Collaborative Research: CNS Core: SMALL: DrGPU: Optimizing GPU Programs via Novel Profiling Techniques

图形处理单元（gpu）在现代计算系统中已经变得很常见。然而，由于架构、编程模型和算法设计的复杂性，对gpu进行高效编程仍然具有挑战性。该项目旨在开发一个框架来识别GPU应用程序中的性能低下，并为代码优化提供直观的指导。智能优点包括三种新的分析技术：(a)多尺度分析，以了解单个GPU内核内部的低效率，(b)协调分析，以测量设备之间的低效率数据移动，以及(c)差异分析，以查看不同执行配置下不同运行的低效率。这三种分析相结合，将提供GPU应用程序的完整性能图，并帮助开发人员获得现代和新兴GPU的裸机性能。这个项目将弥合GPU硬件架构和软件开发人员之间的知识鸿沟。这个项目的成功将显著提高生产代码的计算效率，并因此帮助保持各个领域的持续进步，例如，数据分析、高性能计算和人工智能。提议的框架将引起工业、研究机构和能源部国家实验室的广泛兴趣，以改进他们的代码库和增加系统吞吐量。此外，该项目的成果将被整合到课程规划和教育活动中，学生可以直接从中受益。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Graphics Processing Units (GPUs) have become common in modern computing systems. However, it remains challenging to efficiently program GPUs due to the complexity of architectures, programming models, and algorithm designs. This project aims to develop a framework to identify performance inefficiencies in GPU applications and provide intuitive guidance for code optimization. The intellectual merits include three novel analysis techniques: (a) multi-scale analysis to understand inefficiencies inside individual GPU kernels, (b) coordinated analysis to measure inefficient data movement between devices, and (c) differential analysis to view inefficiencies across different runs with different execution configurations. The combination of these three analyses will give a complete performance picture of GPU applications and help developers obtain the bare-metal performance in modern and emerging GPUs.This project will bridge the knowledge gap between GPU hardware architectures and software developers. The success of this project will enable significant enhancement of computing efficiency for production code, and hence help maintain a sustained advancement of various domains, e.g., data analytics, high-performance computing, and artificial intelligence. The proposed framework will draw broad interest from industry, research institutes, and the Department of Energy national laboratories for improving their code bases and increasing system throughputs. Moreover, the outcome of this project will be integrated into curriculum planning and educational activities, from which students can directly benefit.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.