b\u5e8f\u5458\u65e0\u6cd5\u663e\u5f0f\u6307\u5b9a\u201c\u628a\u67d0\u6570\u636e\u653e L2\u201d\u3002\u4f46\u53ef\u4ee5\u901a\u8fc7\u8bbf\u95ee\u6a21\u5f0f\u5f71\u54cd L2 \u547d\u4e2d\u7387\u3002<\/p>\n

    L1 \u7f13\u5b58 \/ \u5171\u4eab\u5185\u5b58<\/h3>\n\n\u7279\u6027\u53c2\u6570<\/tr>\n\n\n\n\n\n
    \u4f4d\u7f6e<\/td>\n\u6bcf\u4e2a SM \u5185\u90e8<\/td>\n<\/tr>\n
    \u5bb9\u91cf<\/td>\n192KB\/SM<\/td>\n<\/tr>\n
    \u5ef6\u8fdf<\/td>\n\u7ea6 33 \u5468\u671f<\/td>\n<\/tr>\n
    \u7f16\u7a0b\u63a7\u5236<\/td>\n\u5171\u4eab\u5185\u5b58\u624b\u52a8 __shared__；L1 \u81ea\u52a8<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u4f5c\u7528：<\/p>\n

      \n
    • \u5171\u4eab\u5185\u5b58： Block \u5185\u7ebf\u7a0b\u534f\u4f5c\u7684\u201c\u5c0f\u4ed3\u5e93\u201d，\u7528\u4e8e\u4ea4\u6362\u6570\u636e（\u5982\u77e9\u9635\u4e58\u6cd5\u7684\u5206\u5757\u6570\u636e Tiling）；<\/li>\n
    • L1 \u7f13\u5b58： \u4e0d\u624b\u52a8\u7528\u5171\u4eab\u5185\u5b58\u65f6，\u81ea\u52a8\u7f13\u5b58\u5168\u5c40\u5185\u5b58\u6570\u636e\u3002<\/li>\n<\/ul>\n

      \u7f16\u7a0b\u63a7\u5236： \u5171\u4eab\u5185\u5b58\u5b8c\u5168\u624b\u52a8\u3002\u7a0b\u5e8f\u5458\u7528 __shared__ \u58f0\u660e，\u7528 __syncthreads() \u540c\u6b65\u3002\u8fd9\u662f GPU \u6027\u80fd\u4f18\u5316\u7684\u6838\u5fc3\u624b\u6bb5\u3002<\/p>\n

      \u5bc4\u5b58\u5668\u6587\u4ef6<\/h3>\n\n\u7279\u6027\u53c2\u6570<\/tr>\n\n\n\n\n\n\n
      \u4f4d\u7f6e<\/td>\nSM \u5185，\u6bcf\u4e2a CUDA \u6838\u5fc3\u65c1<\/td>\n<\/tr>\n
      \u5bb9\u91cf<\/td>\n256KB\/SM<\/td>\n<\/tr>\n
      \u5e26\u5bbd<\/td>\n\u7ea6 10 TB\/s（\u7406\u8bba）<\/td>\n<\/tr>\n
      \u5ef6\u8fdf<\/td>\n1 \u5468\u671f（\u96f6\u5f00\u9500）<\/td>\n<\/tr>\n
      \u7f16\u7a0b\u63a7\u5236<\/td>\n\u7f16\u8bd1\u5668\u81ea\u52a8\u5206\u914d，\u7ebf\u7a0b\u79c1\u6709<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

      \u4f5c\u7528： \u5b58\u50a8\u7ebf\u7a0b\u7684\u5c40\u90e8\u53d8\u91cf\u3001\u4e34\u65f6\u7ed3\u679c\u3002\u6bcf\u4e2a\u7ebf\u7a0b\u6700\u591a 255 \u4e2a\u5bc4\u5b58\u5668\u3002\u901f\u5ea6\u6781\u5feb，\u4f46\u5bb9\u91cf\u6709\u9650\u3002<\/p>\n

      \u7f16\u7a0b\u63a7\u5236： \u5b8c\u5168\u81ea\u52a8，\u7f16\u8bd1\u5668\u51b3\u5b9a\u53d8\u91cf\u653e\u5bc4\u5b58\u5668\u8fd8\u662f\u6ea2\u51fa\u5230\u672c\u5730\u5185\u5b58\u3002\u7a0b\u5e8f\u5458\u53ef\u4ee5\u901a\u8fc7\u51cf\u5c11\u53d8\u91cf\u3001\u7b80\u5316\u4ee3\u7801\u6765\u964d\u4f4e\u5bc4\u5b58\u5668\u7528\u91cf，\u4ece\u800c\u8ba9 SM \u9a7b\u7559\u66f4\u591a Warp\u3002<\/p>\n

