pipelining

简明释义

英[ˈpaɪplaɪnɪŋ]美[ˈpaɪplaɪnɪŋ]

n. 流水线；管道安装

v. 用管道输送；应用流水线技术设计（pipeline 的 ing 形式）

英英释义

单词用法

同义词

反义词

例句

1.The work speed is optimized through the pipelining design, register matching or key path.

速度优化通过流水线设计、寄存器配平或关键路径实现。

2.Pipelining is one of the main transportation ways for modern petroleum products.

管道输送是现代油品主要运输方式之一。

3.Common table expressions (the WITH clause) allow efficient pipelining of data-change-operations.

公共表表达式(with子句)允许数据更新操作的高效管道。

4.The team used a trick called "pipelining" in which sensors acted as message-passing relays for other nearby sensors.

这支团队玩起一个名叫“流水线”的把戏，让传感器扮演信息传递员的角色把信息传到另外那些在附近的传感器中。

5.The pipelining technique described above is an example of using asynchronous processing to enhance performance.

本文介绍的流水线技术是使用异步处理以提高性能的示例。

6.This technique is called software pipelining, and this code only loses 2 cycles to stalls.

这种技术称为软件流水线(soft ware pipelining)，这段代码只损失了2个周期在暂停上。

7.The software development team is using pipelining to improve the efficiency of their code compilation process.

软件开发团队正在使用流水线处理来提高代码编译过程的效率。

8.In modern CPUs, pipelining allows multiple instructions to be processed simultaneously.

在现代CPU中，流水线处理允许多个指令同时处理。

9.The company implemented pipelining in their data processing to handle large datasets more effectively.

公司在数据处理中实施了流水线处理，以更有效地处理大型数据集。

10.Using pipelining, the manufacturing process can reduce wait times between stages.

通过使用流水线处理，制造过程可以减少各阶段之间的等待时间。

11.The video rendering software employs pipelining to enhance performance and speed up the output.

该视频渲染软件采用流水线处理来提升性能并加快输出速度。

作文

In the world of computer architecture, the concept of pipelining (流水线) plays a crucial role in enhancing the performance of processors. By breaking down the execution process into multiple stages, pipelining allows for overlapping instruction execution, which significantly increases the throughput of the CPU. This technique is akin to an assembly line in a factory, where different parts of a product are assembled simultaneously rather than sequentially. The stages of pipelining typically include instruction fetch, instruction decode, execution, memory access, and write back. Each of these stages can be completed in parallel for different instructions, leading to a more efficient use of the processor's resources. For instance, while one instruction is being executed, another can be decoded, and yet another can be fetched from memory. This concurrency reduces idle time and maximizes the utilization of the CPU. However, pipelining is not without its challenges. One major issue is known as data hazards, which occur when instructions depend on the results of previous instructions that have not yet completed. To mitigate this, various techniques such as forwarding and stalling are employed. Forwarding allows the CPU to use the result of an instruction before it is officially written back, while stalling introduces delays in the pipeline until the necessary data is available. Control hazards also pose a challenge in pipelining. These arise from branch instructions that alter the flow of execution. When a branch is taken, the pipeline may have already fetched several instructions that are no longer needed. Techniques such as branch prediction and delayed branching are used to address these issues, aiming to minimize the performance penalties associated with incorrect predictions. Despite these challenges, the benefits of pipelining are substantial. Modern processors often implement deep pipelines, allowing for even greater instruction throughput. This advancement has led to significant improvements in the performance of applications ranging from simple calculations to complex simulations and gaming environments. In conclusion, pipelining (流水线) is a fundamental concept in computer architecture that enhances the efficiency and speed of processors. By allowing multiple instructions to be processed simultaneously, it maximizes resource utilization and increases overall system performance. As technology continues to evolve, the importance of pipelining will only grow, pushing the boundaries of what is possible in computing.

在计算机架构的世界中，pipelining（流水线）这一概念在提升处理器性能方面发挥着至关重要的作用。通过将执行过程分解为多个阶段，pipelining 允许指令执行重叠，从而显著提高 CPU 的吞吐量。这一技术类似于工厂中的装配线，不同部分的产品可以同时组装，而不是依次进行。 pipelining 的各个阶段通常包括指令获取、指令解码、执行、内存访问和写回。每个阶段可以并行完成不同指令的处理，从而更有效地利用处理器资源。例如，当一条指令正在执行时，另一条可以被解码，而还有一条可以从内存中获取。这种并发性减少了空闲时间，最大化了 CPU 的利用率。 然而，pipelining 并非没有挑战。一个主要问题被称为数据冒险，当指令依赖于尚未完成的前一条指令的结果时，就会发生这种情况。为了缓解这个问题，采用了转发和停顿等各种技术。转发允许 CPU 在正式写回之前使用指令的结果，而停顿则在管道中引入延迟，直到所需的数据可用。 控制冒险也对 pipelining 构成挑战。这些问题源于改变执行流程的分支指令。当采取分支时，管道可能已经获取了几条不再需要的指令。分支预测和延迟分支等技术用于解决这些问题，旨在最小化与错误预测相关的性能损失。 尽管存在这些挑战，pipelining 的好处是巨大的。现代处理器通常实现深度管道，允许更高的指令吞吐量。这一进步使简单计算到复杂模拟和游戏环境等应用的性能显著提高。 总之，pipelining（流水线）是计算机架构中的一个基本概念，它提升了处理器的效率和速度。通过允许多条指令同时处理，它最大化了资源利用率，提高了整体系统性能。随着技术的不断发展，pipelining 的重要性只会增加，推动计算领域的可能性边界。