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docs/em/docs/async.md
👉 😐, 🔠 1️⃣ 🧹 (🔌 👆) 🔜 🕹, 🤸 👫 🍕 👨🏭. & 🏆 🛠️ 🕰 ✊ ☑ 👷 (↩️ ⌛), & 👷 💻 ⌛ <abbr title="Central Processing Unit">💽</abbr>, 👫 🤙 👫 ⚠ "💽 🎁". --- ⚠ 🖼 💽 🔗 🛠️ 👜 👈 🚚 🏗 🧪 🏭. 🖼: * **🎧** ⚖️ **🖼 🏭**.
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 18.7K bytes - Viewed (0) -
android/guava-tests/test/com/google/common/util/concurrent/JSR166TestCase.java
* <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.
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Jun 10 19:21:11 UTC 2024 - 37.7K bytes - Viewed (0) -
docs/fr/docs/async.md
Et comme la plupart du temps d'exécution est pris par du "vrai" travail (et non de l'attente), et que le travail dans un ordinateur est fait par un <abbr title="Central Processing Unit">CPU</abbr>, ce sont des problèmes dits "CPU bound". --- Des exemples communs d'opérations "CPU bounds" sont les procédés qui requièrent des traitements mathématiques complexes. Par exemple :
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sun Mar 31 23:52:53 UTC 2024 - 24K bytes - Viewed (0) -
docs/pt/docs/async.md
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:
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 22.2K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/userguide/authoring-builds/tasks/more_about_tasks.adoc
id("base") } ---- ===== [.multi-language-sample] ===== .app/build.gradle [source,groovy] ---- plugins { id('base') } ---- ===== ==== The `base` plugin adds central lifecycle tasks. Now when we run `./gradlew app:tasks`, we can see the `assemble` and `build` tasks are available: [source,text] ---- $ ./gradlew :app:tasks > Task :app:tasks
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Sat Mar 23 22:37:03 UTC 2024 - 28.5K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/dsl/dsl.xml
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 15:00:02 UTC 2024 - 34.7K bytes - Viewed (0) -
guava-tests/test/com/google/common/util/concurrent/JSR166TestCase.java
* <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.
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Thu Feb 22 17:15:24 UTC 2024 - 37.7K bytes - Viewed (0) -
docs/en/docs/async.md
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:
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Mon May 20 00:24:48 UTC 2024 - 23K bytes - Viewed (0) -
docs/de/docs/async.md
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. ---
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Sat Mar 30 18:06:16 UTC 2024 - 26.6K bytes - Viewed (0) -
docs/zh/docs/async.md
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;
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Apr 18 19:53:19 UTC 2024 - 21.1K bytes - Viewed (0)