execution dead time

简明释义

执行迟延时间

英英释义

Execution dead time refers to the period during which a process or task is not actively being executed or is idle, often due to waiting for resources, inputs, or other dependencies.

执行死时间是指在一个过程或任务未被积极执行或处于闲置状态的时间段，通常是由于等待资源、输入或其他依赖项而导致的。

例句

1.By analyzing the execution dead time 执行空闲时间, we can identify inefficiencies in our workflow.

通过分析执行空闲时间，我们可以识别工作流程中的低效之处。

2.The team implemented new strategies to minimize execution dead time 执行空闲时间 during project development.

团队实施了新策略，以最小化项目开发中的执行空闲时间。

3.The manufacturing process was delayed due to high execution dead time 执行空闲时间 between machine operations.

由于机器操作之间的高执行空闲时间，制造过程被延误。

4.During the audit, we discovered excessive execution dead time 执行空闲时间 in the assembly line.

在审计过程中，我们发现组装线存在过多的执行空闲时间。

5.Reducing execution dead time 执行空闲时间 can significantly improve overall productivity.

减少执行空闲时间可以显著提高整体生产力。

作文

In the realm of computer science and software development, the term execution dead time refers to periods during which a program or process is inactive or not performing any useful work. This concept is critically important when analyzing the performance of algorithms and systems, as it can significantly affect overall efficiency and user experience. Understanding execution dead time is essential for developers who aim to optimize their code and reduce latency in applications.To illustrate this point, consider a scenario where a program is designed to process data in batches. During the execution of this program, there may be instances where the system is waiting for input from an external source or waiting for resources to become available. These waiting periods contribute to what we define as execution dead time, as the CPU remains idle instead of executing further instructions. Such inefficiencies can lead to increased processing times and slower response rates, ultimately frustrating users and diminishing the application's effectiveness.Moreover, execution dead time can arise from various sources, including network delays, I/O operations, and synchronization issues among concurrent processes. For example, when multiple threads attempt to access shared resources, one thread may need to wait for another to release the resource, resulting in a halt in execution. This waiting period represents a significant portion of the execution dead time that can degrade system performance.To mitigate execution dead time, developers employ several strategies. One common approach is to implement asynchronous programming techniques, allowing the system to continue executing other tasks while waiting for time-consuming operations to complete. This method reduces idle time and enhances the responsiveness of applications. Additionally, optimizing algorithms to minimize the number of blocking operations can also help decrease execution dead time. By ensuring that processes have access to the necessary resources when needed, developers can streamline execution and improve performance.Another effective strategy involves profiling and monitoring applications to identify bottlenecks that contribute to execution dead time. By analyzing the execution flow and pinpointing areas where delays occur, developers can make informed decisions on where to focus their optimization efforts. Tools such as profilers and debuggers can provide valuable insights into the behavior of applications, helping developers to visualize and address sources of inefficiency.In conclusion, understanding execution dead time is crucial for anyone involved in software development and system optimization. By recognizing the factors that contribute to these inactive periods, developers can implement strategies to minimize them, leading to more efficient, responsive, and user-friendly applications. As technology continues to evolve, the importance of addressing execution dead time will only grow, making it an essential consideration in the design and implementation of modern software solutions.

在计算机科学和软件开发领域，术语执行死时间指的是程序或过程处于非活动状态或未执行任何有用工作的时间段。这个概念在分析算法和系统性能时至关重要，因为它会显著影响整体效率和用户体验。理解执行死时间对旨在优化代码和减少应用程序延迟的开发人员来说是必不可少的。为了说明这一点，考虑一个设计用于批量处理数据的程序。在该程序执行期间，可能会出现系统等待来自外部源的输入或等待资源变得可用的情况。这些等待期间导致我们所定义的执行死时间，因为CPU保持空闲而不是执行其他指令。这种低效会导致处理时间增加和响应速度变慢，最终使用户感到沮丧，降低应用程序的有效性。此外，执行死时间可以由多种来源引起，包括网络延迟、I/O操作和并发进程之间的同步问题。例如，当多个线程试图访问共享资源时，一个线程可能需要等待另一个线程释放资源，从而导致执行暂停。这段等待时间代表了可能降低系统性能的执行死时间的重要部分。为了缓解执行死时间，开发人员采用几种策略。一种常见的方法是实施异步编程技术，允许系统在等待耗时操作完成时继续执行其他任务。这种方法减少了空闲时间，提高了应用程序的响应能力。此外，优化算法以最小化阻塞操作的数量也可以帮助减少执行死时间。通过确保进程在需要时能够访问必要的资源，开发人员可以简化执行并提高性能。另一种有效策略涉及对应用程序进行剖析和监控，以识别导致执行死时间的瓶颈。通过分析执行流程并确定延迟发生的区域，开发人员可以明智地决定将优化工作集中在哪里。剖析器和调试器等工具可以提供有关应用程序行为的宝贵见解，帮助开发人员可视化和解决低效的来源。总之，理解执行死时间对任何参与软件开发和系统优化的人来说都是至关重要的。通过识别导致这些非活动期间的因素，开发人员可以实施策略来最小化它们，从而导致更高效、响应更快且用户友好的应用程序。随着技术的不断发展，解决执行死时间的重要性只会增加，使其成为现代软件解决方案设计和实施中的一个重要考虑因素。