"Computer Engineering Research Prompts Bug Fixes, Updates to Major GPU Frameworks"
Graphical Processing Units (GPUs) are the driving force behind some of the most important topics in computer science today, including Artificial Intelligence (AI) and Machine Learning (ML). When major technology companies build their own GPUs for use in devices such as computers and mobile phones, testing must be performed to verify that software can operate securely and efficiently on various processors. Here is where assistant professor of computer science and engineering at the University of California, Santa Cruz, Tyler Sorensen, and his team of colleagues and student researchers come in. The team creates tests to guarantee that programming languages can operate correctly and safely on a variety of processors manufactured by different companies. This contributes to the general stability of the processors used in computers and mobile devices, which are being entrusted with more critical functions such as facial recognition. During the development and execution of these tests, major GPU bugs were found, resulting in modifications to an important GPU framework for programming web browsers. This article continues to discuss the research that prompted bug fixes and updates to GPU frameworks.