Associate Professor-
The advancement of semiconductor miniaturization technology has been restricted, leading to a slowdown in the performance improvement and energy efficiency of general-purpose processors. Meanwhile, the demand for computational power in computer systems continues to grow rapidly, driven by recent advancements in generative AI and big data analytics. As a result, using accelerators, such as GPUs, that can efficiently handle specific types of computation is becoming a common way to address this demand. This paradigm shift brings about a range of challenges, including efficient hardware design methods leveraging advanced CMOS process technologies and the need for novel compiler techniques that fully exploit the capabilities of accelerators. Let us work together to tackle these challenges and drive the realization of next-generation computing systems.