论文标题
朱莉娅进行高能量物理分析的表现
Performance of Julia for High Energy Physics Analyses
论文作者
论文摘要
我们认为，Julia编程语言是Python和C ++实施的一种令人信服的替代方法，用于高能物理学中的常见数据分析工作流程。我们将Julia不同工作流的实施速度与Python和C ++的实施速度进行了比较。我们的研究表明，朱莉娅的实施对于由计算负载而不是数据访问主导的任务具有竞争力。对于以数据访问为主的工作，我们演示了一个具有并发文件读取和并行数据处理的应用程序。
We argue that the Julia programming language is a compelling alternative to implementations in Python and C++ for common data analysis workflows in high energy physics. We compare the speed of implementations of different workflows in Julia with those in Python and C++. Our studies show that the Julia implementations are competitive for tasks that are dominated by computational load rather than data access. For work that is dominated by data access, we demonstrate an application with concurrent file reading and parallel data processing.