      \u77e9\u9635\u4e58\u6cd5\u5206\u5757，\u5c55\u793a\u56db\u5c42\u5b58\u50a8\u7684\u5a01\u529b<\/h2>\n

      \u95ee\u9898\u8bbe\u5b9a<\/h3>\n

      \u8ba1\u7b97 C=A\u00d7BC = A \\\\times B<\/span><\/span>C<\/span><\/span>=<\/span><\/span><\/span><\/span>A<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>B<\/span><\/span><\/span><\/span><\/span>，\u5176\u4e2d AA<\/span><\/span>A<\/span><\/span><\/span><\/span><\/span>\u3001BB<\/span><\/span>B<\/span><\/span><\/span><\/span><\/span> \u662f N\u00d7NN \\\\times N<\/span><\/span>N<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>N<\/span><\/span><\/span><\/span><\/span> \u77e9\u9635，N=1024N = 1024<\/span><\/span>N<\/span><\/span>=<\/span><\/span><\/span><\/span>1024<\/span><\/span><\/span><\/span><\/span>\u3002<\/p>\n

      \u6bcf\u4e2a\u8f93\u51fa\u5143\u7d20 C[i][j]C[i][j]<\/span><\/span>C<\/span>[<\/span>i<\/span>]<\/span>[<\/span>j<\/span>]<\/span><\/span><\/span><\/span><\/span> \u9700\u8981：<\/p>\n

      C[i][j]=\u2211k=0N\u22121A[i][k]\u00d7B[k][j]
      \nC[i][j] = \\\\sum_{k=0}^{N-1} A[i][k] \\\\times B[k][j]
      \n<\/span><\/span>C<\/span>[<\/span>i<\/span>]<\/span>[<\/span>j<\/span>]<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span>k<\/span>=<\/span>0<\/span><\/span><\/span><\/span><\/span>\u2211<\/span><\/span><\/span><\/span>N<\/span>\u2212<\/span>1<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>A<\/span>[<\/span>i<\/span>]<\/span>[<\/span>k<\/span>]<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>B<\/span>[<\/span>k<\/span>]<\/span>[<\/span>j<\/span>]<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

      \u5171 NN<\/span><\/span>N<\/span><\/span><\/span><\/span><\/span> \u6b21\u4e58\u52a0\u3002\u603b\u8ba1\u7b97\u91cf：<\/p>\n

      N3=10243\u22481.07\u00d7109\u00a0\u6b21\u4e58\u52a0
      \nN^3 = 1024^3 \\\\approx 1.07 \\\\times 10^9 \\\\text{ \u6b21\u4e58\u52a0}
      \n<\/span><\/span>N<\/span><\/span>3<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>102<\/span>4<\/span><\/span>3<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>1.07<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span>\u6b21\u4e58\u52a0<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

      \u65b9\u6848\u4e00：\u4e0d\u5206\u5757，\u76f4\u63a5\u4ece\u5168\u5c40\u5185\u5b58\u8bfb<\/h3>\n

      \u6bcf\u4e2a\u7ebf\u7a0b\u8ba1\u7b97\u4e00\u4e2a C[i][j]C[i][j]<\/span><\/span>C<\/span>[<\/span>i<\/span>]<\/span>[<\/span>j<\/span>]<\/span><\/span><\/span><\/span><\/span>，\u5faa\u73af kk<\/span><\/span>k<\/span><\/span><\/span><\/span><\/span> \u4ece 0 \u5230 1023：<\/p>\n

      for (int k = 0; k < N; k++) {
      \n C[i][j] += A[i][k] * B[k][j]; \/\/ \u6bcf\u6b21\u4ece\u5168\u5c40\u5185\u5b58\u8bfb A \u548c B
      \n}<\/p>\n

      \u5168\u5c40\u5185\u5b58\u8bbf\u95ee\u6b21\u6570：<\/p>\n

        \n
      • \u6bcf\u4e2a\u7ebf\u7a0b\u8bfb A[i][k]A[i][k]<\/span><\/span>A<\/span>[<\/span>i<\/span>]<\/span>[<\/span>k<\/span>]<\/span><\/span><\/span><\/span><\/span> \u5171 NN<\/span><\/span>N<\/span><\/span><\/span><\/span><\/span> \u6b21，\u8bfb B[k][j]B[k][j]<\/span><\/span>B<\/span>[<\/span>k<\/span>]<\/span>[<\/span>j<\/span>]<\/span><\/span><\/span><\/span><\/span> \u5171 NN<\/span><\/span>N<\/span><\/span><\/span><\/span><\/span> \u6b21；<\/li>\n
      • \u603b\u7ebf\u7a0b\u6570 N2=10242\u22481.05\u00d7106N^2 = 1024^2 \\\\approx 1.05 \\\\times 10^6<\/span><\/span>N<\/span><\/span>2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>102<\/span>4<\/span><\/span>2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>1.05<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>6<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>；<\/li>\n
      • \u603b\u8bfb\u53d6\u6b21\u6570：<\/li>\n<\/ul>\n

