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识别用于GPU性能调整和架构设计的遮光器子模式

Lin Zhao¹, Chai Kiat Yeo², Arijit Khan³

¹College of Computing and Data Science, Nanyang Technological University, Singapore, 639798, Singapore.

Scientific reports

|October 14, 2024

概括

ShaderAnalyzer使用图形挖掘和机器学习来分析低级别的GPU机器代码. 这有助于工程师找到和优化代码段,以提高GPU性能,即使使用机密的源代码.

科学领域:

计算机工程计算机工程
软件工程软件工程软件工程
人工智能的人工智能

背景情况:

图形处理单元 (GPU) 在现代技术中至关重要.
优化GPU性能需要分析应用程序代码,这通常是机密的,需要领域专业知识.

研究的目的:

介绍ShaderAnalyzer,这是一个用于分析GPU机器代码的新框架.
识别代码微调的机会,以提高GPU性能.
帮助工程师和硬件架构师进行性能优化和未来设计.

主要方法:

使用图形结构表示GPU机器代码.
应用图形挖掘技术来识别经常出现的子结构 (模式).
利用机器学习来预测和调查低效率的代码模式.

主要成果:

ShaderAnalyzer成功地识别了具有高性能调潜力的代码段.
该框架为软件优化和硬件设计提供了宝贵的见解.
由行业合作伙伴验证的实验结果证明了该解决方案的有效性.

结论:

ShaderAnalyzer为GPU代码分析和性能增强提供了一个端到端的解决方案.
该方法解决了与代码保密性和域知识要求相关的挑战.
该框架帮助工程师优化GPU性能,并为未来的硬件开发提供信息.

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