使用LAAB报告数学库安装的性能：概述
Performance Reporting of Mathematical Library Installations with LAAB - An Overview
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中文总结 AI 辅助
本文提出线性代数感知基准（LAAB）框架，定义性能报告的四个目标并介绍其设计，以系统评估和报告HPC系统数学库安装的性能，应对相关挑战。
中文摘要 AI 辅助
我们提出线性代数感知基准（Linear Algebra Aware Benchmarks, LAAB）框架，用于系统评估和报告高性能计算（HPC）系统上数学库安装的性能。数学库提供的操作接口是科学应用的计算基础模块，报告其性能对评估应用效率、估算计算时间需求以及准备资源分配请求至关重要。本文定义了性能报告的四个目标：1）可追溯性，将每份报告与精确的库安装及执行设置关联；2）兼容性，关联库操作性能与使用它们的上层科学应用；3）可靠性，支持在测量变异性存在时的解读；4）可访问性，确保报告、基准定义及相关元数据可用于检查和复现。随后我们介绍LAAB的设计，并展示其如何应对这些目标相关的挑战。
英文摘要
We present the Linear Algebra Aware Benchmarks (LAAB) framework for systematically assessing and reporting the performance of mathematical library installations on HPC systems. Mathematical libraries provide interfaces for operations that form the computational building blocks of scientific applications. Reporting their performance is important for assessing application efficiency, estimating compute-time requirements, and preparing resource-allocation requests. In this paper, we define four objectives for performance reporting: 1) traceability, linking each report to the exact library installation and execution settings; 2) compatibility, relating library-operation performance to higher-level scientific applications that use them; 3) reliability, supporting interpretation in the presence of measurement variability; and 4) accessibility, ensuring that reports, benchmark definitions, and relevant metadata are available for inspection and reproduction. We then present the design of LAAB and show how it addresses the challenges associated with these objectives.