        2\u00d7N3=2\u00d71.07\u00d7109\u22482.14\u00d7109\u00a0\u6b21
        \n2 \\\\times N^3 = 2 \\\\times 1.07 \\\\times 10^9 \\\\approx 2.14 \\\\times 10^9 \\\\text{ \u6b21}
        \n<\/span><\/span>2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>N<\/span><\/span>3<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1.07<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>2.14<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span>\u6b21<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

        \u6bcf\u6b21\u8bbf\u95ee\u5ef6\u8fdf\u7ea6 290 \u5468\u671f\u3002\u5373\u4f7f\u6709 L2 \u7f13\u5b58，\u5927\u91cf\u91cd\u590d\u8bfb\u53d6\u4e5f\u4f1a\u9020\u6210\u4e25\u91cd\u74f6\u9888\u3002<\/p>\n

        \u4f30\u7b97\u65f6\u95f4（\u4e0d\u8003\u8651\u7f13\u5b58\u547d\u4e2d）：<\/p>\n

        2.14\u00d7109\u00d7290\u00a0\u5468\u671f\u22486.2\u00d71011\u00a0\u5468\u671f
        \n2.14 \\\\times 10^9 \\\\times 290 \\\\text{ \u5468\u671f} \\\\approx 6.2 \\\\times 10^{11} \\\\text{ \u5468\u671f}
        \n<\/span><\/span>2.14<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>290<\/span>\u00a0<\/span>\u5468\u671f<\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>6.2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>11<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span>\u5468\u671f<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

        A100 \u7ea6 1.4 GHz，\u65f6\u95f4\u7ea6：<\/p>\n

        6.2\u00d71011\/1.4\u00d7109\u2248443\u00a0\u79d2
        \n6.2 \\\\times 10^{11} \/ 1.4 \\\\times 10^9 \\\\approx 443 \\\\text{ \u79d2}
        \n<\/span><\/span>6.2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>11<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\/1.4<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>443<\/span>\u00a0<\/span>\u79d2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

        \u8fd9\u8fd8\u53ea\u662f\u5185\u5b58\u8bbf\u95ee，\u8ba1\u7b97\u672c\u8eab\u8fdc\u5c0f\u4e8e\u8fd9\u4e2a\u6570\u3002<\/p>\n

        \u65b9\u6848\u4e8c：\u5206\u5757\u52a0\u8f7d\u5230\u5171\u4eab\u5185\u5b58（Tiling）<\/h3>\n

        \u628a\u77e9\u9635\u5207\u6210 T\u00d7TT \\\\times T<\/span><\/span>T<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>T<\/span><\/span><\/span><\/span><\/span> \u7684\u5c0f\u5757，T=32T = 32<\/span><\/span>T<\/span><\/span>=<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span>\u3002\u6bcf\u4e2a Block \u8d1f\u8d23\u8ba1\u7b97 C \u7684\u4e00\u4e2a 32\u00d73232 \\\\times 32<\/span><\/span>32<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span> \u5757\u3002<\/p>\n

        \u6bcf\u4e2a Block \u7684\u7ebf\u7a0b\u534f\u4f5c：<\/p>\n

      • \u628a A \u7684\u4e00\u4e2a 32\u00d73232 \\\\times 32<\/span><\/span>32<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span> \u5757\u548c B \u7684\u4e00\u4e2a 32\u00d73232 \\\\times 32<\/span><\/span>32<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span> \u5757\u52a0\u8f7d\u5230\u5171\u4eab\u5185\u5b58；<\/li>\n
      • \u7528\u5171\u4eab\u5185\u5b58\u505a\u4e58\u52a0；<\/li>\n
      • \u6cbf k \u65b9\u5411\u6ed1\u52a8，\u91cd\u590d N\/T=32N\/T = 32<\/span><\/span>N<\/span>\/<\/span>T<\/span><\/span>=<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span> \u6b21\u3002<\/li>\n

        __shared__ float As[32][32];
        \n__shared__ float Bs[32][32];<\/p>\n

        for (int t = 0; t < N\/32; t++) {
        \n \/\/ \u534f\u4f5c\u52a0\u8f7d A \u548c B \u7684\u5757\u5230\u5171\u4eab\u5185\u5b58
        \n As[ty][tx] = A[i][t*32 + tx];
        \n Bs[ty][tx] = B[t*32 + ty][j];
        \n __syncthreads();<\/p>\n

