State-of-the-art computing capabilities allow SCU students and faculty to analyze and visualize data in new ways.
By Ally O'Connor '20
As more and more research in the humanities, social sciences, and in STEM fields like biology and engineering come to utilize larger and larger datasets, Santa Clara University’s need for centralized, integrated, and powerful computer capabilities has become necessary. Working with both the College of Arts and Sciences and the School of Engineering, program manager Shuyuan Chen is developing the new Wiegand Advanced Visualization Environment (WAVE) program with the hopes of enhancing computation speed for SCU research and classroom instruction.
According to Chen, the system consists of two major parts: the computing cluster for massive parallel and/or memory intensive computations; and visualization, which includes augmented reality (AR), virtual reality (VR), human-computer interface/interaction (HCI), and improved information presentation.
Using neuroscience as an example of this improved information presentation, Chen says, “If you take the neuron and want to understand it better, WAVE could help. It can run the numbers and model the communication between neurons to see what the passage of those neural messages looks like. It will model all of the possibilities in a short period of time.”
Neuroscience isn’t the only area on campus that will benefit from this new program; it can be adapted and utilized in many ways. For example, within the fine arts, the WAVE space could synthesize a combination of sound inputs, creating a visual representation of an audible piece.
Thanks to funding from the Wiegand Foundation, SCU has been able to acquire the materials — High-Performance Computing Cluster Servers — needed to kickstart this project, which Chen is aiming to have fully functional by the year 2020. In keeping with SCU’s Integrated Strategic Plan “Santa Clara 2020,” this funding allows the University to continue to enhance its software and overall computing ability by activating these cluster servers that power the WAVE program.
“There is a lot to learn with WAVE,” says Chen, “but it is great to be in this point of discovery.” Once WAVE is fully operational, Chen is interested in exploring how the University community will put it to use.