CLC: A cross-level program characterization method

IF 1 4区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Performance Evaluation Pub Date : 2023-09-01 DOI:10.1016/j.peva.2023.102354

Li Tang, Scott Pakin

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Abstract

Characterization of program execution plays a key role in performance improvement. There are numerous transformations applied to each step that a program takes on its lowering from source code to a compiler intermediate representation to machine language to microarchitecture-specific execution. The unpredictable benefit of each transformation step could lead a notionally superior algorithm to exhibit inferior performance once actually run, and it can be hard to discern which step in the transformation path contradicted the code developer’s assumptions.

Conventional approaches to program-execution characterization consider the behavior after only a single one of those steps, which limits the information that can be provided to the user. To help address the issue of myopic views of program execution, this paper presents a novel cross-level characterization approach for understanding the behavior of program execution at different levels in the process of writing, compiling, and running a program. We show that this approach provides a richer view of the sources of performance gains and losses and helps identify program execution in a more accurate manner.

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CLC:一种跨层次的程序表征方法

程序执行的特征化在性能改进中起着关键作用。程序从源代码到编译器中间表示，从机器语言到微体系结构特定的执行，每一步都有许多转换。每个转换步骤的不可预测的好处可能会导致一个理论上优越的算法在实际运行后表现出较差的性能，而且很难辨别转换路径中的哪一步与代码开发人员的假设相矛盾。程序执行特征化的传统方法只考虑这些步骤中的一个步骤之后的行为，这限制了可以提供给用户的信息。为了帮助解决程序执行的短视问题，本文提出了一种新的跨级别表征方法，用于理解程序在编写、编译和运行过程中不同级别的执行行为。我们表明，这种方法提供了对性能增益和损失来源的更丰富的视图，并有助于以更准确的方式识别程序执行。

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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来源期刊

Performance Evaluation 工程技术-计算机：理论方法

CiteScore

3.10

自引率

0.00%

发文量

审稿时长

24 days

期刊介绍： Performance Evaluation functions as a leading journal in the area of modeling, measurement, and evaluation of performance aspects of computing and communication systems. As such, it aims to present a balanced and complete view of the entire Performance Evaluation profession. Hence, the journal is interested in papers that focus on one or more of the following dimensions: -Define new performance evaluation tools, including measurement and monitoring tools as well as modeling and analytic techniques -Provide new insights into the performance of computing and communication systems -Introduce new application areas where performance evaluation tools can play an important role and creative new uses for performance evaluation tools. More specifically, common application areas of interest include the performance of: -Resource allocation and control methods and algorithms (e.g. routing and flow control in networks, bandwidth allocation, processor scheduling, memory management) -System architecture, design and implementation -Cognitive radio -VANETs -Social networks and media -Energy efficient ICT -Energy harvesting -Data centers -Data centric networks -System reliability -System tuning and capacity planning -Wireless and sensor networks -Autonomic and self-organizing systems -Embedded systems -Network science