        \/\/ \u7528\u5171\u4eab\u5185\u5b58\u505a 32 \u6b21\u4e58\u52a0
        \n for (int k = 0; k < 32; k++) {
        \n C[i][j] += As[ty][k] * Bs[k][tx];
        \n }
        \n __syncthreads();
        \n}<\/p>\n

        \u5168\u5c40\u5185\u5b58\u8bbf\u95ee\u6b21\u6570：<\/p>\n

          \n
        • \u6bcf\u4e2a Block \u52a0\u8f7d A \u5757\u548c B \u5757，\u6bcf\u6b21 32\u00d732 \u4e2a\u5143\u7d20；<\/li>\n
        • \u5171 N\/T = 32 \u6b21\u6ed1\u52a8；<\/li>\n
        • \u6bcf\u4e2a Block \u5168\u5c40\u8bfb\u53d6：<\/li>\n<\/ul>\n

          2\u00d732\u00d732\u00d732=2\u00d732768=65536\u00a0\u6b21
          \n2 \\\\times 32 \\\\times 32 \\\\times 32 = 2 \\\\times 32768 = 65536 \\\\text{ \u6b21}
          \n<\/span><\/span>2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32<\/span><\/span>=<\/span><\/span><\/span><\/span>2<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>32768<\/span><\/span>=<\/span><\/span><\/span><\/span>65536<\/span>\u00a0<\/span>\u6b21<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

            \n
          • Block \u603b\u6570：<\/li>\n<\/ul>\n

            (N\/32)2=322=1024
            \n(N\/32)^2 = 32^2 = 1024
            \n<\/span><\/span>(<\/span>N<\/span>\/32<\/span>)<\/span><\/span>2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>3<\/span>2<\/span><\/span>2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>1024<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

              \n
            • \u603b\u5168\u5c40\u8bfb\u53d6：<\/li>\n<\/ul>\n

              1024\u00d765536\u22486.7\u00d7107\u00a0\u6b21
              \n1024 \\\\times 65536 \\\\approx 6.7 \\\\times 10^7 \\\\text{ \u6b21}
              \n<\/span><\/span>1024<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>65536<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>6.7<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>7<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span>\u6b21<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

              \u5bf9\u6bd4\u65b9\u6848\u4e00：<\/p>\n

              2.14\u00d71096.7\u00d7107\u224832
              \n\\\\frac{2.14 \\\\times 10^9}{6.7 \\\\times 10^7} \\\\approx 32
              \n<\/span><\/span><\/span><\/span>6.7<\/span><\/span>\u00d7<\/span><\/span>1<\/span>0<\/span><\/span>7<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>2.14<\/span><\/span>\u00d7<\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>32<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

              \u5168\u5c40\u5185\u5b58\u8bbf\u95ee\u51cf\u5c11\u4e86 32 \u500d\u3002<\/p>\n

              \u5171\u4eab\u5185\u5b58\u8bbf\u95ee\u6b21\u6570：<\/p>\n

              \u6bcf\u4e2a\u7ebf\u7a0b\u505a NN<\/span><\/span>N<\/span><\/span><\/span><\/span><\/span> \u6b21\u4e58\u52a0，\u6bcf\u6b21\u8bfb\u5171\u4eab\u5185\u5b58：<\/p>\n

              N3=1.07\u00d7109\u00a0\u6b21\u5171\u4eab\u5185\u5b58\u8bfb\u53d6
              \nN^3 = 1.07 \\\\times 10^9 \\\\text{ \u6b21\u5171\u4eab\u5185\u5b58\u8bfb\u53d6}
              \n<\/span><\/span>N<\/span><\/span>3<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>1.07<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00a0<\/span>\u6b21\u5171\u4eab\u5185\u5b58\u8bfb\u53d6<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

              \u5171\u4eab\u5185\u5b58\u5ef6\u8fdf 33 \u5468\u671f，\u8fdc\u4f4e\u4e8e\u5168\u5c40\u5185\u5b58 290 \u5468\u671f\u3002<\/p>\n

              \u4f30\u7b97\u65f6\u95f4：<\/p>\n

                \n
              • \u5168\u5c40\u5185\u5b58：6.7\u00d7107\u00d7290\u22481.94\u00d710106.7 \\\\times 10^7 \\\\times 290 \\\\approx 1.94 \\\\times 10^{10}<\/span><\/span>6.7<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>7<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>290<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>1.94<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>10<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> \u5468\u671f；<\/li>\n
              • \u5171\u4eab\u5185\u5b58：1.07\u00d7109\u00d733\u22483.53\u00d710101.07 \\\\times 10^9 \\\\times 33 \\\\approx 3.53 \\\\times 10^{10}<\/span><\/span>1.07<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>33<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>3.53<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>10<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> \u5468\u671f；<\/li>\n
              • \u4f46\u5171\u4eab\u5185\u5b58\u8bbf\u95ee\u53ef\u4ee5\u6d41\u6c34\u7ebf\u5316，\u4e14 Warp \u5207\u6362\u80fd\u9690\u85cf\u5ef6\u8fdf\u3002<\/li>\n<\/ul>\n

