Bu senaryoda, temizlikçilerin her biri (siz dahil) birer işlemci olacak ve üzerine düşeni yapacaktır.

Yürütme süresinin çoğu (beklemek yerine) iş yapıldığından ve bilgisayardaki iş bir <abbr title="Central Processing Unit">CPU</abbr> tarafından yapıldığından, bu sorunlara "CPU bound" diyorlar".

---

CPU'ya bağlı işlemlerin yaygın örnekleri, karmaşık matematik işlemleri gerektiren işlerdir.

Örneğin:

	// Global cache of dead G's.
	gFree struct {
		lock    mutex
		stack   gList // Gs with stacks
		noStack gList // Gs without stacks
		n       int32
	}

	// Central cache of sudog structs.
	sudoglock  mutex
	sudogcache *sudog

	// Central pool of available defer structs.
	deferlock mutex
	deferpool *_defer

	// freem is the list of m's waiting to be freed when their

func TypeOf(a any) *Type {
	eface := *(*EmptyInterface)(unsafe.Pointer(&a))
	// Types are either static (for compiler-created types) or
	// heap-allocated but always reachable (for reflection-created
	// types, held in the central map). So there is no need to
	// escape types. noescape here help avoid unnecessary escape
	// of v.
	return (*Type)(NoEscape(unsafe.Pointer(eface.Type)))
}

func (t *Type) Kind() Kind { return t.Kind_ & KindMask }

 *   <li>These tests are "conformance tests", and do not attempt to test throughput, latency,
 *       scalability or other performance factors (see the separate "jtreg" tests for a set intended
 *       to check these for the most central aspects of functionality.) So, most tests use the
 *       smallest sensible numbers of threads, collection sizes, etc needed to check basic
 *       conformance.

👉 😐, 🔠 1️⃣ 🧹 (🔌 👆) 🔜 🕹, 🤸 👫 🍕 👨‍🏭.

&amp; 🏆 🛠️ 🕰 ✊ ☑ 👷 (↩️ ⌛), &amp; 👷 💻 ⌛ <abbr title="Central Processing Unit">💽</abbr>, 👫 🤙 👫 ⚠ "💽 🎁".

---

⚠ 🖼 💽 🔗 🛠️ 👜 👈 🚚 🏗 🧪 🏭.

🖼:

* **🎧** ⚖️ **🖼 🏭**.

E a maior parte do tempo de execução é tomada por trabalho (ao invés de ficar esperando), e o trabalho em um computador é feito pela <abbr title="Unidade de Processamento Central">CPU</abbr>, que podem gerar problemas que são chamados de "limite de CPU".

---

Exemplos comuns de limite de CPU são coisas que exigem processamento matemático complexo.

Por exemplo:

            such as method definitions and class definitions.
        </para>
    </section>

    <section>
        <title>Core types</title>
        <para>Listed below are some of the central types which are used in Gradle scripts:</para>
        <table>
            <title>Core types</title>
            <tr>
                <td>org.gradle.api.Project</td>
            </tr>
            <tr>

            <pgp value="CB3808E03CD602A6DC5B882552931F4B72B4F54C"/>
         </artifact>
      </component>
      <component group="net.rubygrapefruit" name="ansi-control-sequence-util" version="0.3">
         <artifact name="ansi-control-sequence-util-0.3.jar">
            <pgp value="5B131E826582CF79510DAA11CD3E539F208832D0"/>
         </artifact>
      </component>

And as most of the execution time is taken by actual work (instead of waiting), and the work in a computer is done by a <abbr title="Central Processing Unit">CPU</abbr>, they call these problems "CPU bound".

---

Common examples of CPU bound operations are things that require complex math processing.

For example:

无论是否轮流执行（并发），都需要相同的时间来完成，而你也会完成相同的工作量。

但在这种情况下，如果你能带上 8 名前收银员/厨师，现在是清洁工一起清扫，他们中的每一个人（加上你）都能占据房子的一个区域来清扫，你就可以在额外的帮助下并行的更快地完成所有工作。

在这个场景中，每个清洁工（包括您）都将是一个处理器，完成这个工作的一部分。

由于大多数执行时间是由实际工作（而不是等待）占用的，并且计算机中的工作是由 <abbr title="Central Processing Unit">CPU</abbr> 完成的，所以他们称这些问题为"CPU 密集型"。

---

CPU 密集型操作的常见示例是需要复杂的数学处理。

例如：

* **音频**或**图像**处理；
* **计算机视觉**: 一幅图像由数百万像素组成，每个像素有3种颜色值，处理通常需要同时对这些像素进行计算；