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；

As noted already, programmers are strongly encouraged to use appropriate synchronization
to avoid data races.
In the absence of data races, Go programs behave as if all the goroutines
were multiplexed onto a single processor.
This property is sometimes referred to as DRF-SC: data-race-free programs
execute in a sequentially consistent manner.
</p>

<p>
While programmers should write Go programs without data races,

Und da die meiste Ausführungszeit durch tatsächliche Arbeit (anstatt durch Warten) in Anspruch genommen wird und die Arbeit in einem Computer von einer <abbr title="Central Processing Unit – Zentrale Recheneinheit">CPU</abbr> erledigt wird, werden diese Probleme als „CPU-lastig“ („CPU bound“) bezeichnet.

---

King's crown on a crimson velvet cushion; and, last of all this
grand procession, came THE KING AND QUEEN OF HEARTS.

  Alice was rather doubtful whether she ought not to lie down on
her face like the three gardeners, but she could not remember
ever having heard of such a rule at processions; `and besides,
what would be the use of a procession,' thought she, `if people

- Improve PVC Protection Controller's scalability by batch-processing PVCs by namespace with lazy live pod listing. ([#125372](https://github.com/kubernetes/kubernetes/pull/125372), [@hungnguyen243](https://github.com/hungnguyen243)) [SIG Apps, Node, Storage and Testing]

    </magic>
  </mime-type>
  <mime-type type="application/x-hwp-v5">
    <_comment>Hangul Word Processor File v5</_comment>
    <sub-class-of type="application/x-tika-msoffice"/>
  </mime-type>
  <mime-type type="application/hwp+zip">
    <_comment>Hangul Word Processor File, zip based</_comment>
    <sub-class-of type="application/zip"/>
    <glob pattern="*.hwpx"/>
  </mime-type>

    accessible from workers. If the worker fails to read from the `work_dir`, it
    falls back to using RPC for dataset graph transfer.
*   Adds support for a new "distributed_epoch" processing mode. This processing
    mode distributes a dataset across all tf.data workers, instead of having
    each worker process the full dataset. See

				writeErrorResponse(ctx, w, apiErr, r.URL)
				return
			}
			reader = &b
			actualSize = n
		}

		// we have found the File part of the request we are done processing multipart-form
		break
	}

	if keyName, ok := formValues["Key"]; !ok {
		apiErr := errorCodes.ToAPIErr(ErrMalformedPOSTRequest)

이 시나리오에서, (당신을 포함한) 각각의 청소부들은 프로세서가 될 것이고, 각자의 역할을 수행합니다.

실행 시간의 대부분이 대기가 아닌 실제 작업에 소요되고, 컴퓨터에서 작업은 <abbr title="Central Processing Unit">CPU</abbr>에서 이루어지므로, 이러한 문제를 "CPU에 묶였"다고 합니다.

---

CPU에 묶인 연산에 관한 흔한 예시는 복잡한 수학 처리를 필요로 하는 경우입니다.

예를 들어:

* **오디오** 또는 **이미지** 처리.

                    getCanonicalPath(fileSystem.getPath(mavenHome)).toString());
        }
    }

    void cli(CliRequest cliRequest) throws Exception {
        //
        // Parsing errors can happen during the processing of the arguments and we prefer not having to check if
        // the logger is null and construct this so we can use an SLF4J logger everywhere.
        //
        slf4jLogger = new Slf4jStdoutLogger();