                \u603b\u65f6\u95f4\u7ea6：<\/p>\n

                (1.94+3.53)\u00d71010\/1.4\u00d7109\u224839\u00a0\u79d2
                \n(1.94 + 3.53) \\\\times 10^{10} \/ 1.4 \\\\times 10^9 \\\\approx 39 \\\\text{ \u79d2}
                \n<\/span><\/span>(<\/span>1.94<\/span><\/span>+<\/span><\/span><\/span><\/span>3.53<\/span>)<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>10<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\/1.4<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>1<\/span>0<\/span><\/span>9<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>39<\/span>\u00a0<\/span>\u79d2<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

                \u5bf9\u6bd4\u65b9\u6848\u4e00 443 \u79d2，\u52a0\u901f\u7ea6 11 \u500d\u3002\u8fd9\u5c31\u662f\u5171\u4eab\u5185\u5b58\u5206\u5757\u7684\u4ef7\u503c\u3002<\/p>\n

                \u65b9\u6848\u4e09：\u5bc4\u5b58\u5668\u8fdb\u4e00\u6b65\u4f18\u5316<\/h3>\n

                \u6bcf\u4e2a\u7ebf\u7a0b\u8ba1\u7b97 C \u7684\u4e00\u4e2a 4\u00d74 \u5c0f\u5757（\u800c\u4e0d\u662f\u5355\u4e2a\u5143\u7d20），\u628a A\u3001B \u7684\u4e2d\u95f4\u7ed3\u679c\u653e\u5728\u5bc4\u5b58\u5668：<\/p>\n

                float c[4][4] = {0}; \/\/ 16 \u4e2a\u5bc4\u5b58\u5668
                \nfloat a[4], b[4]; \/\/ 8 \u4e2a\u5bc4\u5b58\u5668<\/p>\n

                \u6bcf\u4e2a\u7ebf\u7a0b\u7528 24 \u4e2a\u5bc4\u5b58\u5668，\u5171\u4eab\u5185\u5b58\u8bfb\u53d6\u6b21\u6570\u51cf\u5c11：<\/p>\n

                  \n
                • \u539f\u6765\u6bcf\u4e2a\u7ebf\u7a0b\u8bfb 2N \u6b21\u5171\u4eab\u5185\u5b58；<\/li>\n
                • \u73b0\u5728\u6bcf\u4e2a\u7ebf\u7a0b\u8ba1\u7b97 16 \u4e2a\u8f93\u51fa，\u5171\u4eab\u5185\u5b58\u8bfb\u53d6\u5206\u644a\u5230 16 \u4e2a\u8f93\u51fa\u4e0a\u3002<\/li>\n<\/ul>\n

                  \u5171\u4eab\u5185\u5b58\u8bbf\u95ee\u6b21\u6570\u4ece N^3 \u964d\u5230\u7ea6 N^3\/4，\u8fdb\u4e00\u6b65\u51cf\u5c11\u3002<\/p>\n

                  \u5bc4\u5b58\u5668\u5ef6\u8fdf 1 \u5468\u671f，\u51e0\u4e4e\u96f6\u5f00\u9500\u3002\u4f46\u5bc4\u5b58\u5668\u7528\u91cf\u589e\u52a0\u4f1a\u9650\u5236 SM \u9a7b\u7559\u7684 Warp \u6570：<\/p>\n

                    \n
                  • \u6bcf\u4e2a\u7ebf\u7a0b 24 \u4e2a\u5bc4\u5b58\u5668，SM \u6709 65536 \u4e2a\u5bc4\u5b58\u5668，\u6700\u591a\u9a7b\u7559 65536\/(24 \u00d7 32) \u2248 85 \u4e2a Warp；<\/li>\n
                  • \u5b9e\u9645\u53d7 64 \u4e2a Warp \u69fd\u4f4d\u9650\u5236，\u4ecd\u80fd\u6ee1\u8d1f\u8377\u3002<\/li>\n<\/ul>\n

                    \u5982\u679c\u6bcf\u4e2a\u7ebf\u7a0b\u7528 128 \u4e2a\u5bc4\u5b58\u5668，\u6700\u591a\u9a7b\u7559 65536\/(128 \u00d7 32) = 16 \u4e2a Warp，\u5e76\u884c\u5ea6\u4e0b\u964d，\u5ef6\u8fdf\u9690\u85cf\u80fd\u529b\u53d8\u5dee\u3002<\/p>\n

