coprocessor

简明释义

英[ˌkəʊˈprəʊsesə(r)]美[ˈkoʊˌprɑːsesər]

n. [计] 协处理器

英英释义

单词用法

同义词

反义词

例句

1.This paper forwards a hardware solution based on NP and coprocessor which could be used in matching and lookup in application layer.

文章提出了一种基于网络处理器及应用层匹配查找协处理器的硬件解决方案，来实现高速网络环境的入侵检测。

2.A new address generator of the embeded SIMD coprocessor is introduced in this paper.

文章介绍了一种新的嵌入式SIM D协处理器地址产生器。

3.A novel16fixed point embedded SIMD array coprocessor which is used to solve low image comprehension is described in the paper.

论文介绍的SIM D协处理器是用于低层图像理解的16位定点嵌入式阵列处理器。

4.Based on the reconfigurable computing system, the thesis proposes RAC, a reconfigurable array coprocessor model, targeted at multimedia image applications.

本论文基于可重构计算系统提出了针对多媒体图像处理的可重构阵列协处理器模型RAC。

5.A GPU is a hardware coprocessor that accelerates computations for computer graphics applications.

GPU是一种硬件协处理器，可加速计算机图形应用程序的计算。

6.The FPGA was used as a coprocessor for image acquisition and pre-processing.

FPGA作为协处理器完成图像的采集和预处理。

7.The executing of the microcode function of the microprogram controller is very crucial to the instructions decoder in the coprocessor.

在协处理器中，微程序控制器的微码控制是协处理器指令译码的控制核心。

8.The ICA device is modeled after the shallow firmware mode of the 4758 Coprocessor.

ICA设备是照4758Coprocessor的shallow固件模式建模的。

9.The server's performance improved significantly after adding a coprocessor for data processing.

在服务器中添加一个用于数据处理的协处理器后，性能显著提升。

10.In many modern smartphones, a coprocessor is used to manage sensors efficiently.

在许多现代智能手机中，使用协处理器来高效管理传感器。

11.The new graphics card includes a dedicated coprocessor to enhance rendering speeds.

新显卡包含一个专用的协处理器以提高渲染速度。

12.The coprocessor in the gaming console allows for smoother gameplay and better graphics.

游戏控制台中的协处理器可实现更流畅的游戏体验和更好的图形效果。

13.Some machine learning applications benefit from a specialized coprocessor for faster computation.

一些机器学习应用受益于专用的协处理器以实现更快的计算。

作文

In the world of computing, the term coprocessor refers to a secondary processor that assists the primary processor in executing tasks. This concept has been pivotal in enhancing the performance and efficiency of computer systems. A coprocessor can handle specific types of computations, allowing the main CPU to focus on other processes. For instance, graphics processing units (GPUs) serve as coprocessors for rendering images and videos, significantly improving the speed and quality of visual outputs. This division of labor is particularly crucial in applications that require heavy computational power, such as video games, scientific simulations, and machine learning algorithms.The evolution of coprocessors can be traced back to the early days of computing when dedicated hardware was designed to perform specific functions more efficiently than general-purpose processors. As technology advanced, the role of coprocessors expanded beyond simple arithmetic operations to include complex tasks like floating-point calculations, cryptographic functions, and even artificial intelligence processing.One of the most well-known examples of a coprocessor is the math coprocessor, which was commonly used in personal computers during the late 1980s and early 1990s. These specialized chips were designed to handle floating-point arithmetic, which is essential for scientific calculations and graphical computations. By offloading these tasks to a coprocessor, the main CPU could operate more efficiently, leading to faster overall performance.Today, modern computing systems often incorporate multiple coprocessors to maximize their capabilities. For example, many laptops and desktops feature both a CPU and a GPU, with the latter acting as a coprocessor for graphics-related tasks. Additionally, advancements in parallel computing have led to the development of specialized coprocessors like tensor processing units (TPUs), which are optimized for machine learning workloads. These innovations highlight the importance of coprocessors in pushing the boundaries of what computers can achieve.The integration of coprocessors into computing architectures has also paved the way for new programming paradigms. Developers are now tasked with optimizing their code to take advantage of the parallel processing capabilities offered by coprocessors. This shift has led to the emergence of frameworks and libraries designed specifically for leveraging the power of coprocessors, such as CUDA for NVIDIA GPUs and OpenCL for various hardware platforms. By harnessing the unique strengths of coprocessors, developers can create more efficient and responsive applications.In conclusion, the role of the coprocessor in modern computing cannot be overstated. As technology continues to evolve, coprocessors will play an increasingly vital role in enhancing the performance of computer systems. From graphics rendering to machine learning, the ability to delegate specific tasks to coprocessors allows for greater efficiency and innovation in software development. Understanding the functionality and significance of coprocessors is essential for anyone looking to delve deeper into the field of computer science and engineering. As we move forward, the collaboration between CPUs and coprocessors will undoubtedly shape the future of computing, enabling us to tackle more complex challenges and unlock new possibilities in technology.

在计算机领域，术语coprocessor指的是一个辅助主处理器执行任务的次级处理器。这个概念在提升计算机系统的性能和效率方面至关重要。coprocessor可以处理特定类型的计算，从而使主CPU能够专注于其他过程。例如，图形处理单元（GPU）作为coprocessor用于渲染图像和视频，显著提高了视觉输出的速度和质量。这种劳动分工在需要大量计算能力的应用中尤为重要，例如视频游戏、科学模拟和机器学习算法。coprocessor的演变可以追溯到计算机早期，当时设计了专用硬件以比通用处理器更有效地执行特定功能。随着技术的进步，coprocessor的角色从简单的算术运算扩展到包括复杂任务，如浮点计算、加密功能，甚至人工智能处理。最著名的coprocessor之一是数学协处理器，它在1980年代末和1990年代初的个人计算机中广泛使用。这些专用芯片旨在处理浮点算术，这是科学计算和图形计算所必需的。通过将这些任务卸载到coprocessor上，主CPU可以更高效地运行，从而提高整体性能。如今，现代计算机系统通常集成多个coprocessor以最大化其能力。例如，许多笔记本电脑和台式机配备了CPU和GPU，后者作为图形相关任务的coprocessor。此外，平行计算的进步导致了专用coprocessor的开发，如张量处理单元（TPU），它们针对机器学习工作负载进行了优化。这些创新突显了coprocessor在推动计算机能力边界方面的重要性。将coprocessor集成到计算架构中还为新的编程范式铺平了道路。开发人员现在需要优化他们的代码，以利用coprocessor提供的并行处理能力。这一转变导致了专门为利用coprocessor的强大功能而设计的框架和库的出现，例如NVIDIA GPU的CUDA和各种硬件平台的OpenCL。通过利用coprocessor的独特优势，开发人员可以创建更高效和响应迅速的应用程序。总之，coprocessor在现代计算中的作用不容小觑。随着技术的不断发展，coprocessor将在提升计算机系统性能方面发挥越来越重要的作用。从图形渲染到机器学习，将特定任务委托给coprocessor的能力允许更大的效率和软件开发的创新。理解coprocessor的功能和重要性对于任何希望深入计算机科学和工程领域的人来说都是必不可少的。随着我们向前发展，CPU与coprocessor之间的协作无疑将塑造计算的未来，使我们能够应对更复杂的挑战并在技术上解锁新的可能性。