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序
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序
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第 0 章 &nbsp; 前言
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第 1 章 &nbsp; 初识算法
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第 2 章 &nbsp; 复杂度分析
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第 3 章 &nbsp; 数据结构
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第 4 章 &nbsp; 数组与链表
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第 5 章 &nbsp; 栈与队列
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第 6 章 &nbsp; 哈希表
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第 8 章 &nbsp; 堆
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第 9 章 &nbsp; 图
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第 11 章 &nbsp; 排序
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第 12 章 &nbsp; 分治
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第 13 章 &nbsp; 回溯
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第 14 章 &nbsp; 动态规划
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第 15 章 &nbsp; 贪心
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第 16 章 &nbsp; 附录
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参考文献
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<a href="../../chapter_paperbook/" class="md-nav__link ">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><!--! Font Awesome Free 6.5.1 by @fontawesome - https://fontawesome.com License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License) Copyright 2023 Fonticons, Inc.--><path d="M96 0C43 0 0 43 0 96v320c0 53 43 96 96 96h320c17.7 0 32-14.3 32-32s-14.3-32-32-32v-64c17.7 0 32-14.3 32-32V32c0-17.7-14.3-32-32-32H96zm0 384h256v64H96c-17.7 0-32-14.3-32-32s14.3-32 32-32zm32-240c0-8.8 7.2-16 16-16h192c8.8 0 16 7.2 16 16s-7.2 16-16 16H144c-8.8 0-16-7.2-16-16zm16 48h192c8.8 0 16 7.2 16 16s-7.2 16-16 16H144c-8.8 0-16-7.2-16-16s7.2-16 16-16z"/></svg>
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纸质书
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纸质书
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<p>在本章的前两节中，我们探讨了数组和链表这两种基础且重要的数据结构，它们分别代表了“连续存储”和“分散存储”两种物理结构。</p>
<p>实际上，<strong>物理结构在很大程度上决定了程序对内存和缓存的使用效率</strong>，进而影响算法程序的整体性能。</p>
<h2 id="441">4.4.1 &nbsp; 计算机存储设备<a class="headerlink" href="#441" title="Permanent link">&para;</a></h2>
<p>计算机中包括三种类型的存储设备：「硬盘 hard disk」、「内存 random-access memory, RAM」、「缓存 cache memory」。表 4-2 展示了它们在计算机系统中的不同角色和性能特点。</p>
<p>计算机中包括三种类型的存储设备：<u>硬盘（hard disk）</u>、<u>内存（random-access memory, RAM）</u>、<u>缓存（cache memory）</u>。表 4-2 展示了它们在计算机系统中的不同角色和性能特点。</p>
<p align="center"> 表 4-2 &nbsp; 计算机的存储设备 </p>
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<p>一方面，<strong>内存是有限的，且同一块内存不能被多个程序共享</strong>，因此我们希望数据结构能够尽可能高效地利用空间。数组的元素紧密排列，不需要额外的空间来存储链表节点间的引用（指针），因此空间效率更高。然而，数组需要一次性分配足够的连续内存空间，这可能导致内存浪费，数组扩容也需要额外的时间和空间成本。相比之下，链表以“节点”为单位进行动态内存分配和回收，提供了更大的灵活性。</p>
<p>另一方面，在程序运行时，<strong>随着反复申请与释放内存，空闲内存的碎片化程度会越来越高</strong>，从而导致内存的利用效率降低。数组由于其连续的存储方式，相对不容易导致内存碎片化。相反，链表的元素是分散存储的，在频繁的插入与删除操作中，更容易导致内存碎片化。</p>
<h2 id="443">4.4.3 &nbsp; 数据结构的缓存效率<a class="headerlink" href="#443" title="Permanent link">&para;</a></h2>
<p>缓存虽然在空间容量上远小于内存，但它比内存快得多，在程序执行速度上起着至关重要的作用。由于缓存的容量有限，只能存储一小部分频繁访问的数据，因此当 CPU 尝试访问的数据不在缓存中时，就会发生「缓存未命中 cache miss」，此时 CPU 不得不从速度较慢的内存中加载所需数据。</p>
<p>显然，<strong>“缓存未命中”越少，CPU 读写数据的效率就越高</strong>，程序性能也就越好。我们将 CPU 从缓存中成功获取数据的比例称为「缓存命中率 cache hit rate」，这个指标通常用来衡量缓存效率。</p>
<p>缓存虽然在空间容量上远小于内存，但它比内存快得多，在程序执行速度上起着至关重要的作用。由于缓存的容量有限，只能存储一小部分频繁访问的数据，因此当 CPU 尝试访问的数据不在缓存中时，就会发生<u>缓存未命中（cache miss）</u>，此时 CPU 不得不从速度较慢的内存中加载所需数据。</p>
<p>显然，<strong>“缓存未命中”越少，CPU 读写数据的效率就越高</strong>，程序性能也就越好。我们将 CPU 从缓存中成功获取数据的比例称为<u>缓存命中率（cache hit rate）</u>，这个指标通常用来衡量缓存效率。</p>
<p>为了尽可能达到更高的效率，缓存会采取以下数据加载机制。</p>
<ul>
<li><strong>缓存行</strong>：缓存不是单个字节地存储与加载数据，而是以缓存行为单位。相比于单个字节的传输，缓存行的传输形式更加高效。</li>
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