                    \u4e3a\u4ec0\u4e48 GPU \u5185\u5b58\u8981\u5206\u8fd9\u4e48\u591a\u5c42？<\/h2>\n

                    \u7269\u7406\u539f\u56e0：\u8ddd\u79bb\u51b3\u5b9a\u5ef6\u8fdf<\/h3>\n

                    \u7535\u4fe1\u53f7\u5728\u5bfc\u7ebf\u4e2d\u4f20\u64ad\u9700\u8981\u65f6\u95f4，\u7269\u7406\u8ddd\u79bb\u8d8a\u77ed，\u5ef6\u8fdf\u8d8a\u4f4e：<\/p>\n

                      \n
                    • \u5bc4\u5b58\u5668\u5728 CUDA \u6838\u5fc3\u65c1，\u8ddd\u79bb\u6700\u8fd1，1 \u5468\u671f；<\/li>\n
                    • \u5171\u4eab\u5185\u5b58\u5728 SM \u5185，33 \u5468\u671f；<\/li>\n
                    • L2 \u5728\u82af\u7247\u5185\u4f46\u8de8 SM，200 \u5468\u671f；<\/li>\n
                    • \u5168\u5c40\u5185\u5b58\u5728\u82af\u7247\u5916 HBM，290 \u5468\u671f\u3002<\/li>\n<\/ul>\n

                      \u5bb9\u91cf\u4e0e\u6210\u672c\u7684\u6743\u8861<\/h3>\n\n\u5c42\u7ea7\u5bb9\u91cf\u6210\u672c\u901f\u5ea6<\/tr>\n\n\n\n\n\n
                      \u5bc4\u5b58\u5668<\/td>\n256KB\/SM<\/td>\n\u6781\u8d35<\/td>\n1 \u5468\u671f<\/td>\n<\/tr>\n
                      \u5171\u4eab\u5185\u5b58<\/td>\n192KB\/SM<\/td>\n\u8d35<\/td>\n33 \u5468\u671f<\/td>\n<\/tr>\n
                      L2<\/td>\n40MB<\/td>\n\u4e2d<\/td>\n200 \u5468\u671f<\/td>\n<\/tr>\n
                      \u5168\u5c40\u5185\u5b58<\/td>\n80GB<\/td>\n\u76f8\u5bf9\u4fbf\u5b9c<\/td>\n290 \u5468\u671f<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                      \u82af\u7247\u9762\u79ef\u6709\u9650，\u4e0d\u53ef\u80fd\u628a 80GB \u90fd\u505a\u6210\u5bc4\u5b58\u5668\u3002\u53ea\u80fd\u5206\u5c42：\u5c0f\u5bb9\u91cf\u9ad8\u901f\u5b58\u50a8\u9760\u8fd1\u8ba1\u7b97，\u5927\u5bb9\u91cf\u4f4e\u901f\u5b58\u50a8\u653e\u5916\u9762\u3002<\/p>\n

                      \u5c40\u90e8\u6027\u539f\u7406<\/h3>\n
                        \n
                      • \u65f6\u95f4\u5c40\u90e8\u6027：\u521a\u8bbf\u95ee\u7684\u6570\u636e\u5f88\u53ef\u80fd\u518d\u6b21\u8bbf\u95ee（\u5982\u5faa\u73af\u4e2d\u7684\u6743\u91cd）\u2192 L2 \u7f13\u5b58；<\/li>\n
                      • \u7a7a\u95f4\u5c40\u90e8\u6027：\u76f8\u90bb\u6570\u636e\u5f88\u53ef\u80fd\u4e00\u8d77\u8bbf\u95ee（\u5982\u77e9\u9635\u540c\u884c\u5143\u7d20）\u2192 \u5171\u4eab\u5185\u5b58\u5206\u5757；<\/li>\n
                      • \u5e7f\u64ad\u7279\u6027：Warp \u5185 32 \u7ebf\u7a0b\u8bfb\u540c\u4e00\u5e38\u91cf \u2192 \u5e38\u91cf\u5185\u5b58\u4e00\u6b21\u8bfb\u53d6\u670d\u52a1 32 \u7ebf\u7a0b\u3002<\/li>\n<\/ul>\n

                        \u6570\u503c\u76f4\u89c9：\u5ef6\u8fdf\u9690\u85cf<\/h3>\n

                        \u8bbe\u4e00\u4e2a Warp \u8bbf\u95ee\u5168\u5c40\u5185\u5b58\u9700\u8981 290 \u5468\u671f，\u8ba1\u7b97\u9700\u8981 4 \u5468\u671f\u3002<\/p>\n

                        \u5982\u679c SM \u53ea\u9a7b\u7559 1 \u4e2a Warp：<\/p>\n

                        \u5229\u7528\u7387=44+290\u22481.4%\u5229\u7528\u7387 = \\\\frac{4}{4 + 290} \\\\approx 1.4\\\\%<\/span><\/span>\u5229\u7528\u7387<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span><\/span>4<\/span><\/span>+<\/span><\/span>290<\/span><\/span><\/span><\/span><\/span><\/span><\/span>4<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>1.4%<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

