Different Approaches to Distributed Compilation

J. Gattermayer, P. Tvrdík
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引用次数: 4

Abstract

Source code compiling is a non-trivial task that requires many computing resources. As a software project grows, its build time increases and debugging on a single computer becomes more and more time consuming task. An obvious solution would be a dedicated cluster acting as a build farm, where developers can send their requests. But in most cases, this solution has a very low utilization of available computing resources which makes it very ineffective. Therefore, we have focused on non-dedicated clusters to perform distributed compilation, where we could use users' computers as nodes of a build farm. We compare two different approaches: distcc, which is an open-source program to distribute compilation of C/C++ code between several computers on a network and Clondike, which is a universal peer-to-peer cluster that is being developed at the Czech Technical University in Prague. A very complex task able to test deeply both systems is a compilation of a Linux Kernel with many config options. We have run this task on a cluster with up to 20 computers and have measured computing times and CPU loads. In this paper, we will present the results of this experiment that indicate the scalability and utilization of given resources in both systems. We also discuss the penalty of a generic solution over a task-specific one.
分布式编译的不同方法
源代码编译是一项需要大量计算资源的重要任务。随着软件项目的增长,其构建时间增加,在单台计算机上调试成为越来越耗时的任务。一个显而易见的解决方案是将专用集群用作构建场,开发人员可以在其中发送他们的请求。但是在大多数情况下,该解决方案对可用计算资源的利用率非常低,这使得它非常无效。因此,我们专注于非专用集群来执行分布式编译,我们可以使用用户的计算机作为构建场的节点。我们比较了两种不同的方法:distcc是一个开源程序,用于在网络上的几台计算机之间分发C/ c++代码编译;Clondike是一个通用的点对点集群,由布拉格的捷克技术大学开发。能够深入测试两个系统的一个非常复杂的任务是编译一个带有许多配置选项的Linux内核。我们在一个最多有20台计算机的集群上运行这个任务,并测量了计算时间和CPU负载。在本文中,我们将展示该实验的结果,表明两个系统中给定资源的可扩展性和利用率。我们还讨论了通用解决方案相对于特定于任务的解决方案的缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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