Please note: This PhD seminar will take place in DC 1304 and virtually.
Rosina Kharal, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Trevor Brown
Over the past decade, the field of computational science has experienced significant advancements, largely fueled by the evolution of parallel computing. Utilizing the parallel processing capabilities of GPUs has facilitated previously inconceivable gains in computationally demanding tasks. Initially designed for graphics rendering, GPUs now form the foundation of vast domains such as data analytics and machine learning. Currently, we are navigating through another transformation led by GPUs in the realm of high-performance computing (HPC).
Recently, companies like NVIDIA and AMD have launched GPU acceleration hardware to substantially enhance real-time ray tracing capabilities. These specialized components, known as Accelerated Ray Tracing Cores (RTX cores), are now available on consumer-grade GPUs, including the NVIDIA GeForce RTX series and the Titan RTX series. Initially aimed at accelerating ray tracing for graphics, these cores have begun attracting research interest for a variety of other applications.
This seminar will shed light on the progression and potential of accelerated ray tracing technology, from its roots in graphics to its expanding role in non-graphical applications. We will explore how this technology can work alongside existing GPU multiprocessors to foster new developments in computational science. The session’s primary goal is to provide a deeper understanding of RTX technology, including an analysis of existing research where RTX is applied to non-graphical tasks, and a focus on current work in progress.