                        \u5982\u679c\u9a7b\u7559 64 \u4e2a Warp，\u8f6e\u6d41\u4e0a\u8ba1\u7b97\u5355\u5143：<\/p>\n

                        \u5229\u7528\u7387\u2248100%
                        \n\u5229\u7528\u7387 \\\\approx 100\\\\%
                        \n<\/span><\/span>\u5229\u7528\u7387<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>100%<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

                        \u6240\u4ee5 GPU \u7528\u201c\u5927\u91cf Warp \u5e76\u884c\u201d\u6765\u9690\u85cf\u9ad8\u5ef6\u8fdf，\u8fd9\u662f\u541e\u5410\u91cf\u4f18\u5316\u7684\u6838\u5fc3\u3002<\/p>\n

                        GPU \u5185\u5b58\u4e0e CPU \u5185\u5b58\u7684\u672c\u8d28\u533a\u522b<\/h2>\n\n\u7279\u6027GPU (A100)CPU (Xeon)<\/tr>\n\n\n\n\n\n\n
                        \u4e3b\u5b58\u5e26\u5bbd<\/td>\n\u7ea6 2 TB\/s<\/td>\n\u6570\u767e GB\/s<\/td>\n<\/tr>\n
                        \u7f13\u5b58\u63a7\u5236<\/td>\n\u5171\u4eab\u5185\u5b58\u624b\u52a8\u63a7\u5236<\/td>\n\u7f13\u5b58\u5b8c\u5168\u81ea\u52a8<\/td>\n<\/tr>\n
                        \u7ebf\u7a0b\u5bc4\u5b58\u5668<\/td>\n255 \u4e2a\/\u7ebf\u7a0b<\/td>\n16 \u4e2a\/\u7ebf\u7a0b（x86-64）<\/td>\n<\/tr>\n
                        \u5ef6\u8fdf\u5bb9\u5fcd<\/td>\n\u901a\u8fc7 Warp \u5207\u6362\u9690\u85cf\u5ef6\u8fdf<\/td>\n\u5c3d\u91cf\u964d\u4f4e\u5ef6\u8fdf<\/td>\n<\/tr>\n
                        \u5185\u5b58\u6a21\u578b<\/td>\n\u5171\u4eab\u5185\u5b58\u663e\u5f0f\u540c\u6b65<\/td>\n\u7f13\u5b58\u4e00\u81f4\u6027\u534f\u8bae<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                        \u672c\u8d28\u533a\u522b：<\/p>\n

                          \n
                        • CPU \u4e3a\u5ef6\u8fdf\u4f18\u5316：\u7528\u5927\u7f13\u5b58\u3001\u4e71\u5e8f\u6267\u884c\u3001\u5206\u652f\u9884\u6d4b，\u5c3d\u91cf\u8ba9\u5355\u6b21\u8bbf\u95ee\u5feb；<\/li>\n
                        • GPU \u4e3a\u541e\u5410\u91cf\u4f18\u5316：\u5bb9\u5fcd\u9ad8\u5ef6\u8fdf，\u7528\u6d77\u91cf Warp \u5e76\u884c\u9690\u85cf\u5ef6\u8fdf，\u8ffd\u6c42\u5355\u4f4d\u65f6\u95f4\u5904\u7406\u66f4\u591a\u6570\u636e\u3002<\/li>\n<\/ul>\n

                          \u6570\u503c\u4f8b\u5b50：CPU \u8bbf\u95ee\u4e00\u6b21\u5185\u5b58 100 \u5468\u671f，\u4f46\u7f13\u5b58\u547d\u4e2d\u7387 95%，\u5e73\u5747\u5ef6\u8fdf 0.95\u00d75+0.05\u00d7100\u22489.750.95 \\\\times 5 + 0.05 \\\\times 100 \\\\approx 9.75<\/span><\/span>0.95<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>5<\/span><\/span>+<\/span><\/span><\/span><\/span>0.05<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>100<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>9.75<\/span><\/span><\/span><\/span><\/span> \u5468\u671f\u3002<\/p>\n

                          GPU \u4e0d\u8ffd\u6c42\u5355\u6b21\u5feb，\u800c\u662f\u8ba9 64 \u4e2a Warp \u540c\u65f6\u8dd1，\u67d0\u4e2a Warp \u7b49\u5185\u5b58\u65f6\u5176\u4ed6 Warp \u7ee7\u7eed\u7b97\u3002<\/p>\n

