average parallelism degree

简明释义

平均并行度;

英英释义

例句

1.By analyzing the average parallelism degree, we can identify bottlenecks in the workflow.

通过分析平均平行度，我们可以识别工作流程中的瓶颈。

2.The researchers calculated the average parallelism degree to determine how similar the data sets were.

研究人员计算了平均平行度以确定数据集的相似性。

3.In our analysis, the average parallelism degree of the algorithms showed significant improvement over previous versions.

在我们的分析中，这些算法的平均平行度显示出比之前版本显著的改进。

4.The average parallelism degree can be affected by the hardware limitations of the system.

系统的硬件限制可能会影响平均平行度。

5.To optimize performance, we need to increase the average parallelism degree in our processing pipeline.

为了优化性能，我们需要提高处理流程中的平均平行度。

作文

In the realm of mathematics and computer science, the concept of parallelism plays a significant role in enhancing efficiency and performance. One particular measure that has garnered attention is the average parallelism degree, which refers to the average number of processes or tasks that can be executed simultaneously in a given system. Understanding this concept is crucial for optimizing algorithms and improving the overall throughput of operations. To illustrate the importance of the average parallelism degree, consider a scenario where a complex computation needs to be performed. If the computation can be divided into smaller, independent tasks, then these tasks can potentially be processed in parallel. The higher the average parallelism degree, the more tasks can be executed at the same time, leading to a significant reduction in the total computation time. This is particularly relevant in fields such as data processing, simulations, and large-scale computations, where time efficiency is paramount.Moreover, the average parallelism degree is not only applicable in theoretical contexts but also in practical applications. For instance, modern multi-core processors are designed to take advantage of parallelism by allowing multiple threads to run concurrently. In such cases, understanding the average parallelism degree helps developers optimize their code to ensure that it effectively utilizes the available cores, leading to better performance and resource management.Furthermore, the average parallelism degree can also impact the design of software systems. When architects and engineers design systems, they must consider how tasks will be distributed and whether the system can handle multiple operations simultaneously. A well-designed system with a high average parallelism degree can lead to smoother user experiences and faster response times, which is critical in today’s fast-paced digital environment.However, achieving a high average parallelism degree does come with its challenges. Not all tasks can be parallelized effectively, and there may be dependencies between tasks that hinder parallel execution. Therefore, it is essential to analyze the nature of the tasks involved and determine the best approach to maximize parallelism. Techniques such as task scheduling, load balancing, and resource allocation are vital in this regard.In conclusion, the average parallelism degree is a fundamental concept that influences the efficiency of computational processes across various domains. By understanding and optimizing this degree, we can significantly enhance the performance of systems and applications, ultimately leading to greater productivity and innovation. As technology continues to advance, the significance of parallelism will only grow, making it imperative for professionals in the field to grasp its implications thoroughly. This understanding will not only aid in the development of more efficient algorithms but will also contribute to the evolution of computing technologies as a whole.

在数学和计算机科学领域，平行性概念在提高效率和性能方面发挥着重要作用。其中一个引起关注的度量是平均并行度，它指的是在给定系统中可以同时执行的过程或任务的平均数量。理解这个概念对于优化算法和提高操作的整体吞吐量至关重要。为了说明平均并行度的重要性，考虑一个需要执行复杂计算的场景。如果计算可以分解为更小的独立任务，那么这些任务就可以并行处理。平均并行度越高，越多的任务可以同时执行，从而显著减少总计算时间。这在数据处理、模拟和大规模计算等领域尤其相关，在这些领域中，时间效率至关重要。此外，平均并行度不仅适用于理论背景，也适用于实际应用。例如，现代多核处理器被设计用于利用并行性，允许多个线程同时运行。在这种情况下，理解平均并行度有助于开发人员优化他们的代码，以确保有效利用可用核心，从而提高性能和资源管理。此外，平均并行度还会影响软件系统的设计。当架构师和工程师设计系统时，他们必须考虑任务如何分配，以及系统是否能够同时处理多个操作。一个设计良好的系统具有高平均并行度，可以带来更流畅的用户体验和更快的响应时间，这在当今快速发展的数字环境中至关重要。然而，实现高平均并行度确实面临一些挑战。并非所有任务都可以有效地并行化，任务之间可能存在依赖关系，阻碍并行执行。因此，分析所涉及任务的性质并确定最大化并行性的最佳方法至关重要。任务调度、负载均衡和资源分配等技术在这方面至关重要。总之，平均并行度是一个基本概念，影响着各个领域计算过程的效率。通过理解和优化这一度量，我们可以显著提高系统和应用程序的性能，最终促进更大的生产力和创新。随着技术的不断进步，并行性的意义将只会增加，因此，专业人士彻底掌握其影响是至关重要的。这种理解不仅有助于开发更高效的算法，还将促进计算技术的整体发展。