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变得常见。然而，由于体系结构、编程模型和算法设计的复杂性，高效地对GPU进行编程仍然具有挑战性。该项目旨在开发一个框架，以识别GPU应用程序中的性能低效，并为代码优化提供直观的指导。智能优势包括三种新的分析技术：(A)多尺度分析，以了解单个GPU内核中的低效；(B)协调分析，以测量设备之间的低效数据移动；以及(C)差异分析，以查看具有不同执行配置的不同运行的低效。这三项分析的结合将给出完整的GPU应用程序性能图景，并帮助开发人员获得现代和新兴GPU的裸机性能。该项目将弥合GPU硬件架构和软件开发人员之间的知识鸿沟。该项目的成功将使生产代码的计算效率得到显著提高，从而有助于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。拟议的框架将引起工业界、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NSF的法定使命，并通过使用基金会的智力优势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.