                          \u603b\u7ed3<\/h2>\n\n\u5c42\u7ea7\u4f5c\u7528\u7f16\u7a0b\u63a7\u5236\u6570\u503c\u4f8b\u5b50\u4e2d\u7684\u89d2\u8272<\/tr>\n\n\n\n\n\n
                          \u5168\u5c40\u5185\u5b58<\/td>\n\u5b58\u6743\u91cd\u3001\u6570\u636e\u3001\u8f93\u51fa<\/td>\n\u624b\u52a8 cudaMalloc<\/td>\n\u4e0d\u5206\u5757\u65f6\u8bfb 21.4 \u4ebf\u6b21，\u5206\u5757\u540e\u8bfb 6700 \u4e07\u6b21<\/td>\n<\/tr>\n
                          L2 \u7f13\u5b58<\/td>\n\u7f13\u5b58\u70ed\u70b9\u3001\u8de8 SM \u5171\u4eab<\/td>\n\u81ea\u52a8<\/td>\n\u7f13\u5b58\u91cd\u590d\u8bbf\u95ee\u7684 A\u3001B \u5757<\/td>\n<\/tr>\n
                          \u5171\u4eab\u5185\u5b58<\/td>\nBlock \u5185\u534f\u4f5c\u3001\u5206\u5757<\/td>\n\u624b\u52a8 __shared__<\/td>\n\u77e9\u9635\u5206\u5757，\u5168\u5c40\u8bbf\u95ee\u51cf\u5c11 32 \u500d<\/td>\n<\/tr>\n
                          \u5bc4\u5b58\u5668<\/td>\n\u7ebf\u7a0b\u5c40\u90e8\u53d8\u91cf<\/td>\n\u7f16\u8bd1\u5668\u81ea\u52a8<\/td>\n\u6bcf\u7ebf\u7a0b 24 \u4e2a\u5bc4\u5b58\u5668，\u52a0\u901f\u8ba1\u7b97<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                          \u4e00\u53e5\u8bdd： GPU \u5185\u5b58\u6a21\u578b\u662f\u201c\u8fd1\u5feb\u5c0f\u3001\u8fdc\u6162\u5927\u201d\u7684\u56db\u5c42\u7ed3\u6784\u3002<\/p>\n

                          \u5bc4\u5b58\u5668 1 \u5468\u671f\u3001\u5171\u4eab\u5185\u5b58 33 \u5468\u671f\u3001L2 200 \u5468\u671f\u3001\u5168\u5c40\u5185\u5b58 290 \u5468\u671f\u3002\u77e9\u9635\u4e58\u6cd5\u4f8b\u5b50\u4e2d，\u4e0d\u5206\u5757\u76f4\u63a5\u8bfb\u5168\u5c40\u5185\u5b58\u7ea6 443 \u79d2，\u5206\u5757\u5230\u5171\u4eab\u5185\u5b58\u540e\u7ea6 39 \u79d2，\u52a0\u901f 11 \u500d\u3002GPU \u7528\u5206\u5c42\u5b58\u50a8 + \u6d77\u91cf Warp \u5e76\u884c\u6765\u9690\u85cf\u9ad8\u5ef6\u8fdf，\u8ffd\u6c42\u541e\u5410\u91cf；CPU \u7528\u5927\u7f13\u5b58\u548c\u590d\u6742\u63a7\u5236\u6765\u964d\u4f4e\u5ef6\u8fdf\u3002<\/p>\n

                          \u7406\u89e3\u8fd9\u4e2a\u5c42\u6b21\u7ed3\u6784，\u662f\u5199\u51fa\u9ad8\u6027\u80fd GPU \u4ee3\u7801\u7684\u5173\u952e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

                          \/* MD \/ \u5bcc\u6587\u672c\u4e2d\u7684 .toc\uff08\u542b\u535a\u5ba2\u56ed\u642c\u5bb6\u7b49\u5d4c\u5957\u7ed3\u6784\uff09\uff1b.toc-box \u5728\u4fa7\u680f\uff0c\u4e0d\u53d7\u5f71\u54cd *\/#content_views .toc,\/* \u7f16\u8f91\u5668\u5e38\u5728\u76ee\u5f55\u524d\u540e\u63d2\u5165\u7a7a p\uff08:empty \u4ecd\u5360 20px\uff09\uff0c\u4e00\u5e76\u53bb\u6389\u907f\u514d\u9876\u7a7a\u9699 *\/#content_views.markdown_views > p:empty:has(+ .toc),#content_views.markdown_views > .toc + p:empty,\/* \u5bcc\u6587\u672c\u65e7\u7248\u76ee\u5f55\u6807\u8bb0 *\/#content<\/p>\n","protected":false},"author":2,"featured_media":122991,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[99,101,841,292,188],"topic":[],"class_list":["post-122992","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-java","tag-spring","tag-transformer","tag-292","tag-188"],"yoast_head":"\nGPU \u5185\u5b58\u6a21\u578b\u6d45\u89e3 - 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