一句话：提出 ValueExpert 工具，用于定位 GPU 应用中与值相关的性能低效。
现代通用 GPU 被广泛用于加速机器学习、高性能计算和自动驾驶等领域的应用，但 GPU 加速应用中仍普遍存在性能低效，阻碍其达到裸机性能。性能工具对理解复杂代码库中的低效至关重要，然而许多 GPU 性能工具虽能定位耗时代码并提供高层性能洞察，却忽略了一类重要问题——值相关低效。为此，论文提出 ValueExpert，一种用于定位 GPU 应用中值相关低效的新工具，其核心思路是探索应用中的值模式以发现此类低效。摘要未报告具体评估结果。
General-purpose GPUs have become common in modern computing systems to accelerate applications in many domains, including machine learning, high-performance computing, and autonomous driving. However, inefficiencies abound in GPU-accelerated applications, which prevent them from obtaining bare-metal performance. Performance tools play an important role in understanding performance inefficiencies in complex code bases. Many GPU performance tools pinpoint time-consuming code and provide high-level performance insights but overlook one important performance issue---value-related inefficiencies, which exist in many GPU code bases. In this paper, we present ValueExpert, a novel tool to pinpoint value-related inefficiencies in GPU applications.